Post on 05-Feb-2023
THE DEMOCRATIC BENEFITS OF CENTRALIZED INSTITUTIONS IN GHANA
By
JENNIFER C. BOYLAN
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOLOF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2016
ACKNOWLEDGMENTS
During my graduate school career, I received institutional, funding, academic and research
support from a wide variety of organizations and individuals.
First, I would like to thank the institutional support I received from the Department of
Political Science and the Center for African Studies at the University of Florida (UF) for their
formative roles in my graduate training, for inviting leading-edge scholars to present their
research on campus, and for seeking out funding opportunities from which graduate students
like myself have benefited. My doctoral education and research was funded by the David L.
Boren Fellowship, UF Department of Political Science, UF Center for African Studies, UF
Center for International Business Education & Research (CIBER), and the African Studies
Center at Michigan State University. Through these opportunities I was able to complete over
16 months of research across 3 trips to Ghana.
For my academic training, I would like to thank my dissertation advisor, Michael Bernhard,
and my other committee members (Ben Smith, Staffan Lindberg, Brenda Chalfin and
Badredine Arfi) for their encouraging, detailed, critical, and innovative remarks throughout
the development and production of my dissertation project. I also need to thank my Akan-Twi
teachers, particularly James Essegbey, Levi Ofoe, Patience Asare, Forster Asare Kena, and
Emmanuel Kofi Amo Ofori, for over 4 years of language training.
Many, many thanks to all those who assisted me in the completion of my research in
Ghana. The following institutions were of particular help: Ghana Statistical Services, the
Center for Democratic Development (Ghana-CDD), the Parliament of Ghana, the Electoral
Commission (EC), the Ministry of Local Government and Rural Development (MLGRD), the
M/M/DCE offices and staff in each of the six districts in which surveys were conducted, as well
as the Members of Parliament, traditional leaders, assemblypersons, unit committee persons,
and any other individuals who allowed me to interview them as part of this research. I would
also like to thank the following individuals for their help in the completion of this project: my
survey project manager JoJo Baiden, David Kombat, Patrick Adzovor, Juliana Ama Kplorfia,
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Prof. E. Gyimah-Boadi, Franklin Oduro, James Adimah, George Kagya-Agyemang, Benedict
Fiifi Appiah, Yaw Opoku, Edward Takyi, James Atikpo, Anthony Agboga, Godwin Keteku,
Chester Fiagbe, George Atta Quainoo, and each of the other surveyor assistants.
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TABLE OF CONTENTS
page
ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
CHAPTER
1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.1 The Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201.2 The Proposed Solution: National and sub-National Competition . . . . . . . . 211.3 Dominant Party Politics, Neopatrimonialism, and Ethnic Voting . . . . . . . . 22
1.3.1 Elections and the Development of Dominant Party Politics . . . . . . . 221.3.2 Addressing Neopatrimonial Logics . . . . . . . . . . . . . . . . . . . . 241.3.3 The Durability of Ethnic Voting . . . . . . . . . . . . . . . . . . . . . 26
1.3.3.1 The rationality of voting ethnically . . . . . . . . . . . . . . 271.3.3.2 But why is ethnic voting bad? . . . . . . . . . . . . . . . . . 29
1.4 How Effective National-Level Competition Develops in Divided Societies . . . . 301.4.1 Credible Oppositions . . . . . . . . . . . . . . . . . . . . . . . . . . . 301.4.2 Majoritarian Electoral Systems . . . . . . . . . . . . . . . . . . . . . . 32
1.5 Taking the Effects of Institutionalized National and Sub-National Competitionto Ghana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331.5.1 Majoritarian Electoral Systems in Ghana . . . . . . . . . . . . . . . . . 331.5.2 Ghana’s Centralized System of Local Government . . . . . . . . . . . . 34
1.6 Competing Explanations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361.6.1 Democratization-via-Elections . . . . . . . . . . . . . . . . . . . . . . 361.6.2 Democratization-via-Economic Growth . . . . . . . . . . . . . . . . . 38
1.7 Outline of Chapters to Come . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2 GHANA’S HISTORY OF CENTRALIZATION AND ETHNIC POLITICS . . . . . . 45
2.1 The Argument . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 462.2 Pre-Colonial Ethnicity and Colonial Rule . . . . . . . . . . . . . . . . . . . . 47
2.2.1 Ethnicity, Chiefs and Regional Identities . . . . . . . . . . . . . . . . . 472.2.2 The Educated Elite Response in the 1940’s and 1950’s . . . . . . . . . 49
2.3 Post-Colonial Centralization and the Ethnic Response . . . . . . . . . . . . . 512.3.1 CPP versus NLM in the Post-1951 Election Period . . . . . . . . . . . 512.3.2 The Post-Independence CPP Regime . . . . . . . . . . . . . . . . . . 562.3.3 The NLC and the 1966 Coup . . . . . . . . . . . . . . . . . . . . . . 572.3.4 Busia and the Progress Party (PP) . . . . . . . . . . . . . . . . . . . 592.3.5 Acheampong, the NRC and SMC-I . . . . . . . . . . . . . . . . . . . . 62
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2.3.6 Akuffo and the SMC-II . . . . . . . . . . . . . . . . . . . . . . . . . . 642.3.7 Rawlings-I and Limann . . . . . . . . . . . . . . . . . . . . . . . . . . 662.3.8 Rawlings-II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
2.4 Ethnic Voting in the Fourth Republic . . . . . . . . . . . . . . . . . . . . . . 722.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3 GHANA’S CENTRALIZED SYSTEM OF LOCAL GOVERNMENT & THE POWEROF THE DISTRICT CHIEF EXECUTIVE . . . . . . . . . . . . . . . . . . . . . . . 76
3.1 An Overview of Ghana’s System of Local Government . . . . . . . . . . . . . 773.2 District Assembly Authority & Revenue Sources . . . . . . . . . . . . . . . . 82
3.2.1 District Assembly Authority . . . . . . . . . . . . . . . . . . . . . . . 833.2.2 District Assembly Revenue . . . . . . . . . . . . . . . . . . . . . . . . 86
3.3 The Relationship Between MPs and DCEs . . . . . . . . . . . . . . . . . . . 893.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4 ECOLOGICAL INFERENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.1 The Application of Ecological Inference Tools to Ghana . . . . . . . . . . . . 974.2 Ethnic Voting in Ghana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1014.3 The Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1034.4 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1064.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
4.5.1 Method of Bounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1094.5.2 Multinomial-Dirichlet Models . . . . . . . . . . . . . . . . . . . . . . 110
4.5.2.1 Core political party supporters . . . . . . . . . . . . . . . . . 1104.5.2.2 Peripheral political party supporters . . . . . . . . . . . . . . 1114.5.2.3 Unincorporated groups with mixed voting patterns . . . . . . 115
4.6 Presidential Kingmakers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1164.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
5 THE INSTITUTIONALIZATION OF LOCAL-LEVEL COMPETITION IN GHANA . 155
5.1 Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1575.2 Model Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.2.1 Dependent Variable and Primary Independent Variable . . . . . . . . . 1605.2.2 Controlling for Structural Conditions Impacting MP-DCE Relationships 1615.2.3 Controlling for Structural Conditions Impacting Local Politics . . . . . 162
5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1645.3.1 2000 Elections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1655.3.2 2000 Presidential Runoff Elections . . . . . . . . . . . . . . . . . . . . 1665.3.3 2004 Elections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1665.3.4 2008 Elections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1675.3.5 2008 Presidential Runoff Elections . . . . . . . . . . . . . . . . . . . . 1685.3.6 2012 Elections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
5.4 Alternative Explanations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1705.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
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6 SURVEY ANALYSIS OF INDIVIDUALS’ VOTES . . . . . . . . . . . . . . . . . . . 191
6.1 General Conclusions from Chapter 6 . . . . . . . . . . . . . . . . . . . . . . . 1936.2 The Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1956.3 The District Pairs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
6.3.1 NPP Strongholds: Bosome Freho & Birim South . . . . . . . . . . . . 1976.3.2 NDC Strongholds: Adaklu Anyigbe & Ketu South . . . . . . . . . . . 1986.3.3 Mfantsiman & Asikuma Odoben Brakwa . . . . . . . . . . . . . . . . 199
6.4 Qualitative Explanation of District-Level Politics . . . . . . . . . . . . . . . . 1996.4.1 Bosome Freho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1996.4.2 Birim South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2016.4.3 Adaklu Anyigbe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2036.4.4 Ketu South . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2056.4.5 Mfantsiman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2086.4.6 Asikuma Odoben Brakwa . . . . . . . . . . . . . . . . . . . . . . . . 210
6.5 Survey Analysis: Political Knowledge and Behavior . . . . . . . . . . . . . . . 2126.5.1 Biggest Reasons for Your Vote and Votes in the Community . . . . . . 213
6.5.1.1 Overall results . . . . . . . . . . . . . . . . . . . . . . . . . 2136.5.1.2 Within district pairs . . . . . . . . . . . . . . . . . . . . . . 2156.5.1.3 District-by-district analysis . . . . . . . . . . . . . . . . . . . 216
6.5.2 Identifying NDC and NPP Ideologies . . . . . . . . . . . . . . . . . . . 2176.5.2.1 The NDC ideology . . . . . . . . . . . . . . . . . . . . . . . 2186.5.2.2 The NPP ideology . . . . . . . . . . . . . . . . . . . . . . . 2196.5.2.3 Within district pairs . . . . . . . . . . . . . . . . . . . . . . 2206.5.2.4 District-by-district analysis . . . . . . . . . . . . . . . . . . . 222
6.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
7 PREDICTING RESPONDENTS’ VOTES AND SWING-VOTING . . . . . . . . . . 261
7.1 Predicting Votes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2637.1.1 2004 Presidential and Parliamentary Elections . . . . . . . . . . . . . . 2657.1.2 2008 Presidential and Parliamentary Elections . . . . . . . . . . . . . . 2687.1.3 2012 Presidential and Parliamentary Elections . . . . . . . . . . . . . . 271
7.2 Who Are The Swing Voters? . . . . . . . . . . . . . . . . . . . . . . . . . . 2737.2.1 Demographic Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . 2737.2.2 Logit Models Predicting Swing Voters . . . . . . . . . . . . . . . . . . 275
7.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280
8 SURVEY EXPERIMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310
8.1 Identity Bias Voting Experiment . . . . . . . . . . . . . . . . . . . . . . . . . 3128.1.1 Linear Regressions Predicting Candidate Ratings . . . . . . . . . . . . 3158.1.2 Logistic Regressions Predicting Candidate Votes . . . . . . . . . . . . 3198.1.3 Categorical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
8.2 List Experiments to Hide Undemocratic Beliefs/Behaviors . . . . . . . . . . . 3278.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
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9 CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354
9.1 The Mixed-Methods Research Design . . . . . . . . . . . . . . . . . . . . . . 3559.2 Contributions to the Literature . . . . . . . . . . . . . . . . . . . . . . . . . 358
9.2.1 Contributions to Democratization Theory . . . . . . . . . . . . . . . . 3599.2.2 Contributions to Ethnic Politics . . . . . . . . . . . . . . . . . . . . . 362
9.3 Moving Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365
APPENDIX
A VOTING PATTERNS BY TRIBE AND ETHNO-LINGUISTIC GROUP . . . . . . . 368
B METHODS OF BOUNDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375
C ECOLOGICAL INFERENCE RESULTS . . . . . . . . . . . . . . . . . . . . . . . . 419
D SURVEY: MISSING RESPONSE BIAS CHECK . . . . . . . . . . . . . . . . . . . . 444
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445
BIOGRAPHICAL SKETCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 462
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LIST OF TABLES
Table page
1-1 Ghana’s income share held by what population percentage . . . . . . . . . . . . . . 44
3-1 District types (1996-2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4-1 Ghana’s ethno-linguistic groups and tribes . . . . . . . . . . . . . . . . . . . . . . 121
4-2 Asante bounds - Amansie West District . . . . . . . . . . . . . . . . . . . . . . . . 122
5-1 Constituencies under analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
5-2 Changes in party votes: 2000 - 1996 . . . . . . . . . . . . . . . . . . . . . . . . . 177
5-3 Changes in party votes: 2000 Pres. Runoff - 2000 Pres. Election . . . . . . . . . . 179
5-4 Changes in party votes: 2004 - 2000 (reg. election) . . . . . . . . . . . . . . . . . 181
5-5 Changes in party votes: 2008 - 2004 . . . . . . . . . . . . . . . . . . . . . . . . . 183
5-6 Changes in party votes: 2008 Pres. Runoff - 2008 Pres. Election . . . . . . . . . . 185
5-7 Changes in party votes: 2012 - 2008 (reg. election) . . . . . . . . . . . . . . . . . 187
5-8 Number of constituency-level political party strongholds (over 65% of the vote) . . . 189
5-9 Competitive and uncompetitive constituencies . . . . . . . . . . . . . . . . . . . . 190
6-1 Survey population stats vis-a-vis the 2010 Ghana Census . . . . . . . . . . . . . . . 227
6-2 Bosome Freho & Birim South structural characteristics . . . . . . . . . . . . . . . . 228
6-3 Bosome Freho & Birim South presidential vote patterns . . . . . . . . . . . . . . . 229
6-4 Bosome Freho & Birim South parliamentary vote patterns . . . . . . . . . . . . . . 230
6-5 Adaklu-Anyigbe & Ketu South structural characteristics . . . . . . . . . . . . . . . 231
6-6 Adaklu-Anyigbe & Ketu South presidential vote patterns . . . . . . . . . . . . . . . 232
6-7 Adaklu-Anyigbe & Ketu South parliamentary vote patterns . . . . . . . . . . . . . 233
6-8 Mfantsiman* & Asikuma-Odoben-Brakwa structural characteristics . . . . . . . . . 234
6-9 Mfantsiman* & Asikuma-Odoben-Brakwa presidential vote patterns . . . . . . . . . 235
6-10 Mfantsiman* & Asikuma-Odoben-Brakwa parliamentary vote patterns . . . . . . . . 236
6-11 Q9: Three biggest reasons for your vote for President . . . . . . . . . . . . . . . . 237
6-12 Q13: Three biggest reasons for your vote for MP . . . . . . . . . . . . . . . . . . . 238
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6-13 Q10: Biggest reason driving presidential votes within this community? . . . . . . . . 239
6-14 Q20: Do Ghana’s political parties have different ideologies? . . . . . . . . . . . . . 240
6-15 Q21: Components of the NDC’s political ideology . . . . . . . . . . . . . . . . . . 241
6-16 Q22: Components of the NPP’s political ideology . . . . . . . . . . . . . . . . . . 242
7-1 Predicting 2004 presidential votes . . . . . . . . . . . . . . . . . . . . . . . . . . . 283
7-2 Predicting 2004 parliamentary votes . . . . . . . . . . . . . . . . . . . . . . . . . . 285
7-3 Predicting 2008 presidential votes . . . . . . . . . . . . . . . . . . . . . . . . . . . 287
7-4 Predicting 2008 parliamentary votes . . . . . . . . . . . . . . . . . . . . . . . . . . 289
7-5 Predicting 2012 presidential votes . . . . . . . . . . . . . . . . . . . . . . . . . . . 291
7-6 Predicting 2012 parliamentary votes . . . . . . . . . . . . . . . . . . . . . . . . . . 293
7-7 Swing Voters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
7-8 Swing Voters2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296
7-9 Swing Voters3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297
7-10 Swing Voters4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298
7-11 Skirt-and-blouse swing voters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
7-12 Presidential election-to-election swing voters* . . . . . . . . . . . . . . . . . . . . 300
7-13 Parliamentary election-to-election swing voters* . . . . . . . . . . . . . . . . . . . 301
7-14 Logit model odds ratios- predicting swing voters across elections . . . . . . . . . . . 302
7-15 Logit model odds ratios- predicting swing voters across elections . . . . . . . . . . . 303
8-1 Average candidate ratings t-test per district . . . . . . . . . . . . . . . . . . . . . 333
8-2 Vote for candidate? t-tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334
8-3 Linear regression predicting candidate rating . . . . . . . . . . . . . . . . . . . . . 335
8-4 Linear regression predicting candidate rating . . . . . . . . . . . . . . . . . . . . . 336
8-5 Linear regression predicting candidate rating . . . . . . . . . . . . . . . . . . . . . 337
8-6 Logistic regressions (odds ratios) predicting votes for the candidate . . . . . . . . . 338
8-7 Logistic regressions (odds ratios) predicting votes for the candidate . . . . . . . . . 339
8-8 Logistic regressions (odds ratios) predicting votes for the candidate . . . . . . . . . 340
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8-9 Q29: Muslim president list experiment . . . . . . . . . . . . . . . . . . . . . . . . 341
8-10 Q29: Muslim president list experiment- by district . . . . . . . . . . . . . . . . . . 342
8-11 Clientelism list experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
8-12 Clientelism list experiments- 2012 Presidential election by district . . . . . . . . . . 344
8-13 Clientelism list experiments- 2012 Parliamentary elections by district . . . . . . . . . 345
8-14 Q34: Choose the Statement Which Is Closest To Your View . . . . . . . . . . . . . 346
A-1 Presidential Vote Margins by Tribe (1996-2012) . . . . . . . . . . . . . . . . . . . 369
A-2 Parliamentary Voting Margins by Tribe (1996-2012) . . . . . . . . . . . . . . . . . 371
A-3 Presidential Vote Margins by Ethnic Group (1996-2012) . . . . . . . . . . . . . . . 373
A-4 Parliamentary Vote Margins by Ethnic Group (1996-2012) . . . . . . . . . . . . . . 374
B-1 District-Level Bounds of Votes by Tribe - 1996 Presidential . . . . . . . . . . . . . 375
B-2 District-Level Bounds of Votes by Tribe - 1996 Parliamentary . . . . . . . . . . . . 378
B-3 District-Level Bounds of Votes by Tribe - 2000 Presidential . . . . . . . . . . . . . 381
B-4 District-Level Bounds of Votes by Tribe - 2000 Parliamentary . . . . . . . . . . . . 383
B-5 District-Level Bounds of Votes by Tribe - 2000 Pres. Runoff . . . . . . . . . . . . . 387
B-6 District-Level Bounds of Votes by Tribe - 2004 Presidential . . . . . . . . . . . . . 389
B-7 District-Level Bounds of Votes by Tribe - 2004 Parliamentary . . . . . . . . . . . . 393
B-8 District-Level Bounds of Votes by Tribe - 2008 Presidential . . . . . . . . . . . . . 398
B-9 District-Level Bounds of Votes by Tribe - 2008 Parliamentary . . . . . . . . . . . . 403
B-10 District-Level Bounds of Votes by Tribe - 2008 Presidential Runoff . . . . . . . . . 408
B-11 District-Level Bounds of Votes by Tribe - 2012 Presidential . . . . . . . . . . . . . 413
B-12 District-Level Bounds of Votes by Tribe - 2012 Parliamentary . . . . . . . . . . . . 416
C-1 2012 Presidential Vote Estimates by Tribe (urban covariate, flat priors . . . . . . . 420
C-2 2012 Parliamentary Results by Tribe (urban covariate, flat priors) . . . . . . . . . . 422
C-3 2008 Presidential Runoff Votes by Tribe (urban covariate, flat priors) . . . . . . . . 424
C-4 2008 Presidential Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . . 426
C-5 2008 Parliamentary Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . 428
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C-6 2004 Presidential Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . . 430
C-7 2004 Presidential Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . . 432
C-8 2000 Presidential Runoff Votes by Tribe (urban covariate, flat priors) . . . . . . . . 434
C-9 2000 Presidential Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . . 436
C-10 2000 Parliamentary Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . 438
C-11 1996 Presidential Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . . 440
C-12 1996 Parliamentary Votes by Tribe (urban covariate, flat priors) . . . . . . . . . . . 442
D-1 Logit Models Missing Response Bias Check . . . . . . . . . . . . . . . . . . . . . . 444
13
LIST OF FIGURES
Figure page
3-1 Overview of the system of local government in Ghana . . . . . . . . . . . . . . . . 93
4-1 Asante and Akyem presidential voting statistics . . . . . . . . . . . . . . . . . . . . 123
4-2 Ewe presidential and parliamentary voting statistics . . . . . . . . . . . . . . . . . . 124
4-3 Asante and Akyem parliamentary voting statistics . . . . . . . . . . . . . . . . . . 125
4-4 Ga and Mole Dagbani presidential voting statistics . . . . . . . . . . . . . . . . . . 126
4-5 Akan presidential and parliamentary voting statistics . . . . . . . . . . . . . . . . . 127
4-6 Ga and Mole Dagbani parliamentary voting statistics . . . . . . . . . . . . . . . . . 128
4-7 Bimoba and Sefwi presidential voting statistics . . . . . . . . . . . . . . . . . . . . 129
4-8 Dangme and Ga presidential voting statistics . . . . . . . . . . . . . . . . . . . . . 130
4-9 Dagarte and Dagomba presidential voting statistics . . . . . . . . . . . . . . . . . . 131
4-10 Nankansi and Kusasi presidential voting statistics . . . . . . . . . . . . . . . . . . . 132
4-11 Bimoba and Sefwi parliamentary voting statistics . . . . . . . . . . . . . . . . . . . 133
4-12 Dangme and Ga parliamentary voting statistics . . . . . . . . . . . . . . . . . . . . 134
4-13 Dagarte and Dagomba parliamentary voting statistics . . . . . . . . . . . . . . . . 135
4-14 Nankansi and Kusasi parliamentary voting statistics . . . . . . . . . . . . . . . . . 136
4-15 Akuapem and Boron presidential voting statistics . . . . . . . . . . . . . . . . . . . 137
4-16 Denkyira/Twifo and Ahanta presidential voting statistics . . . . . . . . . . . . . . . 138
4-17 Asen and Kwahu presidential voting statistics . . . . . . . . . . . . . . . . . . . . . 139
4-18 Akuapem and Boron parliamentary voting statistics . . . . . . . . . . . . . . . . . 140
4-19 Denkyira/Twifo and Ahanta parliamentary voting statistics . . . . . . . . . . . . . 141
4-20 Asen and Kwahu parliamentary voting statistics . . . . . . . . . . . . . . . . . . . 142
4-21 Guan, Gruma, and Grusi presidential voting statistics . . . . . . . . . . . . . . . . . 143
4-22 Mande and Ethnic Others’ presidential voting statistics . . . . . . . . . . . . . . . . 144
4-23 Guan, Gruma, and Grusi parliamentary voting statistics . . . . . . . . . . . . . . . 145
4-24 Mande and Ethnic Others’ parliamentary voting statistics . . . . . . . . . . . . . . 146
14
4-25 Chokosi, Kasena, and Builsa presidential voting statistics . . . . . . . . . . . . . . . 147
4-26 Guan3, Wasa, and Sisala presidential voting statistics . . . . . . . . . . . . . . . . 148
4-27 Fante, Nzema, and Guan5 presidential voting statistics . . . . . . . . . . . . . . . . 149
4-28 Mamprusi and Kokomba presidential voting statistics . . . . . . . . . . . . . . . . . 150
4-29 Chokosi, Kasena, and Builsa parliamentary voting statistics . . . . . . . . . . . . . 151
4-30 Guan3, Wasa, and Sisala parliamentary voting statistics . . . . . . . . . . . . . . . 152
4-31 Fante, Nzema, and Guan5 parliamentary voting statistics . . . . . . . . . . . . . . 153
4-32 Mamprusi and Kokomba parliamentary voting statistics . . . . . . . . . . . . . . . 154
6-1 Your vote for President- Bosome Freho and Birim South . . . . . . . . . . . . . . . 243
6-2 Your vote for President- Adaklu Anyigbe and Ketu South . . . . . . . . . . . . . . 244
6-3 Your vote for President- Mfantsiman and Asikuma Odoben Brakwa . . . . . . . . . 245
6-4 Your vote for MP- Bosome Freho and Birim South . . . . . . . . . . . . . . . . . . 246
6-5 Your vote for MP- Adaklu Anyigbe and Ketu South . . . . . . . . . . . . . . . . . 247
6-6 Your vote for MP- Mfantsiman and Asikuma Odoben Brakwa . . . . . . . . . . . . 248
6-7 Pres. votes within the community- Bosome Freho and Birim South . . . . . . . . . 249
6-8 Pres. votes within the community- Adaklu Anyigbe and Ketu South . . . . . . . . . 250
6-9 Pres. votes within the community- Mfantsiman and Asikuma Odoben Brakwa . . . 251
6-10 Do parties have different ideologies- Bosome Freho and Birim South . . . . . . . . . 252
6-11 Do parties have different ideologies- Adaklu Anyigbe and Ketu South . . . . . . . . 253
6-12 Do parties have different ideologies- Mfantsiman and Asikuma Odoben Brakwa . . . 254
6-13 NDC ideology- Bosome Freho and Birim South . . . . . . . . . . . . . . . . . . . . 255
6-14 NDC ideology- Adaklu Anyigbe and Ketu South . . . . . . . . . . . . . . . . . . . 256
6-15 NDC ideology- Mfantsiman and Asikuma Odoben Brakwa . . . . . . . . . . . . . . 257
6-16 NPP ideology- Bosome Freho and Birim South . . . . . . . . . . . . . . . . . . . . 258
6-17 NPP ideology- Adaklu Anyigbe and Ketu South . . . . . . . . . . . . . . . . . . . 259
6-18 NPP ideology- Mfantsiman and Asikuma Odoben Brakwa . . . . . . . . . . . . . . 260
15
7-1 Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2004 Pres. race . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
7-2 Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2004 Parl. races . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
7-3 Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2008 Pres. race . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306
7-4 Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2008 Parl. races . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
7-5 Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2012 Pres. race . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
7-6 Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2012 Parl. races . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309
8-1 Vote for candidate- all districts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
8-2 Vote for candidate- Bosome Freho . . . . . . . . . . . . . . . . . . . . . . . . . . 348
8-3 Vote for candidate- Birim South . . . . . . . . . . . . . . . . . . . . . . . . . . . . 349
8-4 Vote for candidate- Adaklu Anyigbe . . . . . . . . . . . . . . . . . . . . . . . . . . 350
8-5 Vote for candidate- Ketu South . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
8-6 Vote for candidate- Mfantsiman . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352
8-7 Vote for candidate- Asikuma Odoben Brakwa . . . . . . . . . . . . . . . . . . . . . 353
16
Abstract of Dissertation Presented to the Graduate Schoolof the University of Florida in Partial Fulfillment of theRequirements for the Degree of Doctor of Philosophy
THE DEMOCRATIC BENEFITS OF CENTRALIZED INSTITUTIONS IN GHANA
By
Jennifer C. Boylan
December 2016
Chair: Michael BernhardMajor: Political Science
Decentralization is widely believed to have positive democratic benefits in new democracies,
while centralized institutions are characterized as a nasty remnant of prior authoritarian
regimes. Using Ghana as a case study, this dissertation explores the contradiction in Ghana’s
famed democratic success despite its highly centralized political system. The findings show that
Ghana’s majoritarian electoral rules encourages turnover of power while its centralized system
introduces political competition at the local-level. Both institutional dynamics encourages more
responsive behavior on the part of politicians and offers citizens the opportunity to consider
information outside of ethnic identities when voting.
The historical background of Ghana’s institutions and their effects on ethnic politics is
presented as a backdrop to the current system of centralized government. Within the current
system, particular emphasis is placed on the relationship between the Presidentially-appointed
District Chief Executives and locally-elected Member(s) of Parliament. Ecological Inference
models are then used to prove increasing volatility in ethno-linguistic and tribal group
voting patterns. OLS regressions next demonstrate that vote volatility in Presidential and
Parliamentary elections significantly increased in areas with institutionally-promoted (i.e.
Unfriendly District Chief Executive-MP Pairs) high levels of competition as compared to low
levels of competition (Friendly District Chief Executive-MP Pairs). Finally, survey evidence
investigating individual vote motivations suggests that voters, and particularly swing voters,
17
increasingly rely on evaluative rationales in comparison to ethnic identity when making vote
decisions.
This work demonstrates the positive outcomes of centralization in the case of Ghana. In
making this argument, this dissertation also makes contributions to the study of ethnic politics
by investigating the political behavior of both ethno-linguistic and tribal groups, as well as to
research methods by combining a wide range of analytic tools (e.g., archival research, in-depth
interviews, survey research, Ecological Inference models, and other quantitative tools) to
ascertain historical, ethnographic, qualitative, and statistical aspects of the research question.
18
CHAPTER 1INTRODUCTION
The democratic record of African1 nations since the independence period has been
irregular at best. Promising democratic transitions in the 1950’s and 60’s were coupled with
strongly centralized governments and powerful individual heads of state. It was popularly
believed that African nations needed strong direction and tough leadership to drive out
structural divides the colonial governments had largely perpetuated and did little to remedy.
After independence was achieved, Africa’s founding fathers were typically reluctant
to leave office. In some instances, founding leaders effectively maintained their positions
(e.g., Kenyatta in Kenya, Houphouet-Boigny in Cote D’Ivoire, Kaunda in Zambia, Ahidjo in
Cameroon), while instability and power struggles quickly developed in others (e.g., Benin,
Democratic Republic of the Congo, Republic of the Congo, Sierra Leone, Ghana). Quite
distinct from the initial democratic hopes, the 1970’s and 1980’s were generally the African
decades of authoritarian or military rule and economic disaster. The effects of these democratic
and economic deficits were widespread and many nations’ economies still have not recovered.
Indeed, by 1999 Collier and Gunning (1999) found that 32 African countries were poorer than
they had been in 1980.
The breakup of the Soviet Union and the end of the Cold War in the late 1980’s and
early 1990’s led to a great deal of political change across the globe. African nations were
swept up in the third wave’s current and many democratic transitions were initiated. According
to Bratton and van de Walle (1994), “Between 1990 and 1993 more than half of Africa’s
fifty-two governments responded to domestic and international pressures by holding competitive
presidential or legislative elections” (453). Though the results of these democratic openings
were mixed, there have been important cases of persistent democratic progress: By 2011,
22 African states had held 3 to 5 uninterrupted rounds of multiparty elections (LeBas 2011,
1 Throughout the text I am primarily referring to sub-Saharan Africa when I reference Africa
19
8). Democratic institutions are taking hold in many African nations. But is good governance
following?
1.1 The Problem
African democracies are plagued by dominant party politics, neopatrimonialism, and
ethnic voting- all of which erode the quality of a democracy. These enduring problems for
African governments are inherently difficult to tackle. Still they are under-addressed by Western
scholars, development agencies and aid practitioners who are instead principally concerned
with the construction of democratic institutions, and particularly electoral institutions, when
promoting democratic governance.
The politicization of ethnicity is intimately related to these persistent obstacles to
improved democratic governance in African states. The development of ethnic identities
has roots in the trans-Atlantic slave trade. Though Africans had participated in global trade
networks prior to contact with Europeans, the introduction of guns and the high demand for
slaves revolutionized Africans’ role in this trade system. This dynamic and competitive trade
with Europeans, first dealing in slaves and later valuable natural resources and agricultural
products, made strict delineations of ‘insiders’ and ‘outsiders’ within African communities
politically useful.2 A perverse manipulation of ethnic group identities led to a differentiation
between ‘sons of the soil’ and outsiders at the local level (Geshiere 2009). These divides
have persisted, at least in part because the absence of formal-legal institutions of the state,
to use Adida’s (2014) term, forced populations to rely on ethnic systems of rule and trade
networks as the primary form of protection from unpredictable forces of the international
market. This perversion now manifests itself in an intense rivalry between a primordial and
civic public, Ekeh’s (1975) words, or between a personalized familial and ethnic-oriented
morality which dominates an impersonal and bureaucratic market-oriented ethic. As primordial
2 See Greene (1996), for instance, for a historical study of the development ofinsider/outsider statuses among the Anlo Ewe in southeastern Ghana.
20
morality overtakes civic morality, the resulting biased and particularistic politics have resulted
in dominant party politics, neopatrimonial political logics, and ethnic voting across Africa’s
democracies.
• Dominant Party Politics: Dominant party systems develop when one political partyconsistently (usually across 3 or more elections (Bogaards 2004)) wins the Presidency ora majority in Parliament and thereby selects the President/Prime Minister. In the contextof Africa’s ethnically divided nations, political parties typically base their support onethnic group membership rather than programmatic differences. Dominant party systemsthus develop when one political party’s ethnic base makes up a majority of the populationor consistently aligns with other ethnic groups to obtain a majority.
• Neopatrimonialsm: Characterized, “as an informal political system based on personalizedrule and organized through clientelistic networks of patronage, personal loyalty andcoercion” (Lindberg 2003, 123), neopatrimonial politics in African democracies tend tofollow ethnic, hometown, and familial networks. The general public loses as governmentfunds are directed toward biased and unproductive clientelistic networks rather thaneffective development strategies.
• Ethnic Voting: when the politicization of ethnicity dominates the politics of a nationsuch that voters use ethnic rationales as the basis for their vote decisions. Ethnic voting,as opposed to ideological, programmatic, retrospective and prospective voting, bringsless qualified politicians to power and does not hold politicians accountable for theirperformance in office.
1.2 The Proposed Solution: National and sub-National Competition
The central argument of this dissertation holds that Ghana has been able to either
dodge or significantly limit the problems of dominant party politics, neopatrimonial political
logics, and ethnic voting through institutionally-induced political competition. Ironically, the
centralized nature of Ghana’s institutions has been instrumental in generating legitimate
political competition at both the national level and particularly the sub-national level.
Democracy is a system for the management of conflict. Grounded in debates in political
theory, scholars interested in democratic institutions in multicultural settings theorize about
the impacts of institutions which incorporate diversity, through decentralized, federal,
parliamentary, and proportional systems of governance, as compared to centralized, unitary,
presidential, and majoritarian institutions which de-emphasize pluralism. However, I maintain
that an important additional condition is that democratic institutions also regulate ethnic
21
divisions. Regulation ensures that politicized cleavages become less potentially volatile and
disruptive of democracy over time. But regulation can also help to move a nation’s politics
away from ethnic politics and toward issue-based politics.
In the work that follows I will demonstrate how one case has been able to significantly
regulate the politicization of ethnicity through national and sub-national political competition.
Though Ghana’s highly centralized system bucks the democratization-via-decentralization
trend, the institutionalization of competitive political environments at both the national and
sub-national levels contribute to the de-politicization of national-level ethnic identities.
How do Ghana’s institutions undermine dominant party politics, neopatrimonial political
logics, and ethnic voting? Far from the norm for new democracies in Africa, Ghana’s national
level institutions compel political parties to appeal to cross-ethnic bases, while, at the local
level, well-funded appointees from the center strategically compete against locally-elected
Members of Parliament. By requiring political parties to seek support from multiple ethnic
groups in Presidential elections and exposing citizens to political competition at the local level,
Ghana’s democratic institutions weaken the cycle of dominant party politics, neopatrimonalism,
and ethnic voting that is so characteristic of African politics. While these problems are not yet
entirely resolved, the longevity of Ghana’s democratic regime, the absence of dominant party
politics at the national-level, and, as I will show, a depreciation of automatic voting based on
national-level ethnic groups is testimony to the success of its institutions. Furthermore, the
unusual way in which Ghana has achieved such democratic success is important. The evidence
offers proof that centralized institutions are an alternative option for fomenting healthy political
competition without the coordination struggles inherent within plurality systems which increase
the numbers of decision-makers.
1.3 Dominant Party Politics, Neopatrimonialism, and Ethnic Voting
1.3.1 Elections and the Development of Dominant Party Politics
A major component of the Democratization literature considers the factors which lead
to institutional democracies. The focus on initial democratic transitions and electoral
22
institutions, such that even democratic consolidation is largely defined by electoral factors,
biases explanations away from the factors which lead to effective democratic governance. One
problematic result of this focus on elections is the ability of dominant party politics to co-opt
a democratic regime. Political parties are crucial for the most effective functioning of modern
democratic regimes. As Kuenzi and Lambright (2001) write, “parties allow diverse groups to
pursue their interests in a peaceful, systematic fashion within a political system” (438). Indeed,
many scholars use between 1 and 3 peaceful transitions of power as a defining characteristic of
a consolidated democracy (Przeworski 1988; Huntington 1991), which inherently presupposes
the existence of multiple political parties. Dominant party political systems, however, develop
when a singular political party dominates national power through consecutive election victories
over time.
Dominant party political systems originate in different ways (Schedler 2013, 4) and
vary in terms of the free and fairness of their electoral environments. At best, the absence
of legitimate inter-party competition stifles the development of diverse competing political
platforms for consideration by the electorate when voting. At worst, freedoms of the press
and association are restricted, opposition leaders and their followers may be harassed and/or
imprisoned, and electoral processes come with voter suppression, unfair access to the media
on the part of the incumbent, and egregious instances of electoral fraud. Some examples of
dominant party politics, such as is the case within Botswana and South Africa, are actual
functioning democracies3 , but others merely offer the facade of democratic governance
with no real chance of an opposition leader or challenger to the President winning a national
election (e.g. Uganda, Rwanda, Zimbabwe, Tanzania, Cameroon).
3 Though these cases are not without their critiques: Botswana in terms of inclusion ofminorities (see Solway 2002; Nyamnjoh 2007) and South Africa in terms of corruption and theelectoral dominance of the ANC (Herbst 2005; Bassett and Clarke 2008; Gumede 2008).
23
In the context of African nations, dominant party politics develop by way of historical and
ethnic traditions which concentrate large portions of a country’s population within particular
party traditions. When one ethnic group makes up a sizable majority of the population in
a nation, it can be difficult for opposition parties without access to government coffers to
foment a campaign strong enough to overturn the incumbent party. Between ethnic voting,
neopatrimonial politics and the use of clientelistic networks to pay for votes, and the unfair
advantages incumbent parties derive from their access to power and money when campaigning,
it has proven difficult for many new African democracies to see a peaceful alternation of power.
To sum up, when we assume that democratic outcomes stem from democratic institutional
features, we ignore the ways in which democratic institutions, including free and fair elections,
fail to produce wholly democratic results. Put differently, this work questions the extent to
which elections can foment meaningful political competition, particularly in new democracies.
Along these same lines, democratization efforts should be oriented towards overcoming these
historical relationships between the state, political elites, and the citizenry in order to improve
the quality of democratic governance in African contexts.
1.3.2 Addressing Neopatrimonial Logics
A radicalization of Weber’s arbitrary, traditional, and personalistic concept of patrimonialism
(Weber [1922] 1978, chap 12-13), neopatrimonialism is the hybridization of both patrimonial
and legal-rational bureaucratic rule. As Erdmann and Engel (2007) explain, neopatrimonial rule
stems from a deeply rooted insecurity in the political system, as actors use both patrimonial
personal relations and legal-rational bureaucratic rules to overcome this insecurity. Similar to
both Ekeh’s (1975) presentation of the bifurcated primordial and civic publics and Mamdani’s
(1996) understanding of ethnicity as a form of anticolonial and anti-centralized state revolt
(184-185), for Erdmann and Engel (2007) a neopatrimonial system is one where “the
patrimonial penetrates the legal-rational system and twists its logic, functions, and output,
but does not take exclusive control over the legal-rational logic” (105).
24
Not only do neopatrimonial logics not abruptly end after a democratic transition, the
deregulation and privatization reforms pushed on African states by the Washington Consensus
create new opportunities for the continuation of corrupt practices (Szeftel 1998). The granting
of governmental positions or contracts as patronage (Arriola 2009) and political elite’s personal
use of public funds both undermine, “the continuity, trustworthiness and objectivity of the
legal order and the rational, predictable functioning of legal and administrative agencies”
(Weber [1922] 1978, 1095), which Weber sees as so necessary for the emergence of industrial
capitalism and stable economies. Further, the resource and information hoarding on which
these networks depend can further deprive citizens of sustainable community development
(Auyero 2000).
Rather than resulting in a redistribution of wealth, the clientelistic politics of neo-patrimonial
systems instead encourages predatory rent-seeking (Kurer 2007), in-turn used to establish a
new wealthy indigenous elite (Szeftel 1982). African leaders have proven themselves adept
at manipulating international support to fund political networks (Reno 1998; Van de Walle
2001) and have also intervened into economic markets, such as through the manipulation of
marketing boards, to accumulate political resources (Bates 1981; Reno 1998, 21). Indeed,
the development literature is intensely concerned about granting recipient governments
opportunities to tailor funding projects to country needs while still maintaining oversight to
prevent misappropriation of funds (Collier 2007). And the slow growth rates in Africa have
been explained as the result of neo-patrimonial rulers’ subversion of state rules, increasing
inequality rates, and ineffective international aid that may even worsen African economies
rather than improve them (Easterly 2007). While the strategies leaders utilize to direct
resources from the state to their personal control are not necessarily linked to ethnicity, the
high politicization of ethnicity and ethnic-voting in African states means leaders’ support
networks are intimately entangled with ethnic politics.
25
1.3.3 The Durability of Ethnic Voting
Elites manipulate ethnic appeals in order to acquire or maintain access to state resources.
Originating in the colonial era, the concept of ethnic representation is used by elites to
justify the allocation of state resources to their group, after it passes through their hands
as the ethnic representative (Bayart 1993). When ethnic elites do not feel the current
institutional makeup allows for adequate representation of their ethnic group at the top, ethnic
representatives have proved adept at mobilizing publics to violent ends (Wilkinson 2004). Elites
in power can also mobilize ethnic publics, and this typically takes the form of mobilization
against minority scapegoats as a distraction from government failures (Panggabean and Smith
2011; Adida 2014).
In newly democratized states, publics can also become mobilized to vote based on identity
and not substantive policies. In African politics, where the state is ‘soft’ and cannot be relied
on to provide consistent and even development across the country, politicians effectively
campaign on promises to develop and direct resources back to their ethnic home regions should
they win the election: “A cabinet minister in Africa is considered ‘a kind of superrepresentative’
who is expected to speak for the interest of co-ethnics, as well as channel resources to them”
(Arriola 2009, 1346).4 Delivering goods back to ethnic communities or networks may contain
a moral dimension which acts as a coercive force pushing politicians to dole out state, and
sometimes personal, resources to co-ethnics (Ekeh 1975; Lindberg 2003, 127). Indeed, once
politicians engage in ethnic politicking, it can quickly slip out of their control (Bates 1974,
471-473).
Finally, in societies where political parties are organized along ethnic lines, and electoral
results take the shape of an ‘ethnic census’ (Horowitz 1985, 84-85, 324-326), stable ethnic
4 The colonial alignment of within-country administrative units to ethnic boundaries (Bates1974, 464), which were then adopted in post-independence regimes, also generally contributedto the understanding of elected officials as ethnic superrepresentatives.
26
population figures equates to pre-determined electoral outcomes and weak opposition parties.
A credible opposition provides citizens with the opportunity to engage with government and
effect political change (LeBas 2011, 13) and can generate accountability, responsiveness, and
compliance with time in office laws (Arriola 2012, 21-22). In ethnically-divided contexts, then,
it is important to foment elite agreement across politicized ethnic groups and cleavages, but, as
Kenya’s politics of collusion demonstrates (Cheeseman 2011), even cross-ethnic elite agreement
may not be enough to produce good democratic governance.
1.3.3.1 The rationality of voting ethnically
Democratization scholars attempt to prove that individuals engage in evaluative voting,
using retrospective and prospective rationales, as opposed to merely relying on candidates’
ethnic backgrounds. It is argued that, after experiencing several electoral iterations with
alternations in power, voters will have the experience and incentives available to make
both retrospective and prospective voting decisions (Key Jr. 1955; Anderson and Dodd
2005; Lindberg and Morrison 2005). But conceptualizing ethnic and democratic voting
as mutually exclusive processes, however, suggests voters cannot be influenced both by
programmatic decision-making processes and subconscious identity factors simultaneously.
And, in democratizing contexts, it will be increasingly difficult to measure the impact of
identity on votes as voters are routinized to justify their voting preferences using democratic
rhetorics, rather than ethnic rationales. Whether because they are embarrassed to admit
their increasingly socially-unacceptable preferences for politicians based on identity, or that
voters are not aware of their suppressed identity-related biases, respondents in exit-poll or
other surveys are increasingly unlikely to mention ethnicity when justifying their votes. The
well-known ‘Bradley’ or ‘Wilder’ effect in American politics shows how hidden ethnic biases
in voting can make vote polling unreliable (Finkel, Guterbock and Borg 1991). Indeed, survey
evidence presented in this dissertation, as well as survey evidence presented in other scholars’
publications, show that Ghanaians rarely say that ethnicity played a part in their vote decision
(Lindberg and Morrison 2008).
27
However, correlational analyses show that ethnic backgrounds clearly have an impact
on voting in African states. Though economic and democratic factors also matter, voting
analyses in African countries consistently show that ethnicity remains the best predictor of
votes, (Bratton and Kimenyi 2008; Keefer 2010). Three explanations are commonly used to
explain ethnic voting.
First, some emphasize the psychological benefits voters receive by supporting their
group (Chandra 2004), a benefit likely driven by some mix of uncertainty reduction and
self-enhancement (Lieberman and McClendon 2013, 676). Second, it is argued that voters can
use identity cues as a cognitive shortcut for politicians’ future decisions. These voter rationales
have sometimes been explained as predictions about future policy implementations (Ferree
2006), but more commonly are explained as predictions about future regional, community
or personal goods likely to be distributed from elected leaders. With regard to the former,
when policy aims and differences between candidates are ill-defined, as is the case in most
African democracies (Van de Walle 2003; Weghorst and Lindberg 2011, 1194-1195; Whitfield
2009, 630), ethnic cues may be used to infer some of this information. With regard to the
latter explanation, in the absence of strong institutions and effective governance, voters might
feel that voting for a co-ethnic politician is their best shot at receiving some benefit for their
community.
A third explanation suggests that a link exists between ethnic or cultural background and
policy preferences (Rabushka and Shepsle 1972; Bates 1974). Ishiyama (2012) finds higher
rates of ethnic bloc voting within more concentrated ethnic groups, an outcome he explains
is the result of common social, economic, and political interests. Lieberman and McClendon
(2013) come to similar findings but conclude that though public policy preferences vary by
ethnic group membership, political relevance and intergroup wealth differentials better explain
this outcome than do cultural accounts.
28
1.3.3.2 But why is ethnic voting bad?
Voting on the sole basis of ethnicity, as mentioned in Section 1.1, brings politicians to
office based on their identities rather than their qualifications and makes these same elected
politicians less accountable to the electorate. When elected officials can rely on their ethnic
bases of support for re-election, they may exhibit poor job performance and still be re-elected.
In other words, neopatrimonial systems based on ethnic voting take away the democratic
incentives of performance review by citizens that otherwise should come with elections. Such a
system also stymies electoral competition from anyone outside of the dominant ethnic group.
However, I argue that ethnic voting is merely symptomatic of a larger issue facing new
democracies: the absence of real political competition. Competitive party politics within
new democratic systems are supposed to combat against non-evaluative voting because
citizens have the opportunity to evaluate a party’s time in power and decide whether they will
continue to vote for the party or will switch their vote to another party. But the lack of policy
differentiation between political parties means that voters are deciding about the quality of
the politician based on other cues. Similarly, voters realistically need to experience different
political parties’ governments in order to make informed decisions about what the parties have
to offer. And the competitive nature of democracy will be significantly hindered, particularly
in terms of accountability and responsiveness of elected representatives, if voters do not have
realistic opportunities to vote for a viable opposition party with an actual shot at winning.
In new democracies, this can be a slow process. The democratic regimes in Botswana
(Botswana Democratic Party in power since 1966) and post-apartheid South Africa (African
National Congress in power since 1994) have never experienced an alternation of power.
The polity has to take a big leap of faith when they collectively decide to bring a first-time
government to power. This gamble becomes even more significant in the absence of distinct
policy differentiations separating candidates and political parties.
Generating sub-national political competition is even more difficult than the national-level
in part because local-level party politics tend to be less developed and because constituencies
29
tend to be more ethnically homogeneous. When parties derive the bulk of their support
from co-ethnics, parties will have difficulty fielding candidates in localities outside of their
ethnic base. Local-level political competition is all the more important because locally elected
representatives are significantly more likely to impact constituents’ lives, with elections based
on issues directly relevant for the locality, as compared to the head of state. The development
of competitive politics in local communities in African states has been extremely slow to
develop and is still largely absent across the continent.
1.4 How Effective National-Level Competition Develops in Divided Societies
Overcoming dominant party politics, neopatrimonial state logics, and ethnic voting are
the greatest tests for new African democracies. A recent surge of publications has indeed
emphasized the importance of national-level competition, through credible opposition parties,
to counter the development of dominant party politics in African democracies. This work
offers a contribution to this literature by pointing out how tailored institutional designs, most
likely taking the form of a 50% +1 majoritarian electoral rule, also substantially contributes
to increased national-level political competition by requiring a wider support base on the
part of the political parties. Yet, as I will introduce in the next section, the coupling of a
majoritarian electoral rule at the national level with the way in which Ghana’s centralized
government institutionalizes sub-national political competition addresses all three of the
common democratic ills facing new African democracies.
1.4.1 Credible Oppositions
A recent literature on democratization in African states emphasizes the development of a
strong opposition as necessary to challenge the authoritarian regime, push for democracy, and
stamp out one-party dominance in the new democratic regime. African nations’ oppositional
groups typically have an ethnic-orientation, usually made up of those groups which the
authoritarian leader failed to incorporate into his political fold. African nations’ authoritarian
governments inherently enjoy cross-ethnic support because of the patronage resources at their
disposal, and will work hard to fragment the opposition (LeBas 2011). When an authoritarian
30
government faces a serious challenge, such as an economic crisis, that challenge is more likely
to result in a democratic transition if the opposition has a cross-ethnic base. A cross-ethnic
opposition is significantly less likely to alienate potential supporters who might otherwise
fear that new leaders would simply replace the authoritarian regime with another exclusive
government.
Scholars emphasize the development of strong oppositions as the result of historical
economic liberties which allowed oppositional elites to develop economic bases independent
of the state (Arriola 2012); as the result of weak authoritarian governments without high
levels of popular support who did not have the opportunity to shape democratic rules to their
own interests (Riedl 2014); because of a country’s ethnic make-up which determines the
development of ethnic versus programmatic parties (Elischer 2013); and finally because strong
opposition parties have been able to utilize the mobilizing structures of the former authoritarian
government and are able to maintain their strength when they use strategies that escalate
conflict along partisan lines of affiliation (LeBas 2011).
The running similarity throughout these strong cross-ethnic oppositional explanations
of democratization is the deterministic and context-heavy nature of their arguments. These
works, like traditional democratization literatures which emphasize strong opposition parties,
are successful in identifying paths through which African nations have attained democracy but,
unfortunately, all of these paths suggest that strong oppositions take significant periods of
time, or the right contextual features, to develop. Works that show how institutional features
affect the expression and nature of politicized ethnic cleavages (Wilkinson 2004; Posner
2005), however, suggest that different types of democratic institutions can encourage a more
rapid development of strong cross-ethnic parties. I argue that tailored institutional rules and
legitimate competition at the national and local level are one way to undercut dominant party
politics and neopatrimonialism and stimulate programmatic voting in new African democracies.
31
1.4.2 Majoritarian Electoral Systems
One institutional mechanism with great potential for encouraging national-level political
competition is a majoritarian electoral rule. Scholars working in ethnically-divided societies have
long debated about the political effects of electoral institutions on the nature of ethnic divides.
Horowitz (1985), Sartori (2000), and Reilly (2001) all argue that majoritarian systems, with
a 2nd round option, are important for diffusing mono-ethnic parties. In a 50% + 1 electoral
game, parties are required to broaden their appeals to wide-swaths of the population and
incumbent governments cannot risk alienating large groups from their list of supporters. As
Briggs (2012) has shown, the absence of widely-distributed political goods in such an electoral
context can prove electorally costly for incumbent governments.
With more constituent support necessary for national-level electoral victories, the overall
electoral competition naturally becomes more competitive. In most cases no one ethnic
group makes up greater than 50% of a population, so even if a political party represented a
dominant ethnic group, it would be forced to offer an ethnically-inclusive campaign platform
(or at least avoid an ethnically-exclusive campaign platform) if it was in serious contention
for national power. While an increasingly number of African governments have turned to the
50% + 1 electoral rules, adopting these rules can be controversial. In Zambia, for example,
the implementation of such a rule has been contentious and, until recently, was a major factor
contributing to a stalled reform of the national constitution despite several constitutional
review committees recommending a 50% + 1 change (Motsamai 2014). In another case, Sierra
Leone’s 1991 Constitution enforces a particularly stringent supermajoritarian electoral system
in which the presidential winner must secure greater than 55% of the vote in order to avoid a
run-off election. Still, it is surprising how rarely majoritarian electoral rules have been adopted
in the history of democratic trials in African states.
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1.5 Taking the Effects of Institutionalized National and Sub-National Competitionto Ghana
A vacuum in political competition challenges democratic principles of self-government,
accountability, and responsiveness. I argue that the implementation of institutions which
generated legitimate party competition at both the national and local level in Ghana have
gone a long way in preventing dominant party politics and regulating patrimonialism and
ethnic politics. In particular, no one ethnic group in Ghana makes up over 50% of the
population meaning the 50% + 1 majoritarian electoral rules at the national level requires
political parties to appeal to voters outside of their traditional ethnic bases. Secondly, the
presidential appointments of well-funded politicians (Metropolitan, Municipal, & District Chief
Executives (referred to as DCEs throughout)) to the local-level to compete for support against
locally-elected Members of Parliament (MPs) has increased evaluative voting on the part of
citizens and politicians’ appeals to voters on the basis of policy platforms. Though personal
ethnic backgrounds still have an impact on many vote decisions, citizens are increasingly less
likely to engage in automatic, knee-jerk co-ethnic voting so common in prior regimes in Ghana.
Ghana proves that institutional engineering and tailoring institutions to country context can
significantly increase the pace at which quality governance deepens in a new democracy.
1.5.1 Majoritarian Electoral Systems in Ghana
First adopted in the 1979 Constitution, Ghana had used a 50% + 1 electoral rule only
once in the 1979 Presidential elections before Flight Lieutenant John Jerry Rawlings staged
a second coup d’etat and installed a 10-year military government beginning in 1982. Once
democracy was restored, the 1992 Constitution again implemented a 50% + 1 electoral
requirement for Presidential elections. Now six Presidential elections have been held since the
adoption of the 1992 Constitution, with run-offs held in 2000 and 2008.
A majoritarian electoral rule is crucial in the context of Ghana’s ethnic population makeup.
Even when linguistically-defined, no ethnic group in Ghana has a population proportion of
greater than 50%. The closest linguistic group are the Akan-Twi speakers, whose population
33
proportion is 47.5% as of the 2010 Census. Historically the Akan-Twi linguistic group has never
been entirely unified, but even if a particularly charismatic leader was interested in uniting all
Akan-Twi speakers behind her or his candidacy, the majoritarian requirement still makes an
automatic victory difficult to accomplish.
The majoritarian electoral rule may also make alternations in power more likely. While
others have pointed out that economic (Arriola 2012) and historical/contextual factors (LeBas
2011; Elischer 2013; Riedl 2014) contribute to the development of strong oppositions, the
simple fact that both governmental and opposition parties are realistically required to appeal
to voters outside of their base, coupled with voters learning that votes for narrow regional
or ethnic political parties are likely to be wasted, is part of the appeal of plurality, and by
extension majoritarian, electoral rules tending toward two-party systems (Duverger 1954). In
the context of plurality electoral rules, the largest ethnic group’s party is most likely to win the
election (a la Horowitz’s (1985) ‘ethnic census’). In a 50% + 1 majoritarian system, a second
round voting option habituates politicians and voters to think in broad-based political logics.
Nonetheless, majoritarian electoral rules, and competitive electoral politics in general, are
not at odds with clientelistic logics driving political goods distributions (Lindberg 2006, 20).
Electoral competition in new democracies does not automatically equate to programmatic
and ideological based competition. Other than strong opposition parties, something further
is needed to encourage programmatic politics. I argue that Ghana’s uniquely centralized
democratic system fills the void by institutionalizing political competition at the local level.
1.5.2 Ghana’s Centralized System of Local Government
The inability of any single ethnic group to win national elections under Ghana’s
majoritarian electoral rule is particularly crucial in the context of Ghana’s local institutions.
In each of Ghana’s districts, the 1992 Constitution authorizes the President to appoint DCEs
who exist alongside locally-elected MPs. Both DCEs and MPs control portions of the national
budget, distributed through the Common Fund, to construct development projects within the
district/constituency. MPs and DCEs are in a natural competition to provide more effective
34
development. Two crucial factors are at play in this development competition. First, DCEs
control a much larger portion of the Common Fund than do MPs. Second, DCEs reside
in the community, while MPs reside in the capital and have to travel home to visit their
constituents. While DCEs have a ‘face-time’ advantage as they are much more accessible
by their constituents, MPs have a lobbying advantage because residing in Accra puts them
in close proximity to the bureaucratic ministries which proactive MPs can pressure for their
constituency’s inclusion within upcoming development projects.
In theory, DCEs and MPs can maintain a cordial and effective working relationship,
particularly if they are members of the same political party. However, even when these
two officials are of the same political party, it is assumed that the DCE aspires to become
the future MP of the constituency. This is for several reasons. First, DCEs face two term
limits whereas MPs can be elected indefinitely. Further, MPs are national figures, reside
in state-furnished housing in Accra, have larger incomes and can even receive Presidential
appointments to simultaneously serve as ministry heads. Overall, MPs have the more coveted
position.
When DCEs and MPs are not of the same political party, which happens when the
national government is of a different political party than the locally-dominant party, the DCE
functions as the local representative of the President and is specifically instructed to implement
development projects in order to convince voters away from the MP’s party. One trick at the
DCE’s disposal, for instance, is to hold founding or opening ceremonies for new development
projects without informing the Accra-based MPs. If you or your representatives are not present
at such an opening ceremony, citizens will assume you had no part in that project.
The level of competition between DCEs and MPs thus ranges from moderate (intra-party
Friendly Pairs) competition to high (inter-party Unfriendly Pairs) competition. When
alternations in national-level power occur, which has happened with two runoff elections
in both 2000 and 2008, the political party in power replaces the prior regime’s DCEs with
their own party-member appointees to the local level. Every district in Ghana has now had
35
both NDC (1992-2000 and 2008-2016) and NPP (2000-2008) appointments to the DCE
positions. Though the national-level appointment of local representatives is a far cry from the
democratization - via - decentralization theme of the development community popular since the
1990’s, I argue that this highly-centralized system of local government has actually been quite
effective in generating legitimate political competition at the sub-national level.
1.6 Competing Explanations
This dissertation argues that Ghana’s specific national-level and local institutions
introduce legitimate political competition which prevents dominant party politics, undermines
neopatrimonial political logics and encourages programmatic voting. In other words, I point to
Ghana’s institutions as the primary factor leading to the increased local-level competition and
weakening of ethnic voting in Ghana. Two other arguments which alternatively may explain
the increase in political competition and changes in ethnic voting are that (1) the occurrence
of elections sets in motion processes which lead to a greater supply and demand for democracy
and (2) economic growth increases the ability of candidates/parties to implement universal
development/wide-ranging appeals as well as makes votes from a wealthier citizenry more
expensive to buy. I address these two alternative explanations below.
1.6.1 Democratization-via-Elections
The most important competing explanation that explains democratic deepening is the
idea that holding multiparty elections pushes democracy forward. Famously argued by Lindberg
(2006), the implementation of even faulty democratic elections is important for re-orienting
elite calculations and citizen perceptions toward democratic rules of political competition.
Citizens now have a mechanism through which they can voice their displeasure with politicians
and become empowered by their newly granted authority. Politicians fear this new authority
and reconsider their political calculations to account for public perceptions of their effectiveness
in office. Further, these new institutions, and actors’ socialization to democratic structures also
leads to the deepening of civil liberties as measured by Freedom House’s civil liberties scores.
Lindberg finds that once African nations held two elections, they were significantly more likely
36
to remain democratic. After three elections, a country’s democratic quality improves radically
(Lindberg 2006, 74).
Though Lindberg’s argument is intuitive and his evidence through 2003 convincing, this
argument has been challenged in other parts of the world. The application of this argument
to Eastern Europe originally looked promising as protests surrounding faulty elections proved
important for initiating democratic transitions. But the initially successful color revolutions
in Yugoslavia, Georgia, Ukraine, and Kyrgyzstan in the early 2000’s have not led to stabilized
democracy and democratic progress has even arguably backslide in these states since. In
other cases civil society mobilization around elections to push for democratic change was less
successful (Belarus, Moldova, and Romania). Scholarly work that applies Lindberg’s argument
to the broader postcommunist states have found that elections do not necessarily promote
democratization (Kaya and Bernhard 2013) and can actually strengthen authoritarianism
in some contexts (Brownlee 2009). This is a similar conclusion found in a hybrid regimes
literature which emphasizes election manipulations as a tool used by authoritarian governments
to retain power (e.g., Levitsky and Way 2010).
Further, in both Latin America and the Middle East, scholars have found that elections
do not have as democratizing an effect as in Lindberg’s argument (Lust-Okar 2009; McCoy
and Hartlyn 2009). Finally, some Africanists have suggested that the early nature of Lindberg’s
dataset accounts for his robust results. Well-summarized by Lynch and Crawford (2011),
depreciations in Freedom House’s civil liberties scores for African nations in 2006 as well
as worse democratic ratings assigned to previously promising democratic regimes in Kenya,
Nigeria, Ethiopia and Senegal (Lynch and Crawford 2011, 280) have made the Africanist
community increasingly skeptical of the democratizing promise of elections.
In Ghana’s case, increased political competition at the local level could be the result of
the long practice with democratic institutions, across 6 elections and 2 peaceful transitions
of power. The real reason behind a lessening of ethnic voting could be that democratic
institutions and repeated elections have incentivized programmatic behavior on the part of
37
campaigning politicians and voting citizens. Though viable, in Chapter 5 I show that vote
differences significantly increased in crucial elections after local institutions altered the nature
of political competition at the constituency level. If vote differentials were not significantly
altered in the wake of changes in local competition, then Lindberg’s explanation might hold
more weight in explaining deepening democracy in Ghana. Instead I argue that it is not just the
routinization of democracy via elections that results in programmatic voting, but an increase in
real political competition at the local level is what is driving programmatic political logics and
nullifying clientelistic vote-buying.
1.6.2 Democratization-via-Economic Growth
First, one of the arguments for economic growth’s contribution to the lessoning of ethnic
voting and neopatrimonial politics is that it potentially supports the funding of far-reaching
programmatic political strategies because governments can now afford to appeal to voters
on a wide-reaching programmatic basis. Indeed, in Arriola’s (2012) work, the ability of
potential opposition leaders to amass the political and economic resources they would need to
generate wide-reaching political coalitions that could challenge the government in power was
dependent on the closed or open nature of the economy. In Cameroon’s closed economy, for
instance, only individuals with ties to the government could gain wealth through the country’s
heavily-regulated avenues. Potential opposition leaders were thus restricted in their ability to
independently gain massive amounts of wealth necessary for coalition-building. In Ghana’s case,
it could be argued that economic growth has meant that both political parties have been able
to spread their campaigns across Ghana, offering monetary support and/or gifts in trade for
citizens’ votes, and thus creating greater vote volatility across Ghana’s localities.
For one, Ghana has experienced strong economic growth recently, but it’s strongest
economic growth only occurred after the discovery of oil in 2007. The World Bank lists
Ghana’s annual GDP growth at between 3.7% and 6.4% between 2000 and 2006. It was not
until after 2007 when Ghana’s annual GDP growth grew to the impressive levels of 9.1% in
2008, 4.8% in 2009, 7.9% in 2010, 14.0% in 2011, 9.3% in 2012, and 7.3% in 2013 (The
38
World Bank 2016b). My analysis starts tracing the effects of central appointments of DCEs in
opposition areas to 2000, prior to the discovery of oil.
Second, assuming universalistic programmatic political strategies did result from increased
economic growth, the power of the district-level DCEs would be even greater as they would
have control over an even larger amount of district-level development. In other words, if
Ghana’s increased development funding did filter through the DCE, as it likely would given this
individual’s crucial knowledge of the needs of local communities within their district, economic
growth would not contradict my theory but would actually heighten the degree of competition
between the DCE and MP(s). Indeed, the District Assembly Common Fund (DACF) did
increase from 5% to 7.5% of Ghana’s budget in 2008.
Third, Ghana’s increased economic growth does not explain the variation in vote volatility
as presented in Chapter 5. In particular, I provide evidence that constituencies with MPs of
the same political party as the DCE, as compared to constituencies with MPs of different
political parties from the DCE, have stable or decreased votes for the MP’s/DCE’s party. When
constituencies elect MP’s of different political parties from the DCE, votes for the DCE’s party
increase in the subsequent election. If economic growth led to more inclusive development
distributions and this in-turn was increasing vote volatility, we should not see this variation in
vote volatility based on friendly (same party) or unfriendly (different parties) MP-DCE pairs.
Next, it is also possible that economic growth in Ghana has led to increased citizen
wealth, which makes it more expensive to rely on an ethnic-based neopatrimonial system
to guarantee one’s power. But this assumes that national-level economic growth leads to
increased wealth across society. In other words, that economic growth could make it more
expensive and thus unfeasible to rely upon a system of co-ethnic vote buying is dependent
upon decreasing inequality.5
5 Theoretically, I argue that neopatrimonial politics functions so well in African statesbecause of the high degree of inequality which exists (e.g. Markussen 2011; Robinson and
39
However, the application of this argument to Ghana cannot account for an increase
in programmatic voting because Ghana has actually become more unequal over time
(Obeng-Odoom 2012). As Table 1-1 shows, the total income value earned by Ghana’s
richest 20% income earners has increased, while the income earned by every other income
sub-population, save the 60-80% income earners, has decreased over time. Though the data
available does not cover all the years of Ghana’s Fourth Republic, the dataset does span prior
to the democratic transition which occurred in 1991, and extends to 2005, which is two years
prior to the discovery of oil off the Ghanaian coast. And preliminary evidence suggests that
the discovery of oil has only led to further increases in inequality. In other words, if economic
growth were making it more expensive to rely on a neopatrimonial system and thus forcing
politicians to appeal to voters with programmatic policies, then we should see decreasing
inequality over time. As it appears now, everyday citizens in Ghana are not becoming wealthier
relative to the top echelons of society, so buying votes should not have become more expensive
and thus cannot be driving the break down of ethnic voting in Ghana.
Finally, as Chapter 8 demonstrates, the list experiments testing for the impact of
clientelistic-inducements on voting were only found to have an impact in the competitive
districts, and not the NPP or NDC strongholds. If clientelistic payoffs were increasingly
turned to as a result of the greater availability of funds in Ghana’s growing economy,
clientelistic-inducements would have been effective across the NDC and NPP strongholds
as well.
Verdier 2013), and which neopatrimonialism may very well perpetuate (Van de Walle 2009,320-321). This is primarily because paying for votes on a mass scale is only effective whenpayoffs per individual or household are relatively low. While we might expect the opposite,that inequality produces calls for redistributive programmatic policies, empirically clientelisticpayouts continues to function very well in African cases with high levels of inequality. However,I would argue that, if economic growth leads to a decrease in inequality, paying the massesfor their votes becomes more expensive and clientelistic political strategies become less viable.More unequal societies, according to this logic, would tend toward particularistic logics whererich political elites use the resources at their disposal to engage in rentier politics.
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1.7 Outline of Chapters to Come
In the chapters that follow, Chapter 2 demonstrates how politicized ethnic divides
contributed to unstable democratic and authoritative regimes prior to Ghana’s Fourth Republic.
This chapter also contextualizes the process of institutional change and how past institutions
were modified as a response to the nature of politicized ethnic divides. Though Ghana was a
notoriously difficult colonial possession to manage, with the imposition of indirect rule facing
strong resistance (Simensen 1975), decades of institutional reform in response to politicized
ethnic group challengers to the state eventually led to the current centralized system of power
in the Fourth Republic.
In comparison to past regimes’ centralized institutions which tried and failed to address
ethnic divisions, Chapter 3 shows how the centralized institutions of Ghana’s Fourth Republic
differ in a way that is crucial to de-politicizing national-level ethnic divides. In particular, the
Fourth Republic institutionalizes political competition at the local-level. The chapter begins
by explaining the current local government system, specifying where the central government
retains control and where the District Assembly can exercise its authority. I then situate the
DCE and MP within this system, highlighting how the incentives and motivations of these
two political actors results in a competitive relationship. I show how the level of competition
between the DCE and MP is moderate when they are of the same political party (friendly
pairs) and significantly stronger when they are of different political parties (unfriendly pairs). I
argue that this level of competition is the driving force behind the break down of ethnic voting,
particularly in the post-2000 elections, in Ghana’s Fourth Republic.
To estimate the impact of political competition on vote outcomes, I use three methodological
tools. Chapter 4 introduces the first of these tools: Ecological Inference (EI) Models. These
models estimate individual vote outcomes using aggregate election and demographic data.
Two general hypotheses are tested in this chapter. First, though the literature on ethnic voting
highlights the importance of linguistic-group definitions of ethnicity, I argue that Ghana’s tribal
group identities are also politically relevant. Tribal group relevance is, as I argue, particularly
41
on the rise given the politicized nature of Ghana’s system of local government. I predict, then,
that analysis of tribal-group voting patterns will show that tribes within the same linguistic
group differ dramatically in their vote patterns and are thus more accurate depictions of
‘ethnic’ voting. Second, I predict that votes by core and peripheral political party supporter
groups will increase for the opposition party from 2004 through 2012. These changes, I argue,
are due to the competitive political environments at the local-level engendered by Ghana’s
centralized system of local government.
Though EI allows us to estimate vote choices along ethnic identity groups, Chapter
5 introduces national-level regression analyses to parse out evidence of actual changes in
partisan votes. Using the percent change in the difference between both Presidential and
Parliamentary votes for the NPP and NDC at the constituency level as my outcome variable,
I show that votes for the DCE’s political party significantly increased, in both Presidential
and Parliamentary races since 2000, in constituencies which had voted in a MP was of the
opposition party in the prior term. In other words, votes for the NPP increased in 2004 at
significantly higher rates for districts with NDC MPs as compared to NPP MPs. Though one
might argue that votes for the NPP could only go up in the NDC strongholds who had voted
in NDC MPs in 2000, the effect holds for 2008. Keeping in mind that 2008 was an electoral
turnover rate where the NDC won the Presidency, votes for the NPP again significantly
increased in districts with NDC MPs as compared to NPP MPs. Finally, in 2012 votes for the
NDC increase at significantly higher rates in districts which had elected NPP MPs in 2008 as
compared to NDC MPs.
Finally, in Chapters 6-8, I analyze the results of an N=1,932 survey conducted across 6
districts in Ghana (September 2013 December 2013) to better pinpoint the factors which
actually contributed to individual vote choices. I introduce the district pairs in Chapter 6,
detailing the structural similarities and voting differences within the NPP strongholds, NDC
strongholds, and competitive district pairs. I explain the stories behind the voting differences,
where possible, and then begin to evaluate three different hypotheses for voting rationales
42
across the entire sample and within/between the district pairs. The three hypotheses are
(1) Identity-Based Voting, (2) Economic or Policy-Based Voting, and (3) Clientelistic-Based
Voting.
In Chapter 7 I use multinomial logistic regressions to test for respondents’ self-report
votes and logistic regressions to predict swing voters from stable voters. In Chapter 8 I test
for predictors of swing voting, analyze a tribal survey experiment, and evaluate two different
list experiments on bias towards Muslim politicians and whether clientelistic gifts affected
respondents’ votes.
The overall analysis finds strong evidence for Hypothesis 2: Policy or Economic-Based
Voting in direct questions but also when testing for respondents’ votes as well as for the
factors which influence swing voters. Outside of Hypothesis 2, Hypothesis 1: Identity-Based
Voting is somewhat supported throughout the analysis, while evidence for Hypothesis 3:
Clientelistic-Based Voting was only found using list experiments.
Chapter 9 concludes the work with a summary of the manuscript and an overview of its
major arguments. In particular, this work has argued that Ghana’s democratic success and
democratic deepening is largely the result of both the country’s national-level majoritarian
electoral rules and uncharacteristically centralized democratic system of local government. This
centralized system greatly affects the levels of local competition at the constituency level in
ways that other decentralized systems do not allow. The politically competitive environments
at both the national-level and local-level in Ghana address the democratic ills of dominant
party politics, neopatrimonial political logics, and ethnic voting which plague many other
democracies in Africa.
43
Table 1-1. Ghana’s income share held by what population percentage
Year Top 20% 20-40% 40-60% 60-80% Bottom 20%1987 42.7% 11.7% 16.3% 22.3% 7.0%1988 43.4% 11.5% 16.0% 22.1% 7.0%1991 45.6% 10.9% 15.2% 21.7% 6.6%1998 46.2% 10.3% 15.0% 22.7% 5.8%2005 48.6% 09.9% 14.6% 21.7% 5.2%
Source: The World Bank 2016a
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CHAPTER 2GHANA’S HISTORY OF CENTRALIZATION AND ETHNIC POLITICS
In this dissertation I argue that national-level electoral rules and the centralization of
institutions in the Fourth Republic encouraged competitive national elections and competitive
local-level politics, and thus prevented dominant party politics at the national-level and led to
a lessening of neopatrimonialism and ethnic voting at the sub-national level. In prior regimes,
however, ethnic mobilization was high and contributed to both authoritarian and democratic
regime instability. The centralization of institutions was, historically, the primary mechanism
used to address ethnic divides, but these reforms only further provoked ethnic-based opposition
and contributed to overall instability. It is only with the imposition of political competition at
the local-level in Ghana’s Fourth Republic that neopatrimonial political logics and ethnic voting
have begun to subside.
From institutional choice literatures we know that historical cleavages and past institutions
heavily influence latter institutional design. Within this same vein, the argument presented
in this chapter identifies both the development of ethnic politics and centralized institutions
as parallel processes in Ghana’s history. After introducing this argument in greater detail
below, I then systematically present the history of centralization and ethnic divisions in
Ghana, pointing out the ways in which regimes’ centralized institutions provoked particular
ethnic responses, which in turn became instrumental in determining the political outcomes
of the economic-motivated coups which ended each of Ghana’s past regimes. In other words,
though economic contractions typically were the last straw that broke the back of different
regimes, the nature of the prior regime’s institutions and the ethnic-based opposition to those
institutions greatly determined the justification of coups as well as the post-coup regime.
Centralization and issues of ethnic representation, including the relative power of ethnic
chieftaincies, were thus fundamental to prior regime instability in Ghana. Finally, at the end
of the chapter I establish that ethnic voting patterns at the beginning of the Fourth Republic
were reminiscent of voting behavior in prior regimes. The overall argument of this work is
45
that neopatrimonial political logics and ethnic voting are diminishing and the sub-national
political competition instigated by the Fourth Republic’s centralized system is the primary
causal mechanism behind this outcome.
2.1 The Argument
With origins in the colonial period, the politicization of ethnicity was intricately linked to
the imposition of centralized rule in each of Ghana’s past regimes. To begin, the centralization
of British power in Ghana was linked to the creation and/or re-definition of ethnic group
boundaries under an artificial and hierarchical chieftaincy structure. The dual aim was both to
rule over society and divide the colonial population. Chiefs became empowered by the British,
making them beholden to colonial rulers rather than their own communities. As indigenous
institutional checks and balances on chieftaincy power faded away, the colonial authorities
favored the traditional chiefs over educated elites who sought a share of political power. When
ethnic entrepreneurs would later use ethnicity as a tool for political mobilization, they implicitly
relied on the concept of an ethnic identity and intra-ethnic unity promoted by colonial-era
centralization.1
After independence, successive regimes perpetuated colonial-era centralized control,
justified to protect or defend against Akan power. On the one hand, some regimes, including
Nkrumah’s and Acheampong’s, argued that centralized rule was necessary to combat both
the inadequacies of traditional chiefs and the ethnic divisions which they reinforced, which
1 Though rarely acknowledged, chiefs have consistently been central to ethnic politics inGhana. As the ultimate arbiters of tradition and culture, chieftaincy institutions provide ethnicentrepreneurs with a ready-made discourse through which ethnicized publics are mobilized.First, chiefs continuously define and reinforce ethnicity, and use tradition to maintain theirrole as the arbiters of the community and its interests. Second, chiefs also are patrons ofcommunity-level development. In Ghana, chieftaincy approval is informally necessary for theimplementation of any public development project, particularly because most of the landavailable for development projects is communal land. Beginning in the colonial period, andextending into the post-colonial era, chiefs in Ghana were consistently incorporated intoinstitutions of rule. This perpetuated their local authority and guaranteed the continuedrelevance of tradition and ethnicity for politics.
46
also served as a thinly-veiled assault on Akan power. On the other, the second justification
emphasized by Busia and Akuffo, used centralized rule in an exclusionary fashion, which
guarded the interests of particularly powerful ethnic groups and their chiefs, namely the
Akans. Whether by de-emphasizing ethnicity or privileging particular ethnic groups, centralized
institutions produced politicized ethnic cleavages either in the form of a politics of grievance by
powerful groups not receiving ‘their fair share’ of the national pie (e.g. Akans under Nkrumah,
Acheampong, and, later, Rawlings) or from groups excluded from positions of privilege (e.g.
non-Akans under Busia and Akuffo). Furthermore, the provocation of politicized ethnic divides
resulted in strong ethnic-based oppositions and unstable authoritarian rule.
Though the centralizing reforms of the Fourth Republic were more a continuation of past
authoritarian control than they were changes made for the sake of democracy, for the first time
the political system encouraged real political competition at the grassroots level. Historically
under-served citizens, particularly those residing in rural areas, now have programmatic
alternatives to voting for the locally dominant party. This has contributed to a lessening of
the influence of neopatrimonial political logics and ethnicity on vote decisions and is crucial for
understanding Ghana’s democratic stability.
2.2 Pre-Colonial Ethnicity and Colonial Rule
2.2.1 Ethnicity, Chiefs and Regional Identities
Ethnicity in Ghana developed out of both pre-colonial and colonial institutional structures.
Ethnicity was neither wholly created by colonial powers nor was it static in response to
changing political and institutional circumstances. Historically the defining features of an ethnic
community were determined by chiefs and elders, and rules/boundary lines determining who
belonged were manipulated over time to serve community needs (e.g., Greene 1996). As the
extension of economic markets and migration patterns put greater strains on local community
resources, community leaders began to differentiate who counted as autochthonous ‘sons of the
soil’ and who was labeled a stranger.
47
This distinction between insiders and outsiders was exacerbated by colonial rule which
promoted particular groups within a largely artificial hierarchical chieftaincy structure
imposed for administrative purposes. Missionary groups also selected particular languages
and dialects over others for translation of the Bible, reinforcing ethnic unity on the basis of
particular dialects. Later, after the British took sole control of the Gold Coast, they imposed
Lugardian Indirect Rule using traditional leaders and customary law. The British employed
anthropologists to codify customary law which was then enforced by the Native Authority and
Native Courts, headed by chiefs and backed by the British; “Thus, custom became transformed
from a political resource for re-negotiation of social status and access to resources to a set of
enforceable rules that froze status and restricted access” (Spear 2003, 14). Based on codified
customs, ethnic boundaries solidified and became convenient political commodities ready for
ethnic elite manipulation in the post-colonial era.
Throughout the colonial period, chieftaincy power waxed and waned but was consistently
incorporated into the formal institutions of the state. Rule through chiefs was administered in
ad-hoc fashion, with different powers allowed to different chiefs and a continual re-codification
of official ethnic customs. In addition, colonial institutions intentionally empowered chieftaincy
institutions at the expense of educated elites. At the same time, the British also ruled the Gold
Coast as three separately administered colonial territories: “the Gold Coast Colony since the
1830’s, Ashanti colony since 1874 and the Northern Territories since 1891” (Massing 1994,
2-3)2 Inconsistencies between and within British colonial administrations were common and, as
2 The Gold Coast colony, consisting of control over coastal territories, was establishedfirst. The extension of British control over the Ashanti Empire was completed after a seriesof Anglo-Ashanti Wars (in which the British utilized Fante (another Akan tribe) soldiers fromthe Gold Coast colony against the hinterland Ashanti Empire). British control of the NorthernProtectorate was established after ‘treaties of friendship’ were signed with the majority ofNorthern chiefs.
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different groups and regions were administrated differently, an overall effect of indirect rule was
an emphasis of regional and chieftaincy-based ethnic identities.3
By the 1940’s, the divide between chiefs, whom relied on colonial authority for power,
and the educated elites, who began to push for independence, was cemented. Relatedly, ethnic
traditions and customs, with chiefs as the custodians, were essentially codified. And, with
greater bureaucratization of political rule, chieftaincy power was limited, but still formally
incorporated, alongside greater centralized British control. This set the stage for the formation
of official elite-based opposition to both British colonial rule and, as their allies, traditional
chiefs.
2.2.2 The Educated Elite Response in the 1940’s and 1950’s
In reaction to the unrepresentative nature of colonial rule, a group of lawyers, merchants
and academics formed the United Gold Coast Convention (UGCC) in Saltpond, Gold Coast
in 1947. They were led by the ‘Big Six’ - Ebenezer Ako-Adjei, Edward Akufo-Addo, Joseph
Boakye Danquah, Emanuel Obetsebi-Lamptey, William Ofori Atta, and the newly-invited
3 Beginning in 1932, after the successful introduction of Lugardian Indirect Rule first inTanzania and then in Northern Nigeria, official indirect rule was brought to the NorthernTerritories, with an emphasis on the regularization of taxes and the creation of a budget tocontrol spending (Crowder and Ikime 1970, xx-xxi). By 1936, Lugardian Indirect Rule provedvery successful in the Northern Territories (e.g., Saaka 1978), partially because of its statusas an underdeveloped region far from the coasts and with fewer educated citizens to protestthe new measures. But indirect rule was not formally introduced in the Gold Coast colonyuntil 1944 (Simensen 1975, 297) when the establishment of official government treasuriesfinally placed local budgets in the hands of the colonial bureaucracy as opposed to chiefs(Owusu 1970, 2000). A uniform policy for the entire country (no longer separated into distinctterritories and colonies) was not adopted until 1951, a mere six years prior to independence(Saaka 1978, 21).Legislation introduced in 1944 further increased British control. Now the tribunals which
had been controlled by chiefs became under control of the Governor, and political control wasalso transferred away from State and Provincial Councils and back to the British Government(Simensen 1975, 304). As Simensen (1975) describes, the general public was extremelyfrustrated that the reforms in both the 1944 legislation and the subsequent Burns Constitutionof 1946 failed to democratize traditional councils and that neither the educated elite nor themasses were formally represented in government.
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Kwame Nkrumah. The UGCC was a conservative capitalist-minded political party which
worked for self-government, but not at a rapid rate. An elitist organization, the UGCC had an
interest in inheriting political rule, but it was also interested in the maintenance of the colonial
economic system upon which their wealth depended (Owusu 1970, 188).4
Partially in response to the elitist orientation of the UGCC5 , the slow time-table for
independence, and the awakening mobilization of the masses, Kwame Nkrumah famously broke
away from the party and founded the Conventional People’s Party (CPP) in June 1949. The
CPP was a mass-oriented populist and socialist-leaning political party whose principal slogan
was ‘Self-Government Now’ (Saaka 1978, 28).6
4 Though the UGCC pushed for independence, it was willing to follow the colonial timelineon when it would be granted. Other segments of the population, the new urban classes, andthose “generally dissatisfied with their economic lot” (ibid, 188), were becoming increasinglyfrustrated with price inflation and their prospects under colonial rule (Simensen 1975, 314).Disturbances in 1948 included extensive riots after colonial forces opened fire on World WarII veterans peacefully protesting the failure of the colonial government to disburse promisedpensions.
5 Allman (1993) describes the political disposition of J.B. Danquah of the UGCC and arepresentative of the Asante old-guard intelligentsia: “Mass support was both cumbersome andirrelevant to the assumption of political office. As the noted African-American novelist, RichardWrite, concluded after interviewing J.B. Danquah, the personification of the old guard: ‘He wasof the old school. One did not speak for the masses; one told them what to do”’ (48).
6 About this same time, the Coussey Constitutional Commission formed to address theWatson Commission’s findings that the lack of self-government and the antiquated andinefficient Native Authority system operating in the rural areas were major issues requiringattention.The status of the chiefs in this pre-1951 election era was continually renegotiated.Chieftaincy power was severely diminished from the early colonial period, but it alsoremained institutionally protected. The 1949 Coussey Report rejected the Watson Report’srecommendation that chiefs be removed from local government (Saaka 1978, 30). TraditionalCouncils thus remained in existence alongside State Councils, though now Traditional Councilsonly handled customary functions. During this time it was established that communal landand profits from its production belonged to the public as opposed to the chiefs. Similarly,“the total replacement of the Native Courts by a full-fledged professional local court system”(Simensen 1975, 317), though not finally enacted until 1959, meant usurping judicial powerfrom Traditional Councils. Local Councils were also re-institutionalized such that theirconstituencies coincided with native state territory and one-third of local council members
50
Leading up to the 1951 elections, the major contending parties were the UGCC and
Nkrumah’s CPP. Nkrumah had been arrested by the British authorities for instigating strife
within the colony and he began campaigning from his jail cell. The arrest only increased
Nkrumah’s popularity and, realizing they had created a martyr, the British were compelled to
release him. The CPP handily won the 1951 Parliamentary elections, leading to Nkrumah’s
appointment to Prime Minister, and it subsequently won over 90 percent of the seats in
the Local Council elections of 1952 (Owusu 1970, 196). Two major campaign issues helped
secure CPP victory. First, Nkrumah had promised to help cocoa farmers in the face of the
British-created Cocoa Marketing Board (Owusu 1970, 191). Second, Nkrumah played upon
chieftaincy disputes, and particularly appealed to the grievances of sub-chiefs who were
disempowered by colonial centralization efforts of the 1940s and 1950s (Simensen 1975, 316).
2.3 Post-Colonial Centralization and the Ethnic Response
2.3.1 CPP versus NLM in the Post-1951 Election Period
As Prime Minister, Nkrumah argued that increased centralized control was necessary
to combat ethnic divisions. Yet the specific policies pursued by the CPP government
particularly targeted elite cocoa wealth and Ashanti power, co-opted Akan sub-tribes to
disunite an Akan-based opposition, and provoked an ethnic response given voice by the Ashanti
Region-based National Liberation Movement (NLM). Finally, the NLM resorted to a call for
were to be nominated by the State Council. The Paramount Chief would act as ceremonialpresident of the Local Council, but the chairman would be an elected citizen (ibid). Further,to some extent traditional interests were also implicitly present in the bureaucracy and in localcouncils as relatives of chiefs were often the privileged in society. Not only would relatives ofchiefs become representatives in government or the bureaucracy, but, “frequently, young menrisen in the modern system as clerks, educators, administrators or political activists enter thetraditional system at a later age by competing for chieftaincy or eldership” (Massing 1994,37). The revolving door between traditional and formal power complicates the incorporationof traditional power in modern rule, particularly in the late pre- and early post-independenceperiod when formal opportunities were scarce and limited to society’s elites.
51
a federal system of government, demonstrating the initiate association between institutional
structures and ethnic politics at the time.
One argument offered to explain the development of regional and ethnic opposition from
the NLM and later the ethnic-coalition United Party (UP) is because “it had proven impossible,
as evidenced by the results of the 1951 election, to compete ideologically with the CPP as
an alternative Gold Coast-wide nationalist party” (Allman 1993, 20). Yet, as Allman agrees,
this does not explain why the strongest form of opposition came from the Ashanti Region.
At a basic level, the historical dominance of the Ashanti Empire, the region’s endowments in
cocoa and gold, and the thriving commercial environment in Kumasi, the capital of the region,
produced a formidable elite whose interests the UGCC had promised to protect. However,
with Nkrumah’s massively popular CPP government in power, an ethno-nationalist Ashanti
movement sprung up largely in response to two policies: the seat allocation in the 1954
Legislative Assembly and the freezing of the price of cocoa at 72 shillings.
Beginning in 1953, the Report of the Commission of Inquiry into Representational and
Electoral Reform had allocated the Ashanti Region with roughly 20% of the seats in the
1954 Legislative Assembly. This was a drop from the 25% share the Ashanti Region had held
in the 1951 Legislative Assembly. This immediately visible loss of power became the first
major rallying point for an Ashanti-regional opposition (ibid, 23). The youngmen of the NLM
movement then sought an alliance with the Asantehene and other Ashanti chiefs, despite
having themselves rallied against chieftaincy power prior to the NLM formation, in order to
gain both economic and cultural resources at the chiefs’ disposal (ibid, 40-48).
The other controversial CPP initiative which solidified the NLM-Asantehene coalition
was the CPP’s decision to not only continue the Cocoa Marketing Board (CMB)7 but also to
7 The colonial powers had created the Cocoa Marketing Board to protect farmers fromexposure to the fluctuations of the international price of cocoa. By setting a price, andempowering the CMB as the only purchaser of cocoa in the country (what Bates (1981)refers to as a monsopony), the colonial government would become the regulator of the
52
freeze the price of cocoa at 72 shillings per load. Though the CMB did provide some level of
protection for peasant farmers, large commercial farmers were particularly against the CMB.
The issue of cocoa regulation was very politicized at this time. As Allman (1993) explains,
“the economic welfare of Asante, as a whole, was inextricably tied to cocoa. Approximately 51
percent of the cocoa exported from the Gold Coast in 1954-55 was produced in Asante at a
time when the Gold Coast was the largest producer of cocoa in the world. Cocoa accounted for
over 80 percent of the total value of domestic exports” (36-37).
In response, Nkrumah began a campaign to disunite the Ashanti-based opposition. As a
first step, he widely publicized the idea that the 72 shillings price set by the CMB was accepted
by poor farmers and that it was only elites represented in the NLM which sought to double the
price to 150 shillings per load (Herbst 1993, 79). Soon after, the CPP rolled out a propaganda
campaign to emphasize the degree to which historical ethnic empires, namely the Ashanti
Empire, wanted to again dominate other ethnic groups as they had done throughout the 18th,
19th and early 20th centuries.8
Finally, the major initiative to disunite the Ashanti-based opposition was Nkrumah’s
strategy of co-optation of potential co-ethnic allies. First, Nkrumah began to chip away
cocoa industry. As it were, however, the price at which cocoa was set remained fairly lowin comparison to the international market price, and Ghanaians began to view the CMBas illegitimate when surplus funds were not re-directed back to the localities (Allman 1993,38-39).
8 For instance, an October 16, 1954 article in the pro-NLM Ashanti Pioneer cites a rulingin Accra Market that Ashanti cloth sellers in Accra could only sell through Ga cloth sellers.The author of the article was of the opinion that the ruling was intended to incite a tribalisticrivalry between the Gas and the Ashantis, by establishing Ga ownership priority in theirtraditional Accra homeland (“Baffoe’s Death Steps up Liberation’s Support” 1954). In thecolonial period, the Ashantis had been allies with and adversaries of the Gas at different pointsin time. Alternatively, a pro-government newspaper reported that the Ashanti FederationMovement aimed to re-institute Ashanti autocratic rule in Ghana and that it represented eliteinterests as opposed to the rural cocoa farmers which had agreed with the CPP government’scocoa price (“Federation Movement Aims At The Revival of Autocratic Rule in Ashanti”1954).
53
at chieftaincy hierarchies by catering to sub-chiefs who had lost power under the colonial
creation of now strong paramount chieftaincies, including Akan chiefs who now reported to
the Asantehene. Nkrumah co-opted these sub-chiefs by promoting them, putting them on
government payroll and demoting other chiefs deemed problematic for CPP rule.9
Secondly, in February 1955 the CPP made moves to co-opt the Brong and Ahafo
tribes by considering a petition to create a Brong-Kyempim Traditional Council as separate
from the Asanteman Traditional Council within the CPP-dominated National Assembly.
The Brong-Ahafo territory had long been a part of the Ashanti Empire and that the
CPP-government considered this issue in 1955, as Allman (1993) puts it, “was a clear
indication to Asantes that the nation was about to be assaulted on all fronts” (99).10
In reaction, the NLM Movement began to advocate for a federal system of government.
The NLM, though fiercely defensive of Ashanti interests in rhetoric used in Kumasi-area
newspapers11 , elsewhere tried to present itself as a non-ethnic party vying for strong regional
institutions which would serve as a protective barrier to Nkrumah’s increasingly centralized
CPP government. The NLM thus made direct appeals to other regional and/or ethnic political
parties and organizations to encourage them to join the movement for regional power.
9 Printed in the Ashanti Pioneer on December 9, 1954, the Ashanti empire thus beganmaking direct political appeals for a federal government for Ghana in order to protect thepro-federation Ashanti movement and the need to return to chieftaincy; “Secondly, Nana OforiAtta said, the Ashantis wanted to regain our traditional institutions and usages and respectfor Chieftaincy which were gradually being snatched away by the introduction of party politicsin the country. Even the whites attached great importance to our traditional institutions andthey consulted the Chiefs before issues of vital importance affecting the country were enacted”(“J.P.C. Debates Asanteman Council...” 1954).
10 The petition was eventually approved in 1959, creating a separate Brong-Kyempim Counciland Brong-Ahafo Region.
11 For instance, the Ashanti Pioneer printed a story about the Asantehene’s endorsementof the National Liberation Movement’s quest for a federation. After the Asantehene stated‘Ashanti knows no retreat’ the crowd responded with the Ashanti War Cry (“Otumfuo BacksFederation Demand...” 1954).
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The ethno/regional organizations associated with the Northern territories12 and the
present-day Volta Region13 were particularly prominent at this time. The parties meeting
with the NLM included the Northern People’s Party (NPP), the Togoland Congress (TC),
the Ghana Action Party (GAP), the Muslim Association Party (MAP), the Ghana Congress
Party (GCP), and the Anlo Youth Organization (AYO). Further, the Daily Echo reported
on September 3, 1955 that the GCP, GAP, AYO, and Ghana Youth Federation had officially
merged with the NLM, while the MAP was an NLM affiliate (“Colony Parties Merge Into
NLM” 1955). In fact, though an Ashanti-Ewe rivalry is widely acknowledged in Ghana’s Fourth
Republic, the Ashanti Pioneer was reporting on the details of the Ewe Unification Movement as
it mattered for the NLM’s own federal negotiations (“Anlo Chiefs For Unification” 1954).
In November 1956, the CPP government appointed the Greenwood Commission to
study the system of local government. The subsequent Greenwood report described two plans
12 Northern interests were concerned with the fast-paced nature of the Gold Coast’sadvancement to independence. Historically under-developed due to its great distance from thecoast as well as its separate administration under British rule, Northern interests were primarilyconcerned that the North should be developed prior to independence so that it would not facepolitical disadvantages in a newly-independent nation (Massing 1994, 38-39). The number ofWestern-educated citizens were fewer in the North as compared to the southern areas, andthe well-founded fear was that early self-government would essentially translate into rule bynon-Northerners.
13 The Ewe organizations of the present-day Volta Region represented at NLM meetings werethe Togoland Congress and Anlo Youth Organization (AYO). Previously a German colonialpossession, the Togoland colony was split into British and French protectorates after WWI. Anarea dominated by Ewes, local leaders of these protectorates saw three options before themin the approaching independence era: (1) the protectorates could each become independenton their own; (2) they could join together and become independent; or (3) they could jointhe Gold Coast. The Togoland Congress ultimately decided that it would (unsuccessfully) viefor unification of British Togoland with French Togoland separate from the Gold Coast. TheAnlo Youth Organization represented the southern-most tip of the present-day Volta Region- an area dominated by Ewes but always part of the Gold Coast colony. The AYO eventuallydecided it wanted the British trans-Volta Togoland territory with Ghana. A 1956 Plebisciteheld in the British Togoland Protectorates saw voters choose to separate from the FrenchProtectorate and to join the Gold Coast (Amenumey 1968; 1989).
55
of local government institutions it saw as viable for the Gold Coast. The CPP government
rejected Plan B of the report, which would have established strong regional governments, and
instead adopted Plan A whereby the central government would maintain authority in local
government through district councils (Saaka 1978, 37; Amegashi-Viglo 2014, 14). However,
given the significant affront Plan A was to Ashanti authority as well as British concerns about
leaving Ghana in the hands of a CPP government which had not granted the opposition
any concessions, a compromise had to be made. In early 1957, just prior to independence,
Nkrumah’s CPP government agreed to create semi-independent regional governments. As
reported on February 11, 1957 in The Liberator, five regions would be created, each with its
own Assembly, House of Chiefs, and Head of State, and no provision was made for a separate
Brong Ahafo region (“Kumasi Rejoices Over Contents of White Paper...” 1957). Celebrations
in the Ashanti Region would not last long, however, as this concession would be eliminated
soon after independence.14
2.3.2 The Post-Independence CPP Regime
After independence, oppositional, regional and chieftaincy power continued to suffer at
the hands of Nkrumah. The Avoidance of Discrimination Act in 1957 prevented any political
party from associating along sectional identities, thereby outlawing the NLM. The United Party
(UP) was thereby formed, made of the NLM, NPP, TC, AYO, and MAP (Owusu 1970, 278).
Also during this initial independence period, Nkrumah “handpicked Regional Commissioners as
representatives of government, even though these were to be chosen by the Regional Council
(House of Chiefs) [and] without awaiting local government elections, he declared district
14 Already suspecting that the agreement on regional governments would not be enforced, thePresident of the Asante Youth Association made a speech on February 26, 1957 threateningAshanti secession if the agreement was not implemented (“Ashanti Bent Upon Secession If..”1957). On March 1, 1957, it was reported that Cabinet Ministers were delivering speechessuggesting that the semi-independent regional governments would not be implemented (“AnyBreaches Of The Constitution Will Destroy Bonds Between Component Regions.” The Libera-tor, March 1, 1957). The Gold Coast achieved independence on March 6, 1957.
56
councils the main units of local government, thereby abolishing and dissolving the regional
councils” (Massing 1994, 4). The compromise on regional governments Nkrumah had used to
guarantee independence was abolished early in the post-independence era.
Matters quickly headed downhill as Nkrumah sought to secure his regime through
authoritarian measures to disrupt the original Ashanti-based opposition. First, the opposition
was crippled by arrests and imprisonment of its members under the 1958 Preventive Detention
and Deportation Acts (Allman 1993).15 Soon after, the Stool Lands Control Act of 1959
(1961) prevented chiefs from receiving revenue from communal lands (Owusu 1970, 281),
the 1961 Local Government Act forbade chiefs from serving as members on local councils
(Massing 1994, 56) and the 1960 Constitution, which removed from the Queen of England as
the Head of State, gave Nkrumah absolute veto power over legislation (Schwelb 1960). By
1964 chieftaincy power was at an all-time low and the CPP was the only legal party in the
country. On February 24, 1966 a successful coup carried out by the military and the police
ousted Nkrumah from power while on a diplomatic mission in Asia. Nkrumah remained in exile
in Guinea thereafter, never returning to Ghana.
2.3.3 The NLC and the 1966 Coup
Though the National Liberation Council (NLC) came to power backed by a cross-ethnic
coalition, it became associated with Akan interests and helped to deliver the election of an
Akan-centric Progress Party (PP) regime. Under Lt .Gen. Joseph Ankrah, the NLC took over
a Ghana bankrupted by the Nkrumah regime’s heavy state-spending. The NLC dismissed the
CPP government and made membership in the CPP illegal. While espousing anti-centralization
and anti-Nkrumah rhetoric, the NLC proved quite committed to return Ghana to democratic
rule. An 18-member Constitutional Commission headed by Chief Justice Edward Akufo-Addo
15 The 1958 Preventive Detention and Deportation Acts empowered the government to“arrest and detain for five years anybody suspected or found acting in a manner prejudicial tothe defense of Ghana, to her relations with other states and to state security” (Boahen 1975,194). In practice, this Act was used to quiet any and all forms of opposition.
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(one of the ‘Big Six’ UGCC founders) was formed on November 18, 1966 to gather public
opinion about a new constitution (Frempong 2007).16 Later, a 150-member Constituent
Assembly also met and adopted a constitution that barred a one-party state, prevented MPs
from ‘crossing carpet’ (i.e., switching parties, as Nkrumah had forced many opposition MPs
to do during his reign) and created a Prime Minister alongside a (semi-ceremonial) President.
As advisors to the Prime Minister and President, the Council of State was composed of the
Prime Minister, the Speaker of the National Assembly, the Leader of the Opposition, and the
President of the National House of Chiefs (Owusu 1979).
Chiefs and regional interests were explicitly supported by the NLC.17 With the deposal
of Nkrumah’s CPP government, the original chieftaincies were restored and many of the chiefs
that Nkrumah had promoted or made into Paramount Chiefs were demoted (Massing 1994,
5). During this time the Chieftaincy Act of 1971 created the National and Regional House of
Chiefs institutions, still politically important in Ghana today (Pul 2003, 45-46). Traditional
interests were also enshrined into local government as local councils were elected partly by
traditional authorities and partly by the public (ibid, 64). Above local councils sat district
councils, whose members were half-elected and half-appointed by these local councils (i.e.
50% traditional interests). Finally, above District Councils sat the Regional Councils originally
created, but immediately dismissed, in the pre-independence compromise between Nkrumah
and the NLM.
16 Though the NLC and Busia’s regime were associated with traditional interests/chiefs,during this Constitutional Commission chiefs had supported the creation of a no-partysystem. This suggestion was strongly opposed by the intellectuals and middle-class elite whichdominated by the Constitutional Commission and subsequent Constituent Assembly (Owusu1979, 101).
17 Though regional and chieftaincy interests were supported, the North particularly suffered atthe barring of CPP members from office as well as the replacement of administrative officers.As Massing (1994) explains, “In the North an entire generation of politicians was retired afterthe coup: most of them were barred from holding office for 5-10 years” (59). The historicaldisadvantages faced by the North would continue.
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Parliamentary elections held in August 1969, saw Kofi A. Busia’s Progress Party (PP) and
Komla A. Gbedemah’s National Alliance of Liberals (NAL) as the top seat contenders. The
Progress Party won the election with 105 out of 140 seats and voted Busia as Prime Minister,
while the NAL won 29 seats (Frempong 2007). Edward Akufo-Addo (the late father of Nana
Akufo-Addo) was subsequently appointed to the largely-ceremonial Presidency.
2.3.4 Busia and the Progress Party (PP)
Rather than justifying centralization as protection against ethnic divisions a la Nkrumah,
Busia’s PP government centralized institutions in the name of alignment with the chiefs and in
order to perpetuate an exclusionary pro-Akan regime. Between enforcing strict interpretations
of institutional rules to exclude political opponents while failing to enforce laws against his own
allies, issuing the 1969 Alien Compliance Order and allowing ethno-political biases to enter in
bureaucratic downsizing policies, Busia’s regime was very clearly understood as a continuation
of the exclusionary and elitist pre-colonial UGCC party, but perhaps with an even stronger
pro-Akan ethnic bent.
While the NLC had emphasized decentralized government, tradition, and chieftaincy
power, Busia’s PP government retained a high degree of centralized power and instigated
ethnic flare-ups. For instance, Busia’s regime continued to play ideological and ethnic games
by persisting with anti-Nkrumah policies previously instituted by the NLC, and in filling cabinet
posts with ethnic Akans (Brown 1983, 443). However, three ethnic-fueled events in particular
cemented the public’s interpretation of Busia’s government as exclusionary.
First, the PP government did not allow the opposition leader, Gbedemah, to take his
Parliamentary seat as representative of the Keta Constituency because, as a former CPP
party member, he was barred from holding office for 10 years. This was a controversial ruling
because Gbedemah had been dismissed from Nkrumah’s government in 1961 and remained in
exile for some time. That the NLC and Busia’s Progress Party were associated with Akan, and
59
particularly Ashanti, interests and were now barring a prominent Ewe opposition leader from
office provided some groundwork for a major ethnic divide.18
Frempong (2007) argues that Gbedemah’s presence in Parliament would have helped to
smooth over ethnic politics because this experienced politician would have had a moderating
influence on his younger opposition colleagues (14). This issue would become politicized to an
even greater extent when Busia’s Finance Minister, J.H. Mensah, was found to be in violation
of Article 61 which stated that ministers could not hold any other office of profit while in
office. Though calls were made for Mensah’s resignation, Busia refused to sack him, creating
an appearance of a double standard (Frempong 2007).
Second, due to perceptions about Nigerian dominance over Ghanaian markets in Accra
and other city-centers, the PP government used this issue to scape-goat foreigners for Ghana’s
economic troubles. Busia issued the Alien Compliance Order on November 18, 1969 forcing
the expulsion of at least 100,000 foreigners from Ghana. Partially because they did not blend
18 Compounding this Ewe issue, an important ethnic matter arose early in the NLC regimewhich has had a lasting effect on the politicization of an Ashanti-Ewe rivalry. Two militaryofficers who had participated in the NLC coup were Brigadier Akwasi A. Afrifa, an Ashanti, andLieutenant General Emmanuel K. Kotoka, an Ewe. To hear the story from an Ewe perspective,Kotoka was known as a fierce and undefeatable warrior who used traditional religious magicto protect himself on the battlefield. Kotoka and Afrifa became good friends during their timestationed in Kumasi. It is believed that Kotoka let his guard down and visited his shrine in theaccompaniment of Afrifa, thus exposing his only weakness in his invisible armor: the back of hisankle. In an abortive coup attempt by junior officers, this information was used to kill Kotoka.In defense of Afrifa, an Ashanti perspective emphasizes that Afrifa was in the northern partof Ghana at the time of the murder and thus could not have participated in Kotoka’s death.Still, many Ewes contend that Afrifa was the mastermind behind the murder. It is still possibleto hear individuals in Eweland warn that though Ewes can be close to Ashantis, they shouldnever trust them with their life because there is the great likelihood that they can betray youas Afrifa betrayed Kotoka. Indeed, I will later discuss the ethnic bias in hiring practices by theRawlings’ regime in the 1980’s. These biased hiring practices were largely restricted to militaryemployment. Some defend these hiring decisions, citing Afrifa’s murder of Kotoka, becauseRawlings could not absolutely trust ethnic-Akan soldiers because of the possibility of betrayal.The Kotoka International Airport in Accra is located at the site of Kotoka’s murder and thusnamed in his honor.
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in as the Nigerian Hausas could in Hausa-speaking communities in Ghana, the Yorubas were
particularly affected by these expulsions (Adida 2014). Still, Hausa-speaking communities
throughout Ghana were harassed as government officials combed through communities trying
to find foreigners. Northerners living in the south often reside in segregated Zongo communities
where Hausa is the lingua-franca. Many ‘foreigners’ were born in Ghana and had never been to
Nigeria before. Others had integrated into Ghanaian society through marriage and had children
born in Ghana. The expulsion of these individuals, as well as the harassment of Zongo-area
residents, created a long-lasting division between a great deal of Northerner votes and the PP
and its successor parties. Still today rumors about the expulsion of foreigners are used to rouse
anti-NPP (New Patriotic Party) sentiment during election time.
Finally, because Nkrumah had over-extended the nation’s budget in adopting massively
inclusive-employment policies and sinking money into protecting nationalized industries,
making them unproductive and causing their failure, Busia’s government was forced to
rationalize expenses. As part of these efforts, the sacking of 568 public servants in 1970,
termed Apollo 568, created controversy after the PP government was accused of selecting
opposition sympathizers to be fired (Frempong 2007). Overall, this move also alienated the
civil service.
The exclusionary and ethnic interpretation of Busia’s PP government thus became
widespread. Massing (1994) summarizes the state of affairs at this time:
“Non-Akan people and particularly Ewe and Ga felt excluded from the ruling
coalition; the Volta and Northern regions which had manifested their opposition
in the elections, reduced contact with government; by 1970, even the Akan and Fante
broke the traditional Akan alliance. The urban professional bias of the Party excluded
other upwardly mobile groups, e.g. traders, farmers, entrepreneurs. The civil service
and the military were hostile to the government and demanded the rectification of
inequitable policies” (66).
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Other than ethno-regional sectional issues induced by the PP government, Busia’s regime
also retained a significantly high degree of centralized control despite Busia having been
outspoken about decentralized government during the NLC tenure. For one, while the Regional
Councils were reinstated, Busia retained the right to appoint the chairmen of the district and
regional councils and could dissolve any Regional Council as he pleased (Massing 1994, 5). In
another case, and very reminiscent of Nkrumah’s meddling in the judiciary during his time in
power, Busia refused to accept a Supreme Court ruling which found that a public servant had
illegally been forced into early retirement, saying that in this case the court had ‘exceeded its
competence’ (Frempong 2007).
However, in addition to the stirring of ethnic issues, the alienation of the civil service as
well as the military (both of which experienced funding cuts), and the hypocritical grasp on
centralized control, the straw that really broke the camel’s back was the 1971 devaluation of
the cedi. Cedi devaluations are extremely politicized in Ghana and are associated with harming
urban interests because food and other imported goods become more expensive. As Massing
(1994) writes,“The grave economic crisis made regionalism and ethnicity even more important
at the end of the Busia period than at the end of the Nkrumah regime” (66). On January
13, 1972, a military coup put Colonel Ignatius K. Acheampong and the National Redemption
Council (NRC) in power.
2.3.5 Acheampong, the NRC and SMC-I
Like Nkrumah, Acheampong argued that centralized control was necessary to rid the
nation of ethnic divisions as well as to put the country back on sound economic footing.
Also like Nkrumah, Acheampong issued policies co-opting chiefs and suppressing ethnicity.
The suppression of ethnicity and a contraction in the economy resulted in an environment of
heightened ethnic politicization, with particular opposition stemming from Akan-dominated
regions, and resulted in an overall unstable authoritarian regime overthrown in a palace coup in
1978.
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Acheampong’s National Redemption Council (NRC) came to power in 1972 citing
the need to re-unify the nation. The NRC regime’s first step was to arrest more than
1,300 politicians and limit the freedom of speech (Massing 1994, 5-6). Actions taken by
Acheampong’s government, such as banning the use of the word ‘tribe’, avoidance of ethnic
bias in political appointments, and increasing centralized control over local government
institutions, was intended to quell ethnic dissention. In reality, attempts to stamp out the
politicization of ethnicity only reinvigorated ethnic mobilization (ibid, 68).
Acheampong paired the anti-ethnic flavor of his regime with highly centralized institutions.
This was done to de-emphasize participatory politics and thus regional and local influence: “In
effect, local government in Ghana from 1974 [had] ceased paying even lip service to the idea
of local autonomy. The new system made local government, in essence, the local agency of
central government” (Saaka 1978, 43-43). As an example, now the Regional Commissioners
and the District Chief Executives were both political appointees from the center (ibid, 45-46).
Acheampong’s regime also promoted a ‘return to tradition’, co-opting chiefs support while
de-emphasizing ethnicity. The District Councils were now composed of two-thirds members
nominated by the government and one-third representative of traditional bodies. Below
District Councils sat Municipal, Urban, Area, and Local Councils which would also consist of
appointments made by traditional councils and the government (ibid, 45). Chiefs were directly
employed under Acheampong’s regime and received regularized payment from the government
(Massing 1994, 68). By empowering the central government and traditional leaders while
excluding regional-based and educated elite voices, Acheampong’s regime was reminiscent of
the centralized strategies used under colonial rule.
Though Acheampong attempted to increase national unity, regional and ethnic issues
grew and created more structural problems. As happened during the Nkrumah and Busia
regimes, economic difficulties finally exacerbated the situation: “In 1975 opposition and
strikes by unions, students, professionals, churches and regional traditional authorities against
the government grew so strong that the military purged the NRC of civilians and placed
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government in the hands of an Acheampong-led Supreme Military Council (SMC) which
promised a return to constitutional rule and civilian government for 1978/79 under a so-called
non-partisan Union Government” (Massing 1994, 6).
Acheampong had vowed that power would not be handed over to a civilian regime until
the Ghanaian economy was on sound footing (Frempong 2007), but continued economic
failure forced action.19 The NRC was modified into the SMC and pushed a Union Government
concept which would implement a no-party democratic government where the army and
police would share power with civilians (Hitchens 1979). An ad hoc committee was formed to
survey public opinion about ‘Uni-Gov’ and a highly-questionable March 30, 1978 referendum
claimed that Uni-Gov was favored 54% to 46% (Frempong 2007). Three regions, the Ashanti,
Brong-Ahafo, and Eastern Regions (all with Akan-dominant populations), had a majority
opposing the Referendum, despite Acheampong’s Ashanti-regional roots.
After the Uni-Gov referendum passed, a Constitutional Commission was formed in April to
submit a draft constitution by October. By this time, widespread discontent existed amongst
the Akan regions, the Ewes of the Volta Region, and increasingly the Fanti and Ga (Chazan
and Le Vine 1979, 189). Further, the chiefs were demanding public pay-raises and “regional
leaders demanded more equitable distribution, [meaning] that the depoliticization attempts of
the early years were thwarted by growing ethnic discontent and regional disparities” (Massing
1994, 68). A palace coup removed Acheampong from office on July 5, 1978.
2.3.6 Akuffo and the SMC-II
Paralleling Busia’s reaction to Nkrumah’s regime, Lt. Gen. Fred Akuffo’s short-lived
SMC-II regime reacted against the suppression of ethnicity under Acheampong’s rule and
19 Chazan and Le Vine (1979) describe the 1977 situation as a time of sharply fallen exportprices, commonplace smuggling, a staggering rate of inflation, and a cedi which had dropped inreal terms to 1/6 of its official rate (181). Herbst (1993) similarly describes how Acheampong’selimination of most of the devaluation implemented by the Busia regime led to massiveovervaluation of the cedi, crippling the Ghanaian economy (23).
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became aligned with Akan and elite interests. The SMC–II regime was in many ways a
continuation of the highly-centralized SMC-I, except with more guarantees for Akans. Akuffo
also attempted to implement economic and anti-smuggling reforms, but this would not be
enough to dissuade the successful AFRC coup led by junior officers on June 4, 1979.
Akuffo’s reform efforts were noble, but had limited success, and it became clear that
Akuffo was not fully in control of the SMC-II regime. While Acheampong’s NRC regime had
proven unable “to cope with the economic crisis and to restore at least creditworthiness and
an air of credibility in the economic domain” (Massing 1994, 66), Akuffo’s SMC-II regime
implemented reforms to try and remedy the economic and political situation in Ghana. For
instance, Chazan and Le Vine (1979) credit Akuffo with attempting to reverse the decline in
cocoa revenues by addressing smuggling and mismanagement within the Cocoa Marketing
Board, by deporting two Lebanese merchants for tax evasion, and by devaluing the cedi
(something which Acheampong had refused to do) (202). The anti-smuggling efforts were
only somewhat successful (Amamoo 2000, 174) and, importantly the reform efforts did not do
much in the way of alternating either the overall distribution of power or the system for the
accumulation of resources. When Akuffo decided not to prosecute Acheampong and released
him from prison, this was taken as a clear sign that former leaders were safe and Akuffo would
not make any significant changes to the power distribution guaranteeing elite wealth and
privilege (Goldschmidt 1980).
The Akuffo regime began taking steps to transition to civilian constitutional rule. In
November 1978, the Mensah Commission published its proposals for a new Constitution.
Non-partisan local council elections were also held. These elections prompted the SMC-II
regime to lift the political party ban, in effect since the NRC coup in 1972, because local
council candidates were well-known former members of either the CPP or PP and citizens
overwhelmingly voted along party lines. The political party ban was lifted on January 1, 1979,
and a Constituent Assembly established to discuss the new Constitution completed its work in
May 1979 (Goldschmidt 1980). Nonetheless, on June 4, 1979, Jerry John Rawlings and other
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junior military officers in the Armed Forces Revolutionary Council (AFRC) overthrew the Akuffo
government.
2.3.7 Rawlings-I and Limann
The AFRC takeover was economically-motivated, like past coups, but also differed in that
it specifically aimed to change the mechanisms guaranteeing elite wealth and power. Though
critical of traditional power, the AFRC did not espouse an ethnic-orientation and was more
concerned with economic power distributions than it was with ethnic divisions. During the
three-month long time in power, the AFRC conducted a ‘house-cleaning exercise’, supervised
Presidential and Parliamentary elections, and oversaw the transfer of power from military to
civilian rule on October 1st, 1979.
Prior to June 4th, Flight Lieutenant Rawlings and several other members of the air force
had been arrested and tortured for participating in a failed coup attempt several weeks prior.
On June 3rd, a small group of junior officers released Rawlings from a military prison, and
on June 4th the coup was publicly announced. The stated goal of the June 4th coup was to
clean-up the failures that Akuffo’s regime had refused to address. The house-cleaning exercise
that commenced included the arrest and charging of military officers, former and current
officials, and wealthy businesspeople with crimes related to corruption and embezzlement.
Famously, eight senior military officers, including three former heads of state (Afrifa20 ,
Acheampong, Akuffo), were accused of corruption and embezzlement and were executed on
June 16th and June 26th, 1979. The AFRC also sent hundreds of officers and civilians to
long prison sentences on accusations of corruption, blew up Makola market (the major trading
center in Accra), and sacked hundreds of top civil servants and police officers for corrupt
20 Afrifa had only been in power for a little over a year during the NLC tenure, after JosephArthur Ankrah was forced to resign amidst a bribery scandal. Afrifa won the Parliamentaryseat for the Mampong North constituency as a candidate for the United National Convention(UNC) in the June 18th, 1979 elections, but was executed on June 26th, 1979. That Afrifawas singled out for execution, given his short tenure as head of state, is popularly believed aspunishment for Afrifa’s involvement in Kotoka’s murder in 1967.
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practices (Hanson and Collins 1980, 3; 18). The blowing up of Makola was part of a broader
agenda to end hoarding by forcing traders to sell at controlled prices which the poor could
afford. Those found to be uncooperative faced public discipline and other sanctions (Ahiakpor
1991, 587-588). Rawlings used populist rhetoric and promised to hold elections to legitimize
the coup.21
Despite the on-going house-cleaning exercise, the Presidential and Parliamentary elections
were still held on June 18th and the handover to civilian government was only postponed from
July 1st to October 1st. The new 1979 Constitution, based on the proposals by the Mensah
Commission and finalized by the Constituent Assembly, was still implemented. The Mensah
Commission had emphasized local government institutions and the 1979 Constitution made
the district the basic local government unit. Local and traditional power thereby increased,
as traditional members would hold a maximum of one-third of the district council seats, and
because “an amendment of the constitution [had to] be accepted by two-thirds of all local
government councils, and [as] the chiefs [were now] represented in the Lands Commission and
the regional police committees” (Goldschmidt 1980, 56-57).
In the 1979 elections, the major parties were the PNP, whose candidate was Professor
Hilla Limann (a Northerner and the eventual winner), the Popular Front Party (PFP), whose
candidate was Victor Owusu (a prominent member of the Ashanti-based National Liberation
Movement in the pre-independence period), the United National Convention (UNC), whose
candidate was Paa Willie Ofori-Atta (a UGCC founding member and ex-Foreign Minister in
Busia’s government), and the Action Congress Party (ACP) whose candidate was Colonel
Bernasko (a Fante who worked as the Commissioner for Agriculture under Acheampong’s
NRC). Massing (1994) describes the broad-based nature of the PNP as compared to the PFP:
21 See Hansen and Collins (1980) on the importance of coup legitimation in Ghana.
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“the PNP represented local combinations of class, ethnic and other group factors
rather than presenting a homogenous Akan cum elite-professional alliance as the PFP;
and the PNP stressed the centrality of local community and regional issues (in the
North) in politics. Presidential candidate Limann, being Imoru Egala’s nephew and
political successor, campaigned on Nkrumah’ist issues like Egala himself who as an
ex-CPP member was barred from running for office” (77).
Goldschmidt (1980) explains that though many former PP members joined the social
democratic PFP “embracing Busia’s ideals of liberalism and human rights” (50-51), not
all former PP members joined the PFP. Some were attracted away to the UNC, led by
Ofori Atta, a former head of state during General Afrifa’s NLC regime. For the first time,
the 1979 elections saw the major Akan ethno-linguistic groups split their votes. The PFP
relied on Asante and Brong votes, the UNC relied on an Ewe-Ga alliance with Akan votes,
while the ACP relied on southern Fante votes, leaving PNP’s Limann to secure a narrow
base of Northern and Nkrumah’ist votes. The PFP and PNP each secured enough votes to
push the election to a runoff. In the subsequent election the Akan-Ewe-Ga votes which had
supported the UNC and the ACG’s Fante votes mostly transferred to PNP’s Limann (Jeffries
1980), making him the first Northerner President in Ghana’s history. Importantly, Limann’s
government seemed unaware of its narrow power base (Massing 1994, 79) and quickly made
moves to alienate itself from the military.
Limann began to publicly separate himself from Rawlings and the latter was forced into
early retirement after he refused to sit on the State Council (Massing 1994, 79). Unlike past
regimes, Limann’s government was not wide-reaching enough to achieve national support, and
its ethno-regional base was too narrow to guarantee the regime. Further, Rawlings and his
associates began to openly criticize Limann’s government after it failed to end corruption and
revitalize the economy (Brown 1983, 456). Limann came to understand Rawlings as a threat,
attempted to label the June 4th Revolution as tribalistic in nature and accused Rawlings of
tribal aggrandizement. As Brown (1983) writes, “at the core of the accusations during 1980
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and 1981 was that Rawlings and his associates were Ewes who were seeking to use the 4 June
‘revolution’ and their earlier domination of the Armed Forces Revolutionary Council (AFRC) in
order to further their own narrow interests of Ewe domination” (ibid, 457). However, there is
more evidence that it was actually Limann’s own government which was stirring the ethnic-pot:
“When the government appointed representatives from the regions to the 27-member Council
of State it chose chiefs, academics and professionals without roots among the Akan and Ewe”
(Massing 1994, 79).
The increasingly divisive tactics used by the Limann regime were not backed by a
broad-based constituency that cut across regional and ethnic power bases. As Massing
(1994) writes, “Despite Northern support for the victorious PNP, it had a smaller and more
fragmented power base than earlier parties. Notwithstanding, the victorious presidential Hilla
Limann used heavy-handed tactics towards opposition groups, warned of another military
takeover and personally attacked Flight Lieutenant J.J. Rawlings. During the 26 months of its
existence the Limann government was neither able to correct the economic problems inherited
from its predecessors nor reform the political process” (6). The Limann regime’s inability to
change the economic system, where wealth was concentrated in the hands of a few rich and
well-connected individuals while the poor purchased goods at expensive and uncontrolled prices
on the black market, prompted Rawlings’ second coup on December 31, 1981 (Ahiakpor 1991,
593).
2.3.8 Rawlings-II
Rawling’s highly-centralized military authoritarian regime, the Provisional National Defense
Council (PNDC), relied on a narrow political base, surviving through the violent enforcement of
the regime. During PNDC rule, Rawlings appealed to other ethnic groups, notably the cocoa
farmers in the Akan-dominated Ashanti, Eastern, and Central regions, but was still pegged
as ethnically-biased towards Ewes, particularly in regime hiring practices. When Rawlings led
the transition from the PNDC regime to Ghana’s Fourth Republic in 1991, he implemented a
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highly-centralized democratic system reminiscent of Acheampong’s NRC institutional designs.
As before, opposition coalesced around Akan interests.
When Rawlings’ PNDC staged the 1981 coup, he initially held fast to a populist
Nkrumah-esque rhetoric, with direct appeals made to workers and rural-dwellers. The major
issue of concern was the economic and political distribution of power, with particular focus on
the black market and hoarding. The overvalued cedi had made basic goods very cheap and
abundant. In response, traders hoarded goods to force consumers to pay at high black market
prices. Rawlings saw this behavior as the epitome of everything that was wrong with Ghanaian
society: the rich had access to basic goods while the poor lost the ability to purchase bread,
sugar, milk, and other basic needs. The PNDC response to traders was harsh and the regime
was accused of publicly stripping and beating market women and those accused of hoarding.
The ‘second coming of Rawlings’ was characterized by heavy government interference
in the economic market and a furthering economic decline (Jeffries 1982; Ahiakpor 1991),
but Rawlings quickly realized the extent of economic problems and in 1983 turned to the
International Monetary Fund (IMF) to ease the worsening situation. It did not take long for
Rawlings’ socialist ideology to be replaced by market capitalist principles, per IMF stipulations.
Beginning in 1983, Rawlings instituted tough IMF restructuring policies with the help of
repressive tactics (Herbst 1993, 46). The cedi was devalued in such a way that the allocation
of foreign exchange was altered dramatically. In essence, this meant that the PNDC would be
unable to easily influence the exchange rate in the future, making the rate externally reliable
and thereby encouraging foreign investment (ibid, 51).
The Rawlings’ military regime certainly exhibited high levels of centralized control, but
this was not expressly justified in the name of national unity nor for the protection of particular
interests (though the regime was certainly also weary of Akan challenges to Rawlings’ rule).
Instead centralized control was necessary, it was argued, so that Ghanaians would accept
the tough restructuring of society, power, and economic affairs with which prior regimes had
miserably failed. The brutal enforcement of power made these restructuring reforms possible
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under Rawlings (Herbst 1993). Additionally, some also point to the fact that the economic
situation at the time was so terrible that citizens largely withdrew from the state, allowing the
regime to push through economic reforms that otherwise would have faced strong resistance
(Haynes 1999, 107; Herbst 1993, 32).
Though not a major issue pushed by the PNDC, ethnic divisions long in the making
became a polarizing issue for the regime. First, Rawlings is half-Scottish, half-Ewe, and
though resources were not particularly delivered to the Ewe-dominated Volta Region, certain
Ewe-preferences in hiring practices did lead to an overall public perception of the PNDC as
Ewe-biased (Herbst 1993, 87). Importantly, anti-PNDC ethnic sentiment came most strongly
from the Ashanti and other Akan groups. That mobilized Ashantis and Akan groups in general
have positioned themselves in opposition to Nkrumah’ist logics, which the Rawlings regime
was associated with, is not surprising. Rather, what is surprising is that Akan groups made
up the strongest source of opposition even though the primary benefactors of Rawlings’ 1983
Economic Recovery Program were the predominantly Akan cocoa farmers. As Herbst (1993)
describes, the devaluation of the cedi increased the price of cocoa and reforms pushed through
the Cocoa Marketing Board meant cocoa farmers were receiving higher prices for cocoa (81).
Herbst even points to the cocoa farmers as the big winners in Ghana’s structural adjustment
program while acknowledging that the PNDC never really received credit for this amongst Akan
constituents. Finally, the PNDC regime also began explicitly developing the historically-ignored
northern regions.
As part of his attack on the well-to-do, Rawlings’ continued his critique of chieftaincy
power. The AFRC’s 1979 populist coup had been based on heavy critique of traditional rulers,
particularly chiefs, but the 1979 elections brought Limann’s pro-chief civilian government to
power (Pul 2003, 46). When Rawlings’ PNDC regime took power again in 1981, he continued
to openly question the authority of the chiefs. This led to the passage of a 1985 amendment
to the Chieftaincy Act of 1971 which empowered the government’s discretion to recognize
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or withdraw recognition from chiefs (ibid, 47). It would not be until the passage of the 1992
Constitution and transition to democracy that this amendment was revoked.
By 1987, a policy of local government (misleadingly termed ‘decentralization’) was
announced and, via the Local Government PNDC Law 207, the District Assembly was
established. Two-thirds of assembly representatives were directly elected in the subsequent
local government elections of 1988 and 1989, while one-third of assembly members were
appointed by the PNDC. The PNDC also appointed the District Secretary who sat as the
head of the District Assembly. This local government system was reminiscent of the reforms
implemented during the Acheampong years, but, notably, traditional authorities’ influence was
no longer formally institutionalized within the assembly structure.22
Two years after the establishment of the District Assemblies, two delegates from each
assembly and civic and business organizational reps were sent to the National Consultative
Assembly to discuss a new constitution in April 1991. The new constitution was approved in
March 1992 and elections were held in November (Presidential) and December (Parliamentary).
Under newly-elected NDC President Rawlings, Ghana’s Fourth Republic was initiated on
January 1st, 1993.
2.4 Ethnic Voting in the Fourth Republic
The response to the Rawlings’ NDC regime was ethnic in nature, as had happened
with the highly-centralized regimes of the past. The top two presidential contenders in
the 1992 elections were Rawlings’ Progressive Alliance, itself a coalition of the National
Democratic Congress (NDC), National Convention Party (NCP), and the Every Ghanaian
22 Chiefs are still powerful political players in Ghana’s Fourth Republic. Massing (1994)found that the majority of those elected into the assembly were close relatives of establishedtraditional powers, particularly in the North (7). Similarly, traditional disputes also creepedinto the system when the PNDC “reorganized the districts on the basis of the former LocalCouncils” such that “the creation of new districts reflected ethno-political divisions and ethnicconflicts of previous years, as well as the demand by local groups to be represented in thevarious representative bodies” (Massing 1994, 7).
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Living Everywhere (EGLE) movement, against A. Adu Boahen’s New Patriotic Party (NPP).
A college professor of history, Boahen “was ideologically in the conservative-liberal tradition
of J.B. Danquah and K. Busia” (Jeffries and Thomas 1993, 334-335). Rawlings espoused
a political rhetoric critical of intellectuals and elites who sought to take advantage of the
common people, similar in ideology to the prior CPP regime. Boahen’s NPP won 30.3% of
the Nov. 1992 Presidential elections, as compared to Rawlings’ 58.4% and, citing electoral
irregularities (largely, though not wholly, refuted by Jeffries and Thomas (1993)), the party
boycotted the December 1992 Parliamentary elections.
The two major political parties which remained after the 1992 election, the New Patriotic
Party (NPP) and the National Democratic Congress (NDC), are widely understood as
representing the Akan and Ewe peoples, respectively. Fridy’s (2007a) article uses GIS maps
to demonstrate that the NPP and NDC party strongholds have consistently been located in
the respective Ashanti (Akan-dominated) and Volta (Ewe-dominated) regions. Determining
the ways in which Ghanaians have voted, however, has been a great challenge for scholars.
This is mostly due to the fact that the Electoral Commission has never publicly released polling
station-level election data. Analyses of district level election data generates ecological fallacy
concerns, as researchers cannot be sure which voters in electoral districts are turning out for
the election and casting a vote.
Complicating matters is that both political parties are also associated with political
ideologies, somewhat distinct from ethnic concerns. The first tradition, known as the
Danquah-Busia-Dombo ideology, supports capitalism, business interests, federalism and/or
restrictions on the power of the central state. The second tradition, Nkrumahism, has
traditionally been in favor of socialist policies, concerned about the rural and poor population
sectors, and supportive of a strongly centralized state (Fridy 2007b, 57-58). While the
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Danquah-Busia-Dombo ideology was linked to the Akans23 from its inception, Nkrumahism
was more associated with ‘ethnic others’, underrepresented ethnic groups and ethnic groups
fearful of Akan hegemony in Ghana. Through the NDC, Nkrumahism did become associated
with Ewes over time, but this connection was only really solidified when half-Ewe J.J. Rawlings
staged his second coup d’etat in 1981.
In summary, ethnic divides in Ghana have historically existed primarily between Akans and
those likely to lose out from pro-Akan regimes. It is well known that Ashantis and Akyems
have always been prominent tribes within the Akan-based Danquah-Busia-Dombo tradition
but, beyond these two groups, it is more difficult to determine the voting patterns of smaller
Akan tribes. Though Northerners and Gas also historically leaned toward Nkrumahism, the
combination of the Trans-Volta Togoland Protectorate history, the belief that Afrifa betrayed
Kotoka, and the authoritarian-turned-democratic regime under J.J. Rawlings all served to
thrust Ewes forward as the most incorporated Nkrumahi’st ethnic group in the Fourth Republic.
2.5 Discussion
Centralized institutions and ethnic politics must be studied in conjunction to understand
regime change and historical institutional design in Ghana. The implementation of centralized
control has consistently provoked aggregate ethnic responses, either from Akans whose
interests are not protected by an anti-ethnicity centralized regime (i.e. Nkrumah, Acheampong,
and to some extent Rawlings) or from groups excluded from the particularistic nature of the
centralized regime (i.e. Busia and Akuffo), and consistently created unstable authoritarian
regimes. That the centralized nature of the democratic institutions in Ghana’s Fourth Republic,
inclusive of Presidential-appointments of very powerful heads of district assemblies (DCEs),
should produce a relatively unified Akan opposition front is not surprising. The only time in
Ghana’s history that the Akan vote had fractured was under Rawlings and the AFRC’s watch
23 Akan refers to the overall ethno-linguistic Twi-speaking group, while the major politicizedsub-groups strongly associated with the NPP are the Ashantis and Akyems.
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in the 1979 elections. And in that case the AFRC regime had specifically encouraged voters to
elect a responsible government which the AFRC would hold accountable (Jeffries and Thomas
1993), giving sub-Akan groups the opportunity to rise against the elitist and Ashanti-dominated
Danquah-Busia-Dombo political tradition.
What is surprising is that the centralized system in Ghana’s Fourth Republic has endured
without reform across six national elections. Further, unlike many other new democratic
regimes in sub-Saharan Africa, the correlation between party votes and ethnic groups have
continually decreased since the 2000 elections. Some might say that is a normal progression
under democratic elections as voters have greater opportunities to make retrospective and
prospective vote decisions with each passing election (e.g., Lindberg 2009). But other
perspectives point to the enduring nature of structural cleavages and party systems generated
by historical critical junctures that would be difficult to simply dissipate ( Lipset and Rokkan
1967; Collier and Collier 2002). The next chapter of this work details Ghana’s centralized
system of government, the fourth chapter uses Ecological Inference models to show that
ethnic voting has decreased across subsequent Fourth Republic elections, and Chapter 5
provides evidence that it is Ghana’s centralized system of government which is producing these
significant vote changes.
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CHAPTER 3GHANA’S CENTRALIZED SYSTEM OF LOCAL GOVERNMENT & THE POWER OF THE
DISTRICT CHIEF EXECUTIVE
The centralized nature of past regimes in Ghana continues into the Fourth Republic, yet
this chapter details the new mechanisms at the sub-national level which generates political
competition at the local level. It is this political competition which has directly contributed to
the lessening of the effects of neopatrimonial logics and ethnicity on individual vote decisions.
While regimes had appointed their own officials as their local-level representatives in the past,
now centrally-appointed DCEs exist alongside locally-elected Members of Parliament (MPs).
The most powerful political player in local government, the DCE retains a lot of authority
as the head of the District Assembly and thus has a great deal of control over development
within the district. Though the independence of the district assembly is restricted by the
central government, the District Assembly Common Fund allows for some independent planning
of development projects. Further, even when the central government dictates development
initiatives, the district assembly still retains a great deal of control in the placement of those
projects.
After providing an overview of Ghana’s system of local government and detailing the role
of the District Assembly, the third part of the chapter characterizes the relationship between
the DCE and MP, emphasizing the enhanced degree of competition between these two officials
when they are of different political parties. While these officials do not compete in the same
electoral contests, they both strive to increase support for their respective parties. When the
DCE and MP are of the same political party (Friendly pairs), the level of competition between
them is moderate as it is often assumed that the DCE is aiming to become the next MP.
But when the DCE and MP are of different political parties (Unfriendly Pairs), that naturally
competitive relationship is heightened. In the case of Unfriendly Pairs, DCEs are still presumed
to covet the MP position, but now the DCE and MP also compete to increase support for
their respective parties which plays out in the competitive installment of development projects.
As DCEs and MPs compete for the public’s support, citizens get a first-hand opportunity to
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compare both officials’ performance within their own localities. I argue that this mechanism
is causually linked to the depreciation of neopatrimonial political logics and ethnic voting in
Ghana’s Fourth Republic.
3.1 An Overview of Ghana’s System of Local Government
Ghana’s current system of local government is technically a five-tiered system which exists
alongside the network of locally-elected MPs who sit in Parliament. The five-tiered system
at first appears quite complicated. However, apart from the Central Government and the
Metropolitan, Municipal, & District Assemblies (shortened to District Assemblies throughout),
the other three tiers are comprised of councils with largely unspecified roles and which only
operate as consultative bodies providing advice to the Central Government and District
Assemblies.
Debrah (2014) describes Ghana’s local government structures as, “a fused or mixed type
in which institutions extending from the central government and deconcentrated departments
and agencies as well as grassroots institutions are aggregated in a single unit at the local level”
(55). Essentially, the institutions extending from the Central Government are the Regional
Coordinating Councils (RCCs) and the District Assemblies, the deconcentrated departments
and agencies refer to the bureaucratic civil-service backdrop of the District Assemblies, and
the grassroots institutions refer to the sub-district councils and unit committees (see Figure
3-1). Within these five tiers, evidence of the central government’s control is seen in the
Presidential-appointment of Regional Ministers (heads of the RCCs), DCEs (heads of District
Assemblies), 30% of District Assembly Members, 100% of Town/Zonal/Urban, Town, Area
Council Members, and 5 of the 15 members of each village-level Unit Committee. Furthermore,
District Assembly Members, Council Members, and Unit Committee Members are all unpaid
positions, though District Assembly Members do receive marginal sitting fees.
Created by the 1993 Local Government Act 462, the 10 Regional Coordinating Councils
(RCCs) are charged with coordinating and supervising local assemblies within their region.
Each RCC is chaired by a Presidentially-appointed Regional Minister. The duties and functions
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of the Regional Minister are largely unspecified (Ahwoi 2010, 14), though Regional Ministers
often play important informal roles at the level of the District Assemblies.1 The rest of the
council is composed of the Deputy Regional Minister (also Presidentially-appointed), the DCE
and Presiding Member from each District Assembly, and two chiefs from the Regional House of
Chiefs. Additionally, the regional heads of decentralized ministries sit as non-voting members
(Crawford 2004, 12).
Below the Regional level sits the District Assemblies. In response to the 1992 Constitutional
mandate that Parliament devolve power and resources to the local level, the above mentioned
1993 Local Government Act 462 also shifted functions to the District Assemblies (Debrah
2014, 49). The District Assemblies have both a political head, in the DCE, and an apolitical
bureaucratic head, in the Metro./Municipal/District Coordinating Director (DCD). The DCE
is appointed by the President of Ghana, with the Assembly’s approval2 , while the occupant of
1 From my field research it is clear that Regional Ministers often become directly involved inthe Assembly Members’ voting process to approve of nominated DCEs. In particular, RegionalMinisters are often present during the first and especially the second District Assemblyvote, to encourage the approval of the President’s nominee. Regional Ministers can offermoney to secure the support of disaffecting assembly members, they can remind the DistrictAssemblies that it will take months for another nominee to come, or they can coerce appointedassembly members to vote to approve by facilitating the immediate rejection of AssemblyMembers’ appointment to the District Assembly. In cases where a DCE is not yet nominatedor when a nominated DCE does not receive the 2/3 vote of approval necessary to confirm thePresident’s appointment, Regional Ministers, or perhaps their deputies, temporarily assume theresponsibilities of DCEs.
2 The appointment of DCEs requires a vote of approval by 2/3 of Assembly members.An appointed DCE has two chances to receive a 2/3 approval vote. It is not uncommonfor an appointee to require two votes, as assembly members have an interest in holding outfor the first vote in order to receive some payoff or benefit approving the DCE the secondtime. The 2/3 approval vote requirement acts as a check on Presidential appointments,though this check is significantly limited in three ways. First, 30% of Assembly members arethemselves Presidential appointees, and are thus unlikely to vote to reject the DCE. In caseswhere Presidentially-appointed Assembly members are suspected of having voted against theDCE, the Assembly Members appointment can and have been immediately withdrawn andthe member replaced prior to the second vote. Second, when DCE appointees do receivetwo votes of no confidence, it typically takes several months if not years for the President to
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the DCD position has climbed up the bureaucratic ranks to arrive at their position. The DCE
is the head of the Assembly, and also serves as the Chairman of the Executive Committee, the
most powerful and important committee within the Assembly.3 On the other hand, the DCD
is allegiant to both the central government, via the Ministry of Local Government and Rural
Development (MLGRD), and to the DCE.4
Other than the DCE, the District Assemblies are composed of anywhere between 54 to
upwards of 130 members (USAID 2003, 9), 70% of which have been elected by the public
and 30% of which have been appointed by the President. The justification for this mixed
elected/appointed system within the District Assemblies is that such a system creates
nominate a new DCE. This means districts have to operate a considerable amount of timewithout an Assembly head. In the absence of a DCE, for one, the district’s developmentfunds are administered by the Regional Minister, who is not likely to engage in any significantdevelopment planning or begin any major projects. As districts development plans halt andcommunity projects suffer, Assembly Members realize the full effects of rejecting the initialDCE appointee. Finally, a recent development now occurring under President John Mahama’stime in power is that, after the two votes rejection of the Presidential DCE appointee, thecentral government has waited several months only to re-appoint the same individual tothe DCE position. To my knowledge this has occurred on at least one occasion (AkimSwedru). This move has obviously generated some controversy, but the Mahama governmentis defending it as a legal re-interpretation of the Local Government Act. For each of thesereasons, the 2/3 Assembly member vote of approval requirement is not nearly as important acheck on centralized power as it might initially appear.
3 The Member(s) of Parliament within a district are also non-voting members of the DistrictAssembly.
4 A fault commonly identified in analyses of Ghana’s decentralization system is thatbureaucratic departments operating at the district level are not decentralized. Thesedepartments are still appointed by and responsible to their parent ministries in Accra. Thisis despite legislation within the 1992 Constitution (Article 240[2][d]) which stipulates that theDistrict Assemblies were to assume control over the deconcentrated bureaucratic departments.In December 2009, however, the 2003 Local Government Service Act (Act 656), whichimplements the 1992 Constitution’s directive regarding decentralizing bureaucratic departments,became operational. The result was that the management of these civil service employeesoperating at the local level was somewhat shifted from the central government to the localgovernment (Debrah 2014, 61). Yet, these deconcentrated departments are still not under thefull control of the District Assemblies.
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a balance between national and local interests (Debrah 2014, 57-58) and it allows for
the representation of special groups (i.e. traditional authorities), underrepresented groups
(e.g., women5 , Muslims, occupational groups, etc.) and individuals with special skills (e.g.,
engineers, etc.). However, as one interviewee, who had served on the consultative committee
for the 1992 Constitution, complained, “At Constitution time, we were thinking local politics
would be exempt from national politics. That’s why we saved 1/3 [of the] seats for [the]
government to appoint specialists and experts. But appointed members are now just party boys
who contribute poorly to the assembly” (Interview, 12/06/2013). Similarly, the appointment of
30% of the District Assembly members is supposed to be done in consultation with important
social and economic groups, as well as the traditional authorities, within the District Assembly.
Yet, in practice, this directive is often overlooked, causing great consternation for traditional
authorities who worry about the continuous erosion of their power and influence.
Every member of the District Assembly must be a member of at least one legislative
committee within the assembly. The most powerful committee, the Executive Committee,
is not supposed to contain more than 1/3 of the total number of Assembly Members (Ayee
1996, 37). Related, the Presiding Member and Member(s) of Parliament are excluded from the
Executive Committee. This is intended to provide a check on the DCE when they report on
the activity of the executive committee to the District Assembly (Crook 1994, 17). In reality,
however, removing other powerful political players from the Executive Committee only further
bolsters the DCE’s independence and power.
The Presiding Member leads 3 to 4 general assemblies a year, while the rest of the District
Assemblies yearly activities take place through committee structures. Other than the Executive
Committee, the other permanent committees consist of development planning, social services,
5 A 1998 government directive instructs that at least 30% of appointment members shouldbe women. As for elected members, Crawford (2004) writes that women made up only 5% ofelected DA members in 2000.
80
works/technical infrastructure, justice and security, and finance and administration. Still
the Executive Committee reigns supreme. For instance, one regular critique from Assembly
Members was that decisions made on the floor of the District Assembly were often later
changed and implemented by the Executive Committee without consulting the general
assembly. Similarly, other Assembly Members inherently acknowledged the power of the
DCE when they described their lobbying efforts to convince the DCE to implement some
project within their electoral area. Assembly Members known as opposition sympathizers
appeared to be less likely to have development projects bestowed on their electoral areas, as
compared to Assembly Members whose party is in government.
Finally, the distinction between a Metropolis, Municipality, and a District is based on
population size and economic activity (see Table 3-1). In particular, per Act 462 of the
1993 Local Government Act, Metropolitan Districts are to have populations of more than
250,000 residents, Municipal Districts should have between 75,000 and 250,000 residents,
while Districts have less than 75,000 residents (Hoffman and Metzroth 2010, 6-7). These
qualifications are not always met in actuality (see Ahwoi 2010) as more districts are created or
upgraded by the party in power in order to appease local populations.6
Third, below the District Assemblies sit the sub-district structures, namely the sub-Metropolitan
councils, the Town, Zonal, and Urban/Town/Area councils, and Unit Committees, which are
closely attached to the District Assemblies. They carry out functions delegated to them,
have no independent source of power, and largely exist to promote community self-help
development projects and meet on complex local issues, including those dealing with the effects
of urbanization (Crook 1994, 5; Ayee 2008; Debrah 2014). Crawford (2004) writes there were
6 Though the creation of districts is used as a political tool in order to gain votes, it is alsothe case that the creation of new administrative areas can create political chaos. For instance,see Lentz (2006) for insight into the exacerbation of land ownership and citizenship conflict inGhana that occurs whenever administrative and political units are drawn more narrowly.
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roughly 1300 Town, Zonal, and Urban/Town/Area councils as well as 16,000 Unit Committees
in Ghana in 2000 (11).
The Town, Zonal, and Urban/Town/Area council members are not elected. They are
composed of 25-30 representatives from the District Assembly, from the Unit Committees,
and from DCE appointments made on behalf of the President (Crawford 2009). The Unit
Committees, on the other hand, are composed of 10 elected members and 5 DCE-appointees.
Both the Town, Zonal, and Urban/Town/Area Councils and Unit Committees act essentially as
implementing agencies of the District Assemblies. A powerful indicator of the (in)effectiveness
of these sub-district structures, in October 2002 over 10,000 Unit Committee elections were
canceled because of an insufficient number of candidates (USAID 2003, 8).
3.2 District Assembly Authority & Revenue Sources
As we have seen, the District Assembly is the most powerful institution of local
government in Ghana. Similarly, we have seen the extent to which the District Assembly is
dominated by the Executive Committee, headed by the Presidentially-appointed DCE. In such
a highly-centralized system it should come as no surprise that the central government has
devolved little independent authority to the District Assemblies.
However, that little independent power is devolved to the local level should not obscure
the fact that this system of local governance in Ghana’s Fourth Republic has transferred more
power, and has resulted in greater attention to local development, than had previously ever
existed in Ghana’s history (Owusu 2005). Importantly, those living outside of the capital have
greater access to central government resources. In the past, rural residents had to travel all
the way to Accra before they could reach central government officials. Similarly, the creation
of more districts in 2004, 2008, and 2012 mean rural communities become bigger fish in their
political representatives’ constituency pond and thus receive greater concentrated attention
from their political representatives. This section will outline the extent of devolution of
authority and revenue to the District Assemblies, emphasizing the areas in which the DCE can
most effectively implement change in local communities.
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3.2.1 District Assembly Authority
The District Assemblies are generally understood as the principle institution in charge
of development activities at the local level, including coordinating development efforts from
both governmental and non-governmental sources. Crawford (2004) divides District Assembly
responsibilities into three categories: deconcentrated public services, delegated public services,
and devolved public services. Deconcentrated public services refer to those services provided
by the central government which the District Assembly coordinates but does not actively
participate in the provision of that service. These deconcentrated public services include police,
customs and excise, immigration, and the fire service. Delegated public services are those
which the District Assemblies are assigned to by a parent government ministry or agency.
Crawford (2004) gives the example of the provision of public lighting in conjunction with
the Electricity Corporation or the provision of public health in consultation with the Ministry
of Health. Finally, devolved public services refer to those services over which the District
Assembly maintains the most authority and these projects tend to be related to improving
electoral results in favor of the President and DCE’s political party. As Crawford (2009)
describes, “DA activities are concentrated on small-scale construction projects such as rural
health posts, nurses’ and teachers’ accommodation, classroom blocks and boreholes, favoured
for their high visibility to the local electorate” (72-73).
Within the realm of devolved public services, every District Assembly is required to draw
up three-year Medium Term Development Plans, subject to Ministry of Local Government and
Rural Development approval. According to one DCE, the process is as follows: First, the DCE
and the entire bureaucratic/departmental staff move to the grassroots to assess local needs.7
7 This DCE does not go to the Assembly Members to ask for community needs becauseevery Assembly Member represents several communities or villages, only one of which theAssembly Member hails from. As a result, the Assembly Member will naturally want to pushdevelopment projects to his/her home village and will provide a biased assessment of localneeds.
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Once the needs of his District are assessed, the DCE and bureaucratic/departmental staff
prioritize projects and draw up a proposed development plan. This plan is debated within the
Executive Committee and its modified form is presented to the District Assembly. After final
revisions, the plan is sent to the Regional Department where the DCE has to go and defend
it. If the District wants to complete any development project, it must be in the Medium Term
Development Plan. Unplanned development spending is only allowed in times of emergency
(Interview with a DCE, 10/13/2013). In another District Assembly, however, the MCE8
explained that,
“for the Medium Term Development Plan, we call all the assembly members to bring
input. We put together the plan and then have a public hearing. We assemble some
public opinion leaders to air the plan and get their input and approval. We then bring
it back to the assembly for the general house to approve. After the plan is approved,
we have to arrange projects in terms of priority. Sometimes the priority plan has to be
re-arranged. In that case you have to complete an Action Plan and a Supplementary
Action Plan” (Interview with a MCE, 11/11/2013).
In reference to the drawing up of the Medium Term Development Plan, one Assembly
Member, emphasized the degree of DCE discretion over the plans: “Politics comes in. The
MCE at times wants to favor some people as a thank you for voting for the government.
[The Medium Term Development Plan] is at the discretion of the MCE and the Executive
Committee” (Interview, 11/04/2013). Though it is clear that the DCE has a large hand in
the creation of Medium Term Development Plans, other respondents placed greater emphasis
on the ability of the DCE to implement emergency spending outside of the Medium Term
Development Plan. For instance, upon being prompted about this issue a Senior District
8 Note that a MCE is the equivalent of a DCE, only they are in charge of a Metropolis orMunicipality rather than a District.
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Planning Officer retorted that emergency funding is done at the DCE’s discretion, and is
only tracked within the Quarterly Progress Reports (Interview, 10/23/2013). Though some
restraints are in place which restrict DCE power, the system still allows for a great amount
of DCE influence over development planning, and loopholes allow the DCE to circumvent the
Medium Term Development Plans when necessary.
Finally, in addition to control over development initiatives, DCEs also have some
leeway over the awarding of contracts. Per the Local Government Act 1993 and the Public
Procurement Law 2003 (Act 663), publicly-awarded contracts must be publicly announced and
firms can bid for contracts.9 Contracts are typically awarded within the District Assembly.
Two crucial stipulations to this rule increase the DCE’s power in this process. First, the
DCE can create service contracts on their own, as long as they stay under 50,000 GHc.10
Second, contracts between 50,000 and 200,000 GHc must be reviewed by the District Tender
Board, of which the DCE is the chairman. As the chairman of both the Executive Committee
and District Assembly which award contracts and the District Tender Board which reviews
contracts, the DCE has a good deal of influence in this process. Both of these stipulations offer
the DCEs significant opportunities to influence the system of awarding contracts.
Through this system of local government, an extensive range of public services is provided
at the local level. At each level of public services (deconcentrated, delegated, and devolved),
the central government maintains significant, if not almost complete, authority. Accountability
9 Another category of contract awards is single-source or sole-source procurement. Theseawards apply when goods or services are only available from one particular supplier. In thesecases, the contract does not have to be advertised publicly and the district can hire thesupplier outright. In order for this to happen, the DCE must first seek approval from theNational Procurement Authority, empowered by the Public Procurement Act 663. The NationalProcurement Authority will do a background check to ensure this is the only provider beforethe contract can be awarded.
10 Since 2007, the value of the Ghana Cedi vis-a-vis the U.S. Dollar has continuouslydepreciated. While the exchange rate was roughly 1 GHc : 1 USD in 2008, the rate has variedbetween 3.2-3.8 GHc : 1 USD in 2015.
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thus flows upward to the central government, instead of downward to the public. As the
centrally-appointed head of the District Assembly, the DCE obviously acquires a great deal of
individual authority from this system and is, “undoubtedly the most powerful person in the
DA system” (Crawford 2009, 62). The authority of the DCEs is constrained, however, by a
structure which limits the amount of unrestricted transfers from the central government and in
a context where local revenue raising ventures (i.e. taxes) are insufficient for district spending
needs.
3.2.2 District Assembly Revenue
The District Assemblies’ three sources of revenue include revenue ceded from the central
government (typically with strings attached), the District Assembly Common Fund (DACF),
and through the District Assemblies own revenue-raising powers (primarily through the issuance
of business licenses and local taxation).
The revenue ceded from the central government to the District Assemblies is tightly
controlled and makes up about 85% of District Assembly budgets (Hoffman and Metzroth
2010, 7). It includes money from international donor grants, transfers from different funds
including the Highly Indebted Poor Country (HIPC) initiative, and ministerial funds to cover
the salaries of bureaucrats working within the deconcentrated bureaucratic departments at the
District Assembly.
All of Ghana’s revenues and international sources of funding are housed in the Consolidated
Fund. A portion of the Consolidated Fund is diverted to Ghana’s Development Budget,
which is the annual installment of the Public Investment Programme (PIP). The National
Development Planning Commission (NDPC), which is tasked with creating five-year
development plans, guides the generation of the three-year PIP. The NDPC, Ministry of
Finance, and Ministry of Local Government and Rural Development (MLGRD) all coordinate
national and district-level development projects. Some of the more prominent development
funds disbursed to the district-level include the District Wide Assistance Project (DWAP), the
District Development Facility (DDF), the GETFUND, and the Road Fund.
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The District Wide Assistance Project (DWAP) was funded from 2004 to 2012 by the
Canadian International Development Agency (CIDA). It supported districts in the northern
three regions of Ghana in the creation of their development plans and served as the template
for the later District Development Facility (DDF). The DDF grants districts an additional
source of revenue according to their performance on the Functional and Organisation
Assessment Tool (FOAT). The FOAT is a general performance tool to determine the
effectiveness of the District Assembly in terms of administrative, organizational and financial
indicators. The DDF is joint-funded by the AFD (France), CIDA, DANIDA (Denmark), KfW
(Germany), and the Government of Ghana. Donors impose restrictions on the ways in which
the District Assemblies can spend DDF funds. International-donor restrictions mandate that
DDF funds cannot be used for consumables (i.e. office materials, the construction of office
buildings, the purchase of vehicles), but can be used for infrastructure projects, such as the
building of schools and hospitals, and for internal capacity building (i.e. training programs
for the bureaucratic staffs or the assembly members). Additionally, these infrastructure and
capacity building projects still have to get approved by the central government via the Medium
Term Development Plan.
Because the DWAP and the DDF are donor-sponsored programs, there are no delays
in the transfer of funds, in important contrast to domestic funding sources, and the District
Assemblies plan their most important projects with these funds. In one conversation which
took place with both an Assembly Member and a District Planning Officer, the Assembly
Member wanted ‘covereds’ or simple bridges to help with flooding in his electoral area. The
District Planning Officer replied that the project has already been planned for, prompting the
Assembly Member to react, “But we need DDF money to pay for it because DDF money is
cash! Government of Ghana money? When will that come?” (Interview 10/23/2013). Clearly
the differences in the sources of development funding are significant enough to even effect the
way Assembly Members lobby for development in their electoral areas.
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Other prominent development funds are under strict central government control. The
Ghana Education Trust Fund (GETFund), established in 2000 by the Ghana Education Trust
Fund Act 581, disburses money to the districts for targeting projects including the construction
of classroom blocks, sending classroom materials to schools, and the provision of buses for
secondary schools. The District Assembly can appeal to the GETFund to sponsor a particular
project, but this project must be approved by the GETFund agency, whose head administrator
is appointed by the President. Similarly, the Road Fund disburses resources to ensure the
management and upkeep of Ghana’s roads networks. It is administered by the Road Fund
Management Board, whose chairman is the Presidentially-appointed Minister of Roads and
Highways.
Apart from these development funds, the revenue which is intended to consistently
support the District Assemblies is the District Assembly Common Fund (DACF). Established
by Act 455 in 1993, the DACF is a block grant administered to the District Assemblies
based on a guarded Revenue Sharing Formula created by Parliament. Previously 5% of total
national revenues were transferred to the DACF, but this stipulation was recently increased
to 7.5% by the 2008 Local Government Instrument (LI) 1961 (Hoffman and Metzroth 2010,
9). DACF funds account for 40% of District Assembly revenue (Debrah 2014) and are
administered quarterly by the Office of the Administrator of the District Assemblies Common
Fund, though these transfers can be significantly delayed as much as a year (King et al. 2003).
The DACF funds are technically discretionary, but in practice DACF transfers often come
with conditionality constraints (ibid, 64). Estimates of the percentage of DACF funding fully
discretional to District Assemblies ranges from 15% to 25% (Crawford 2004; Hoffman and
Metzroth 2010).
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Ten percent of the DACF budget goes to the ‘Reserve Fund’.11 The remaining
65%-75% of funds are determined by Ministry of Local Government and Rural Development
(MLGRD), NDPC, and Ministry of Finance guidelines. Still, even when DACF funds come
with conditionality specifications attached, the District Assembly typically gets to decide which
communities or individuals in particular will benefit from DACF spending. If funds are provided
to construct 10 primary schools, for instance, the District Assembly typically retains the
authority to decide where these schools will be built. This is the arena in which the authority of
the DCE comes into play, and local politics greatly determine where development projects are
placed.
Finally, the extent to which District Assemblies can raise local revenue on their own is
stipulated by the 64 revenue authorities devolved through the Sixth Schedule of the 1993
Local Government Act 462, though only some of the rates are determined by the District
Assemblies (Debrah 2014, 63). While increasing the revenue-raising powers of the District
Assemblies technically increases its authority, the low economic base of most districts means
little revenue is actually generated (Hoffman and Metzroth 2010) and the imposition of taxes
from deprived areas has at times seriously damaged the relationship between the district and
local communities (Ayee 1996, 42).
3.3 The Relationship Between MPs and DCEs
In low-development/rural contexts, prominent government positions are hard to come
by. In Ghana, the DCE and MP are the most prominent politicians in any locality, though
the MP spot is more coveted. Many DCEs aim to use their position as a stepping stone to
becoming the next MP. MPs are aware of this aim and the relationship between DCEs and
11 Within the Reserve Fund, 50% of this fund (or 5% of the total DACF) is allocated to theMPs and is referred to as the MP’s Common Fund. The RCCs are allocated 25% of this fund.Finally, the remaining 25% is allocated for activities on sanitation, maintenance of rural/feederroads, and for rural health, housing, telecommunication, and emergencies (King et al. 2003,12).
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MPs is naturally competitive. Still, when DCEs and MPs are of the same political party, they
have to work together to appease party executives and to present a united political front to
the public. When DCEs and MPs are of different political parties, they may have a working
relationship but DCEs explicitly try to implement development projects to attract voters away
from the MP’s party. The MPs have to respond with development initiatives of their own,
which creates a development race in full-view of the voters. As voters have the opportunity to
compare the effectiveness of these two politicians, they bring that information with them to the
voting booth. I argue that the competition between the MPs and DCEs drives vote volatility
and a breakdown of ethnic voting in Ghana.
Alongside Ghana’s system of local government exists Members of Parliament (MPs)
popularly elected per constituency. As the constituency-level representative in Ghana’s
House of Parliament, the MPs’ primary role is to participate in the legislative process. Yet,
service to the nation as a good legislator is not enough to ensure re-election. In addition to
frequent visits back to the constituency from their residence in Accra, Ghana’s MPs must
implement development projects in their communities if they wish to remain competitive in
the next election. MPs face several difficulties in the never-ending pursuit of development
initiatives. First, though the MP is a national-level politician who is better positioned to lobby
Accra-based ministries for development, Ghanaian voters want to see their representative and
are very sensitive about feeling forgotten while their MP enjoys life in Accra. This requires
MPs to travel back to their constituencies frequently, though a busy schedule and Ghana’s
poor roads network makes visits back home quite arduous. Secondly, though constituents
expect development projects, MPs are allocated a comparatively smaller portion of the District
Assemblies Common Fund (DACF), with which to pay for these projects, and which they are
quick to complain about.12
12 Several calls for the creation of an independent Member of Parliament ConstituencyDevelopment Fund (CDF) have been raised during Ghana’s Fourth Republic. Former President
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When lobbying the ministries, MPs of the opposition party are at a disadvantage. This is
because Presidential-appointed heads of the ministries tend to not want to prop-up opposition
MPs’ re-election chances. In addition to the ministries, MPs can also lobby international NGOs
for development. But there is no guarantee that such an opportunity will be found. Given
the limited funding opportunities, in many cases MPs spend large portions of their personal
wealth within their constituencies. Finally, MPs face a particularly formidable challenger for
local popularity in the DCE. In contrast to the Accra-based MPs with little automatic access to
development funding, the DCEs reside within the community and have significant control over
District Assembly development planning, the awarding of contracts13 , and the placement of
development projects.
As the two most prominent officials in a given area, the relationship between MPs and
DCEs is often competitive (Debrah 2014, 51; Ahwoi 2010). The position of DCE is less
prestigious and the position faces two term limits. As such, MPs typically perceive DCEs as
gearing up to challenge the MP for the Parliamentary seat in a future election (Ayee 1999, 60).
When the MP and DCE are of the same political party, this level of competition is typically
moderate (ibid, 58). After all, both actors have an interest in improving the party’s support
at the local level. For instance, I know of one case where the DCE had previously served as
the MP’s campaign manager. When asked about development in the district, the DCE replied
that (s)he does not complete any project without first getting the MP’s approval (Interview,
11/15/2013). In another example, another district’s DCE and MP were of the same political
party, but the MP was also preoccupied as a Minister in Accra. In this case, the MP gave the
Atta Mills gave this suggestion the most serious thought when he promised that such a CDFwould be put in place by 2009. As of 2015, however, no MP CDF exists in Ghana.
13 Though DCEs serve as the Chairman of the District Tender Board, one of the MPs withinthe district also serves on that board. When the DCE and MP are of different political parties,this likely serves as a check on the DCEs influence, assuming that the MP is fully aware of, andpresent within, District Tender Board meetings.
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DCE power of attorney to administer the MP’s Common Fund on his/her behalf (Interview
11/17/2013).
But when the MP and DCE are of different political parties, the relationship between these
two actors can be quite competitive, even fierce. As an appointed District Assembly Member
described, “Any project that needs financial support, the DCE and MP work together [if]
they are from the same party. If the DCE is of a party other than the MP, they can’t always
work together; they will try to thwart each other’s projects” (Interview, 10/23/2013). Almost
ensuring a degree of animosity, the central government sometimes appoints the unsuccessful
Parliamentarian candidate of the last election as DCE, causing predictable problems within
MP-DCE working relationships. Further, the DCE controls the disbursement of the MP’s
portion of the Common Fund, and every MP has heard stories of DCEs who have refused to
disburse money to their corresponding MP(s). A common strategy used by DCEs to ‘sabotage’
MPs is to implement development projects with MP support while forgetting to notify the MP
of the project’s opening ceremony: “ , as DCE, would not invite the MP to inaugurate
projects so (s)he became popular” (Interview with constituency-level political party executives,
11/15/2013). If the MP is not present at the ceremony, the public will assume the MP is not
involved.
Particularly when the MP and DCE are of different political parties, then, they compete
against one another for constituent support. If the MP builds a school in one community, for
instance, the DCE feels tough pressure to respond with a corresponding development project in
another.
3.4 Discussion
The chapter has gone into detail about the organization of Ghana’s centralized system
of local government and made the argument that the DCE is the most powerful political
player at the sub-national level. As the head of the District Assembly and the Executive
Committee, the DCE has a large amount of power in determining local development initiatives
and the placement of DACF funding projects. The combination of this power along with the
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DCE’s full-time residence in the district makes him/her a formidable opponent against the
incumbent MP. When the DCE and MP are of different political parties, the competition can
become fierce. The artificial introduction of political competition in this way has opened up
the opportunity for voters to compare prominent local politicians against one another, thus
encouraging retrospective/prospective voting bases. In the following chapter I use EI models to
demonstrate a decline in ethnic voting in Ghana since 2004 which I attribute to the heightened
levels of local competition in Ghana’s Fourth Republic.
Figure 3-1. Overview of the system of local government in Ghana
Source: Crawford 2009, 61.
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Table 3-1. District types (1996-2012)
Year Metropolitan Municipal District N1996 3 4 103 1102000 3 4 103 1102004 3 4 131 1382008 6 39 125 1702012 6 49 161 216
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CHAPTER 4ECOLOGICAL INFERENCE
The central argument of this dissertation is that Ghana’s centralized system of local
government contributes to a lessening of neopatrimonialism and ethnic voting, and thus
contributing to deepened democratic governance. The mechanism whereby democracy is
deepened is through the insertion of the president’s party member into districts as DCEs,
granting them charge of district-level development funding, and generating a competitive
political environment between the DCE and MP(s). This level of competition allows voters
the chance to compare the dominant party in the area against the president’s appointee, thus
opening up opportunities for evaluative voting outside of neopatrimonial or ethnic voting cues.
I argue that volatility in Ghana’s levels of ethnic voting, as presented in this chapter, is unusual
for a new democracy and is fueled by Ghana’s centralized system of local government.
In order to identify ethnic voting patterns, I use Ecological Inference (EI) models to
estimate votes by ethno-linguistic and tribal groups in Ghana’s 1996 through 2012 Presidential
and Parliamentary elections. I find that since 2004, core party supporters and particularly
peripheral party supporters from both sides are increasingly willing to vote against their ethnic
group’s voting tradition.1
When comparing the NDC and NPP’s core support groups (the Ewes for the NDC and
the Asantes and Akyems for the NPP), against peripheral party supporters (i.e. NDC or NPP
- leaning tribes)2 , the core groups are more stable in their voting traditions. Importantly,
1 See Table 4-1 for a list of Ghana’s Ethno-Linguistic Groups and Tribes, the tribes includedin the EI analysis in this chapter, and the overall political leanings of the tribe-encompassingethno-linguistic groups.
2 Peripheral party supporters is used to refer to tribes which clearly have a preference forone party or the other, but are outside either party’s core support groups. The NDC-leaningtribes are the Bimoba, Sefwi (an Akan tribe), Dangme, Ga, Dagarte, Dagomba, Nankansi,and Kusasi. The NPP-leaning tribes are all Akan tribes and consist of the Akuapem, Boron,Denkyira/Twifo, Ahanta, Asen, and Kwahu.
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however, both the Ewes and Asantes do increase their support for the opposing party in recent
Presidential and Parliamentary races, and particularly the 2012 Parliamentary election. On
the other hand, Akyem support of the NPP has increased relative to the NDC, in both the
Presidential and Parliamentary races since 2004. This observation corresponds to the fact that
since 2008, the NPP Presidential Candidate Nana Akufo Addo is a member of the Akyem
tribe.
Of the peripheral party supporters, the vote margin of difference separating the NDC
and NPP has narrowed since 2004 for 2 out 8 NDC-leaning groups in both Presidential and
Parliamentary races, 4 out of 6 NPP-leaning groups in Presidential races, and 5 out of 6
NPP-leaning groups in Parliamentary races. The evidence suggests that a greater number of
NPP-leaning groups are more willing to vote for the opposition as compared to NDC-leaning
groups. Similarly, there is some support that ethnic voting is more volatile in Parliamentary
races as compared to Presidential races.
Finally, we can pinpoint the groups whose changes in votes critically affected changes in
power at the Presidential level. The 2000 and 2000 runoff elections saw increased support for
the NPP across NPP and NDC-leaning tribes, but I maintain that this result has more to do
with the end of Rawlings’ 19-year long rule and the public’s interest in a peaceful turnover
of power. A popular President, Kufuor won re-election in 2004, but no longer with as broad
a coalition of voters as NDC-leaning groups, and even some NPP-leaning groups, began to
withdraw their prior support.
In the second peaceful alternation of power in 2008, Atta Mills (NDC) won after
depreciated support for the NPP from NPP-leaning groups and increased support for the NDC
among NDC-leaning groups forced a runoff election. In the runoff election, 5 of 8 NDC-leaning
groups and 2 of 6 NPP-leaning groups again increased their support for the NDC in the runoff
as compared to the 2008 regular election. Lastly, in the 2012 race, Mahama (NDC) won the
election helped in part by the 125% estimated increase in NDC votes, as compared to the
28.9% increase in NPP votes, by Asante voters from 2008 to 2012. Other than the Asantes,
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the Nankansi (NDC-leaning) were the only other group to increase their votes for the NDC in
2012 as compared to the 2008 general election.
That some groups important for the political parties are increasingly turning out for the
opposing party is an important observation from the Ghanaian political landscape. In the next
chapter I provide evidence that these changes in vote volatility are due to increased local levels
of competition as the result of Ghana’s centralized system of government.
4.1 The Application of Ecological Inference Tools to Ghana
Establishing a link between ethnic identity and vote outcomes is a problem for researchers
when the data is in ecological form. At the most basic level, researchers cannot easily use
vote outcomes to determine levels of ethnic voting because voter identities are secret. It is a
potential fallacy to assume that citizens turn out to vote in the same proportions that ethnic
groups make up the local population. Some ethnic groups might be more politically motivated
and thus more likely to vote as compared to other ethnic groups.
Without ecological inference tools, researchers have had to rely on survey data, which
depend on truthful and accurate memories of past voting behavior, and exit polls to draw links
between individual identities and vote choices. And while these tools may establish general
links between ethnic identities and vote behavior, national-level analyses would rarely collect
enough data from enough respondents to make any assertions about voting behavior from
any ethnic or tribal groups other than the largest groups in the country. By incorporating
deterministic information within a three-stage hierarchical Bayesian model, the Ecological
Inference models presented in this chapter provide unbiased estimates, with reported confidence
intervals, of vote decisions by ethno-linguistic and tribal group members in Ghana.
This is not the first time scholars have applied EI models to African Politics. Most
prominently, Ferree’s (2002) dissertation on racial voting in South Africa incorporated King’s
(1997) R x C ecological inference approach. At this stage, King’s approach was still based
on dichotomous data, but R x C estimates could be produced in iterations, or to different
subsets of the data at a time (Ferree 2004, 144). Later, Horowitz (2012), a student of Ferree,
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incorporated Ecological Inference models to estimate ethnic bloc voting in Kenya into his
dissertation. In that work Horowtiz used the frequentist approach to multinomial-dirichlet
methods of ecological inference developed from Rosen et al. (2001) for use in the ei.RxC
package in R by Wittenberg et al. (2007) (Horowitz 2012, 59).
The analysis presented in this dissertation relies on the latest improvements in the EI
model series, found within ei.MD.bayes, a multinomial-dirichlet model using a hierarchical
Bayesian model fit. In comparison to past work, I use a more advanced EI model to predict
both ethno-linguistic groups and tribal groups vote patterns in Ghana. The analysis makes
several important contributions to vote analysis in Ghana. First, the EI models compare
ethno-linguistic groups against tribal groups voting patterns3 for Presidential and Parliamentary
races over time. To my knowledge this is the first ever comprehensive analysis of voting on the
basis of tribal group delineation in Ghana. Second, by looking at ethnic vote patterns over
time I can pinpoint not only core party supporters but also NDC- and NPP-leaning groups.
Other than the Asantes and Akyems, for instance, a host of other tribes belong within the
Akan ethno-linguistic group, yet their voting behavior has not been systematically analyzed.
As this analysis will show, it is a mistake to assume all Akans vote alike because they all speak
derivatives of Twi. Several Akan tribes (e.g., the Sefwi, Chokosi, Fante, Builsa, Wasa, Nzema)
have competitive voting traditions and/or at times voted strongly for the NDC. Challenging
researchers’ automatic analysis of political behavior at the ethno-linguistic group level, as
opposed to the tribal group level, is an intentional objective of this work.
3 Ethnicity is generally defined by groups’ shared language, culture, customs, and so on.Linguistic differences have become the paramount criteria distinguishing one ethnic group fromanother. Tribal groups are found within ethno-linguistic groups and they are distinguished byvariations in their language, culture, history, and/or customs. Ghana’s Census distinguishesbetween 9 ethno-linguistic group categories, and 63 tribal group categories. According to the2010 Census, “The classification of ethnic groups in Ghana is that officially provided by theBureau of Ghana Languages and has been in use since the 1960 census” (Ghana 2010 Census,xi).
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I use Ecological Inference models to analyze ethno-linguistic and tribal voting trends for
all Presidential and Parliamentary elections in Ghana’s Fourth Republic, save the founding
1992 Presidential and boycotted Parliamentary races.4 However, I do not expect ethnic voting
trends in the 1996 and 2000 elections, including the 2000 runoff, to follow the same ethnic
voting patterns in the 2004-2012 elections. This distinction is warranted for several reasons.
First, both the 1996 and 2000 elections were held while Rawlings’ NDC government was
still in power. At the very least, Rawlings’ government utilized incumbent advantages, including
lifting the ban on party politics only a few months prior, in securing the 1992 election (Jeffries
and Thomas 1993, 339; Nugent 1998, 8; Gyimah-Boadi 2001a; 2001b).5 In the 1996 elections,
still capitalizing on incumbent advantages, appealing to it’s everyday citizen/rural voter base,
and playing up fears about the Ashanti-hegemony background of the NPP, the NDC won a
majority of the votes in every region except for the Ashanti Region.6 The 1992 and 1996
Presidential elections were far from competitive, as compared to the future Fourth Republic
elections.
Next, the 2000 elections were the first contests in which Rawlings was not running
and in which the NPP had a legitimate chance of taking the Presidency. Many forces came
4 As mentioned in chapter two, the NPP held that electoral irregularities de-legitimized the1992 Presidential results, which declared J.J. Rawlings the winner, and thus boycotted thesubsequent Parliamentary elections. (The 1992 Presidential and Parliamentary elections wereheld almost two months apart. In every election thereafter, the Presidential and Parliamentarycontests were held on the same day.) The contested nature of the presidential contest andthe NPP’s boycott of the parliamentary contests led me to exclude these elections from theanalysis.
5 The NPP refers to the 1992 Presidential Election as ‘The Stolen Verdict’. Some scholarsagree with this interpretation (Oquaye 1995), while others suggest that the NPP’s claim ofmassive vote-rigging was greatly overstated (Jeffries and Thomas 1993, 349; Nugent 1998,15-16.
6 As Nugent (1998) writes, “If Kufuor [NPP] had managed to sweep the Akan board in themanner of Busia in 1969, he would almost certainly have made it to a second round of voting.As it happened, he fell well short of the target” (19).
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together to push the NPP through to win the 2000 Presidential election7 and today many
NDC members acknowledge that the NPP victory in 2000 was necessary to keep opposition
supporters satisfied with the regime and to prove that Ghana’s government was indeed
democratic. In many ways, the 2000 elections were the Fourth Republic’s founding elections.8
For instance, though the Presidential race went to a runoff because no candidate received
more than 50% of the vote, John A. Kufuor (NPP), helped by the six opposition parties who
threw their support behind the NPP in the runoff election (Gyimah-Boadi 2001a, 108) easily
won with 56.9% to Atta Mills’ (NDC) 43.1%. The politics surrounding the 2000 elections
were paramount to Ghana’s overall democratic transition and its step away from the prior
authoritarian regime.
Third, the overall argument made in this dissertation is that the centralized nature of
Ghana’s government counter-intuitively offers voters a competitive political environment
and incentivizes voters’ reliance on evaluative voting rather than historical ethnic-based
voting. Though this centralized system of local government was in place at the beginning
of the Fourth Republic, the mechanism that introduced competition at the local level was
absent during Rawlings’ presidency. As Chapter 5 will explain in greater detail, I argue that
the appointment of local-level DCEs by the President leads to more competitive political
environments in opposition strongholds. However, the appointment of NDC DCEs by President
Rawlings after the 1992 and 1996 elections were unlikely to be interpreted as anything but
7 For instance, “All five minor opposition parties came together to support and campaign forthe NPP and its presidential candidate in the runoff. For once, the left-of-center Nkrumahistparties and the right-of-center NPP, which have been feuding since the early 1950s, seemed tohave found common ground” (Gyimah-Boadi 2001a, 113).
8 Gyimah-Boadi (2001a) underscores the importance of the 2000 elections: “Even the 1996elections, however, failed to remove fundamental doubts about the prospects for democraticconsolidation. Ghana appeared to be developing a ‘party-state’ political system in which theNDC was permanently entrenched in power; the opposition parties, civil society, independentmedia, and other key democratic institutions rooted in the 1992 Constitution were constrainedby severe handicaps” (104).
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the continuation of authoritarian-era interference in local politics. Even if Rawlings’ DCEs
were effective local development agents, they would likely be resented by local populations,
particularly in opposition strongholds, just as the District Secretaries had been resented under
the authoritarian PNDC regime. It is only after the 2000 NPP presidential candidate John
Kufuor won the Presidency in the 2000 runoff elections that I would expect the presidential
appointment of DCEs to genuinely contribute to a competitive local political environment.
The Ecological Inference models presented in this chapter estimate votes by ethnic group
members, compare and contrast ethno-linguistic and tribal groups’ voting behavior, and show
how the relationship between ethnicity and vote choice has diminished over time. Chapters 5,
6, 7 and 8 help us understand these changes in voting behavior first by showing that they occur
in relation to changes in levels of local competition and second by using survey analysis to test
for programmatic versus ethnic inputs in vote decisions.
4.2 Ethnic Voting in Ghana
As introduced in Chapter 2, ethnic divides have dominated Ghana’s political scene since
independence. Yet when the secret vote prevents us from knowing the ethnic backgrounds
of voters, we cannot easily know the relationship between ethnicity and votes based on
correlational analyses alone. In the case of Ghana, NPP and NDC voting blocs in the
Ashanti and Volta Regions, respectively dominated by the Asantes and Ewes (Fridy 2007a),
corroborates contextual information we know about the existence of an Asante-Ewe rivalry long
in the making. But we cannot know how many Asantes and Ewes, in comparison to ethnic
minorities, turned out to vote in those block regions and, further, this tells us nothing about
how ethnic biases impact other Ghanaians’ votes.
A related concern is that ethno-linguistic groups may not be the ethnic identities most
relevant for political analysis in Ghana. Certainly ethnic entrepreneurs would prefer to lead
broader unified ethnic groups when vying for political power. But the historical rivalries and
dialect differences within ethno-linguistic groups in Ghana make the study of tribal voting
similarly worthy of analysis.
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A growing literature tests for politically relevant identity group boundaries or configurations
(Laitin and Posner 2001; Fearon 2003; Posner 2004; Desmet, Ortuno-Ortin, and Weber 2009;
Wimmer, Cederman, and Min 2009; Baldwin and Huber 2010). But these studies pair linguistic
data with new information, rather than reconsider the relevance of ethno-linguistic boundaries
for social conflict within their cases. That the political relevance of other ethnic boundaries,
such as cultural differences, is not explored disregards valuable contextual information. Rather
than assume that linguistic differences are the causal mechanism behind identity-driven political
behavior, it might be that linguistic group boundaries do not define the set of politically
relevant groups in a given area. Politically relevant identities refer to those identities which are
made salient at the group level and can be mobilized to achieve some political aim. Different
identities can be made salient within the same communities at different times, and for different
issues. In some cases, ethno-linguistic groups are the most politically relevant identity groups.
In other cases, however, other identity categories are the most politically relevant groups, such
as caste in India (Banerjee, Iyer and Somanathan 2005). Political institutions go a long way in
determining the politically relevant groups, particularly when political goods are at stake during
elections (Posner 2005).9
9 By way of example, a recent article published on Ghana in the American Political ScienceReview uses advanced geocoded polling station-level election results to test for the votingbehaviors of rural voters. The sample is split between rural voters whose geographical area isdominated by members of another ethnic group as compared to rural voters residing in areaswhere their group makes up a larger portion of the population (Ichino and Nathan 2013).Relying on election and census data, these authors find “that the vote share of a politicalparty identified with a particular ethnic group is significantly greater for polling stations inareas where that ethnic group makes up a larger share of the surrounding population” (ibid,1). Second, combining census data with Afrobarometer data, they, “show that rural surveyrespondents are significantly more likely to support an ethnically affiliated political partywhen living in an area where the ethnic group affiliated with that party makes up a largerproportion of the population, even when this means voting against the party affiliated withthe respondent’s own ethnic group” (ibid, 2). Even though the analysis uses Presidentialelection results, by using ethno-linguistic groups Ichino and Nathan do not account for thedivisions within the ethno-linguistic groups, which are particularly prominent for the Akans.As this analysis will show, the major Akan group which dominates the Brong-Ahafo Region,
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4.3 The Model
At the most basic level, the ecological inference problem is one concerned with the
reconstruction of individual behavior from aggregate data. When King developed his EI
program (1997), he was interested in solving the distribution of white and black voters (2
categories) in U.S. elections. King’s work combined 2 previous approaches to ecological
inference problems: a deterministic methods of bounds approach and a two-stage hierarchical
model to fit the data and then estimate the quantities of interest. The two-stage hierarchical
stage modeled the racial turnout distribution as if they were generated by a truncated bivariate
normal distribution, conditional on the proportion of the voting-age population who belonged
to the white and black racial categories.
Within R, there have been a number of extensions to this EI program, primarily because of
the original program’s limitation to two demographic categories (i.e. black and white voters).
The first model, ei.reg, uses Goodman’s 1953 ecological regression, which uses regressions
based on row and column marginals to estimate population proportions, and is provided in the
eiPack module. Second, ei.reg.bayes uses the same principles in Goodman’s models, but
implements Bayesian normal regression. The unfortunate part about Goodman’s approaches
in general, however, is that they usually provide at least some out of bounds point estimates
(i.e. turnout estimates under 0% or over 100%) (Rosen et al. 2001, 135; Lau, Moore, and
Kellermann 2007). Another extension, ei.RxC, provides a frequentist approach using the
Hierarchical Multinomial-Dirichlet Ecological Inference Model for RxC tables, as discussed
in Rosen et al. (2001). Finally, the models used in this paper, also presented in Rosen et al.
(2001), is ei.MD.bayes, a Multinomial-Dirichlet model which uses a three-stage hierarchical
Bayesian model fit using a Metropolis-within-Gibbs algorithm.
the Borons, are themselves not fully incorporated within the New Patriotic Party (NPP) (seeFigures 4-15 and 4-18). My research has shown that local political traditions, uncontrolledfor in their analysis, are highly determinative of ethnic voting patterns and turnout rates bydominant and minority groups in a given locality.
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First, prior to the implementation of ei.MD.bayes, I present Method of Bounds output
made available by the eiPack. King’s (1997) implementation of the method of bounds
combines information from two deterministic processes, capitalizing on the amount of
deterministic information available in order to provide more specific parameter bounds with
greater precision (see Duncan and Davis 1953 for reference). For determining the upper bound
of the number of, say, Asante voters who turned out to vote in a heterogeneous district, the
following algebraic expressions are used. First, the proportion of voting-age Asantes who voted
(βbi ) is equal to the number of Asantes who turned out to vote (N bT
i ) divided by the number
of Asantes of voting age (N bi ). The number of Asantes of voting age is known, but the number
of Asantes turning out to vote is unknown. Further, the number of Asantes turning out to vote
cannot be larger than the total number of people (Asantes + everyone else) who turned out
to vote. Similarly the number of Asantes turning out to vote cannot be larger than the total
number of Asantes of voting age.
Thus, the maximum number of Asantes turning out to vote (max(N bTi )) is equal to
min(NTi , N
bi ) where min(a, b) equals a if a is less than or equal to b and b otherwise. King
divides the equation by N bi (the number of Asantes of voting age) to arrive at the upper bound
of βbi (the proporition of voting-age Asantes who voted).
max(βbi ) = max
(N bT
i
N bi
)= min
(NT
i
N bi
,N b
i
N bi
)(4–1)
= min
(Ti
Xi, 1
)(4–2)
A similar, though slightly different procedure, is used to find the minimum value of the
proportion of Asantes who voted and also the proportions of Asantes who voted for a particular
political party or candidate (see King 1997, Appendix B).
Relying heavily on Rosen et al. (2001) here, the first stage of the hierarchy assumes that
the column totals representing the number of voting-age people who turnout to vote for each
political party follows a multinomial distribution, under the constraint that the sum of all the
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voters and non-voters = 1. The contribution of a polling station i to the likelihood is:
θT ′1i
1i × ...× θT ′C−1,i
C−1,i × (1−∑C−1
c=1θci)
Ni−∑C−1
c=1 T ′ci . (4–3)
The second stage of the hierarchical model assumes that the vectors containing the vote
estimates by ethnic group follow independent Dirichlet distributions, which means that the
proportion of members of, say, the Asante tribe who showed up to vote is not related to the
number of Asantes in any given district or precinct. This is a problem if, for instance, Asantes
in highly homogenous Asante districts were more likely to turn out to vote than Asantes in
heterogeneous districts or in districts where they make up the minority.10 The second-stage
means of the βirc’s are
drexp(γrc + δrcZi)
dr
(1 +
∑C−1j=1 exp(γrj + δrjZi)
) =exp(γrc + δrcZi)
1 +∑C−1
j=1 exp(γrj + δrjZi), (4–4)
for i = 1, ..., p, r = 1, ..., R and c = 1, ..., C − 1, which implies the following log odds
logE(βi
rc)
E(βirC)
= γrc + δrcZi. (4–5)
In these equations, the log odds depend linearly on the covariate Zi11 .
At the third stage, the regression parameters (the γrc’s and the δrc’s) are assumed to
be a priori independent, putting a flat prior on these regression parameters. This assumption
means that voting turnout rates are independent of each other, after taking into account the
proportion of Asantes who turn out to vote. In other words, there should not be geographical
or spatial or other patterns in voter turnout. Finally, the parameters dr, r = 1, ..., R, are
assumed to follow exponential distributions with means 1/λ.
10 This could be a problem given theories suggesting that ethnicity is ‘realized’ in urban areas,where individuals share city spaces with members of other groups. I address this concern byrunning the EI models with urban covariates, or the proportion of citizens residing in urbanareas within each given district (the unit of analysis).
11 I use a covariate for urban districts in my analysis.
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Markov chain Monte Carlo (MCMC) models rely on samples taken from the posterior
distribution, where estimation events depend on the current state of the process and the
probability of changing to another state (Young 2005). As Rosen et al. (2001) write, “By
Bayes’ theorem, the posterior distribution is proportional to the likelihood times the prior”
(138). In order to estimate the marginals of the posterior distribution, Rosen et al. (2001) rely
on the Metropolis-within-Gibbs sampler, which uses iterations to determine if a value sampled
from the univariate normal distribution is representative of the stationary distribution in which
we are interested.
4.4 Data
To construct the dataset used in the Methods of Bounds and Ecological Inference
analyses, I paired 2010 district-level census data with constituency-level 1996-2012 election
results. Rather than apply ethnic population information at the district level to each
constituency contained within the district, I instead maintained districts as the level of
analysis and, where necessary, aggregated constituency-level electoral information up to the
district-level.
Next, the EI programs require that the total ethnic population in each district is equal to
the total population of voters and non-voters. Since the 2010 ethnic data needed to match
with 1996 through 2012 electoral data, I calculated ethnic group population proportions per
district based on the 2010 data. However, I needed population totals for each election year
upon which these district-level proportions would be applied.12 Rather than use the total
number of voters in each election as the district population total, I instead applied the ethnic
12 Keep in mind that, outside of electoral information, the only district-level populationinformation available was through the 2010 census information. District populations wouldbe different in the election years (1996-2012) as compared to the year in which the census wascollected (2010).
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proportions to the registered voter population at the district level.13 In using this method,
I risk making a fallacy by assuming that ethnic populations registered to vote in the same
proportion as their population total. However, this risk is (1) much less severe than using
voter population totals and assuming Ghanaians voted in the same proportion as their ethnic
population proportion and (2) there are substantial reasons to believe that registering to vote
would have much less of an ethnic bias as compared to actual voting.
In Ghana, voter registration cards are the most common form of national identification
used by the populace. This is for several reasons. First, a national identification card system,
the ‘Ghana Card’, was slow to become established in Ghana’s Fourth Republic.14 Pilot mass
registrations for the Ghana Card, issued by the National Identification Authority (NIA), were
not begun until 2007. Then, with the introduction of a biometric identification system in
Ghana, the Ghana Card collection and issuing process was reformed and the new cards were
not available for re-issue until 2011.
Second, voter registration cards have been more available in Ghana. Prior to the initiation
of the Ghana Card system, the Electoral Commission had been issuing low-technology voter
registration cards since 1992. Unlike national identification cards which required traveling to
the district capital on two occasions (to submit an application and then to pick up the card),
13 Since the ethnic population totals are equal to the registered population totals, thedatasets upon which the Methods of Bounds and Ecological Inference models are thereforebased on the following categories: NDC, NPP, Third Party, Rejected Ballots, and No Vote.In order to calculate political party vote estimates by ethnic group, presented in Figures 4-1 -4-32, I take the Registered Total minus the No Vote estimate to obtain a new Voted total. Ithen divide the NDC and NPP respective estimates by the new Voted total to arrive at NDCand NPP estimates as a proportion of total votes rather than registered voters.
14 One casual conversation during my fieldwork led to an anecdotal story where the individualtold me that when he tried to cross into Burkina Faso from Ghana and showed his Ghanaiannational identification card, the guard stopped him, presented him in front of the entire line,and admonished the other would-be border crossers that this man was proof that Ghanaiannational identification cards exist! The guard knew the card to exist but cited that almost noGhanaian crossing the border ever seemed to have one.
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the Electoral Commission travels to voters’ polling stations to register voters and, until the new
2012 biometric registration cards, issued registration cards within minutes. Further, until the
new 2012 biometric system was established, voters’ registration cards did not expire. Though
the capture of biometric information and issuing of registration cards was more complicated in
the 2012 registration process (the EC still travels to polling stations to register voters but cards
are issued on a different day), Ghanaians were already routinized to use voter registration cards
as national IDs.
Even before the biometric registration process, voter registration cards were accepted
when making bank transactions, engaging with public institutions, registering a business,
picking up international money transfers, and so on. Further ECOWAS (Economic Community
of West African States) stipulations allow citizens of West African nations to cross borders
without passports15 , making the registered voters cards the most common ID used at
border crossings. That registered voter cards are widely accepted, and that locally both
voter information is collected and registered voter cards distributed, make the registered
voter card the preferred form of ID in Ghana. And now with the new biometric fingerprint
capture included in the 2012 registration process, these identification cards are more reliable
than ever. As a result, even if one is not politically active and does not intend to vote, it still
is very rational to register to vote in order to receive a registered voter identification card.
Unlike voting, interest in receiving an ID card is significantly less likely to depend on structural
characteristics such as ethnicity.
15 Obtaining a Ghanaian passport is its own challenge. It requires two trips to the districtcapital (for application and for pick-up), anywhere from weeks to months of waiting to receiveit, and, until recently, expired every 5 years. And, finally, you cannot use a passport to vote.Unless one is traveling outside of the ECOWAS territories, getting a passport is not thepreferred form of ID for the vast majority of Ghanaians.
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4.5 Results
4.5.1 Method of Bounds
As discussed previously, the Method of Bounds analysis provides deterministic information
about the minimum and maximum proportion of voters, by ethnic group, for any given political
party. Usually the boundaries estimated by the Method of Bounds are too wide to be of any
analytic use. But the information provided by the Method of Bounds is theoretically important
because EI models generally use districts with strong ethnic-political party correlations to
estimate the voting behavior of ethnic members in other districts.
The Method of Bounds tables show the deterministic information about tribal groups
for each of Ghana’s districts. By way of example, I showcase bounds information in Table 4-2
about voting patterns in Presidential elections by Asante voters in the Amansie West District
in the Ashanti Region. What this information shows is that, deterministically, at most 18.5% of
Asante constituents voted for the NDC, while at least 58.0% of voted for the NPP, in the 2012
Presidential race in Amansie West. Amansie West is an NPP stronghold and it is clear that
Asante voters make up a great part of the party’s success in that district. Overall, I provide
the Method of Bounds results16 to show which groups in which districts are contributing more
information to the EI modeling process.17
16 See Appendix B.
17 It is important to keep in mind that Method of Bounds estimates, like the EI models, arepredicting vote patterns based on the registered population. So when between 58.0% and78.0% of Asantes in Amansie West deterministically voted for the NPP, that is based on thetotal possible number of voters (i.e. registered voters) rather than the total number of voters.In other words, between 58.0% and 78.0% of registered Asante voters voted for the NPP in the2012 election, while the rest of the Asante population either voted for the NDC party, a thirdparty, had their ballot rejected, or did not vote in the election.
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4.5.2 Multinomial-Dirichlet Models
Next, I provide EI results for Presidential and Parliamentary races in Ghana from
1996-2012. I estimate results for both ethno-linguistic groups as well as tribal group
delineations18 , with error bars representing 95% confidence intervals19 20
4.5.2.1 Core political party supporters
As previously introduced, the ethno-linguistic groups most associated with political party
support are the Akans (NPP) and the Ewes (NDC). Within the Akan group, the two tribes
most notorious for their support of the NPP are the Asantes and the Akyems. While there
are divisions within the Ewe ethno-linguistic group, these differences are not captured by the
census. Asante, Akyem, and Ewe Presidential and Parliamentary voting patterns are presented
in Figures 4-1 - 4-3.21
Beginning with Presidential voting trends (Figures 4-1 and 4-2), we see that Asante
and Akyem support for the NPP and Ewe support for the NDC is consistently high. There
is a minimum of about 75 percentage points consistently separating NPP and NDC votes by
Asantes, and a consistent minimum of 54 percentage points separating NPP and NDC votes by
Ewes. Both Asante support for the NPP and Ewe support for the NDC dipped slightly in 2012:
at 87.1%, the Asante-NPP vote dropped below 90% for the first time since 1996 while the
Ewe-NDC vote slightly dropped to 85.2% from 87.7% and 92.6% in the respective 2008 and
2008 Runoff elections. The degree of NPP and NDC vote separation by Akyem voters has also
been wide with no signs of diminishing. That the Akyem-NPP vote levels have continuously
18 The full EI results are provided in Appendix C.
19 Figures 4-1 - 4-32
20 Also, see Appendix A for a table presentation of tribes and ethnic groups’ estimated votepercentages for the NDC and NPP in Presidential and Parliamentary elections.
21 In order to derive the party support percentages used in these graphs, I take the EIestimate of the number of ethnic voters who have not voted and subtract that from the totalregistered amount. I then divide NDC and NPP vote estimates by this new total.
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increased since the 2004 Presidential race is likely related to the fact that Nana Akufo-Addo,
the NPP Presidential candidate beginning in 2008, is a member of the Akyem tribe.
Turning to Parliamentary trends by the Asantes, Akyems, and Ewes (Figures 4-2 and 4-3),
there is a greater degree of volatility in Asante votes in Parliamentary races than Presidential
races, particularly after 2004. At first Asante support for NPP MPs has been high, and support
for NDC MPs low, but the margin between the parties dipped to about 60% in 2008 from a
roughly 90% margin in 2004. This margin slightly widened to about 70% in 2012, but Asante
votes for the NDC remained at about 13% (up from 5.5% in 2004).22 As for the Akyems, like
the presidential races the parliamentary trends show increasing NPP support and decreasing
NDC support since 1996, the largest margin at about 66% in 2012. Finally, Ewe votes in
Parliamentary races are high for NDC MPs and low for NPP MPs as expected. Yet 2012
showcased a dip in Ewe-NDC support to 64.3% of the vote with Ewe-NPP support at 23.8%,
the lowest point spread in the Fourth Republic elections. Like the Asante-NPP Parliamentary
trends, the Ewe-NDC vote peaked in 2004 and was lower in subsequent elections.
The groups encompassing the Core Party Supporters were relatively stable in their NPP
or NDC support. Yet two groups, the Asantes and Ewes, decreased the vote margin separating
the two political parties in recent Presidential and particularly Parliamentary races. For both
groups, these depreciations occurred in the 2008 and 2012 elections as compared to prior races.
4.5.2.2 Peripheral political party supporters
Outside of the Ewe core-NDC group, the Ga-Dangme and Mole Dagbani ethno-linguistic
groups usually lean toward the NDC, while the Akans are the broader NPP-leaning ethno-linguistic
group which encompasses Twi-speaking groups including and beyond the Asante and Akyem.
22 As mentioned elsewhere, several NPP-gone-Independent candidates were successful inthe 2008 Parliamentary elections, taking away votes from the NPP candidates. While thismay explain the particularly low turnout for the NPP in 2008 among Asante voters, thisdoes not explain the still comparatively low Asante-NPP turnout in 2012 nor the increasesin Asante-NDC votes over time.
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The Presidential and Parliamentary voting trends for these groups are presented in Figures 4-4
- 4-6.
First, the Ga-Dangme and Mole Dagbani groups have been relatively consistent in their
support for the NDC and NPP in Presidential elections since 2004. Mole Dagbani support for
the NDC is comparatively higher than that of the Ga-Dangme group.23 Ga-Dangme and Mole
Dagbani NPP votes have been very stable as well, such that a dip in Mole Dagbani NDC votes
in 2012 did not translate into an increase for the NPP Presidential candidate.
The Akan Presidential voting trends are more interesting. Since the 2000 runoff elections,
Akan votes for the NPP Presidential candidate have steadily decreased while Akan votes for
the NDC Presidential candidate have steadily increased. Given that we have seen Asante and
Akyem Presidential voting trends alone cannot account for this overall Akan-NPP Presidential
vote downtrend, it appears some Akan tribes are not as driven in their support of the NPP as
the Asante and Akyem Twi language speakers.
In the Parliamentary races (Figures 4-5 and 4-6), the difference between NDC and NPP
votes by Ga-Dangmes has increasingly narrowed since 1996, from about a 60 percentage
point spread to a less than 10 percentage point difference in 2012. This is in stark contrast
to the very consistent Ga-Dangme Presidential voting trends. Mole Dagbani Parliamentary
votes, on the other hand, have consistently largely gone to the NDC, though support for the
NPP did reach about 35% in 2008. The vote margins between the NDC and NPP since the
2000 elections are also narrower in Parliamentary races than in the Presidential races for Mole
Dagbani voters. Whereas the NDC-NPP vote margin had ranged from 30.3 to 36.6 percentage
points in the Presidential races, the NDC-NPP vote margin was significantly narrower in the
Parliamentary races, ranging from 18.7 to 25.5 percentage points.
23 The confidence intervals are relatively wide for the Ga-Dangme estimates, probablybecause of the Ga dominance in Accra where it is difficult to parse out voting patterns inconcentrated, diverse, and urban settings.
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Finally, like the Akan Presidential voting trends, Akan votes for NPP MPs were lower in
2008 and 2012 as compared to 2000 and 2004, while support for the NDC has continuously
risen and was up to 33% in the 2012 races. Overall, the Presidential and especially the
Parliamentary estimates demonstrate vote volatility within these peripheral ethnic supporters of
the respective NDC and NPP parties.
Excluding the Ewe ethno-linguistic group, each of Ghana’s 8 other ethno-linguistic group
categories can be divided into a number of encompassing tribal groups. My analysis of tribal
voting patterns is restricted to those tribes which make up at least 50% of the population
in one district, or at least 35% of the population in 2 or more districts. As explained above,
EI relies on deterministic information and voting patterns from administrative areas in which
groups are dominant as part of its estimation technique to determine overall ethno-linguistic
or tribal group voting patterns. This cutoff is used to ensure the results from the Ecological
Inference models are reliable.24
First, in Figures 4-7 - 4-14, we consider the NDC-leaning tribes. We have already looked
at Ewe (the NDC core group) Presidential and Parliamentary voting patterns, but here we also
consider vote patterns of peripheral-NDC supporters: Bimobas, Sefwis, Dangmes, Dagartes,
Dagombas, Nankansis, Kusasis, and Gas. For these tribes, the differences between NDC and
NPP support in Presidential races since 2000 remained about the same or widened in 6 out
of 8 groups (the Bimoba, Dangme, Dagarte25 , Dagomba, Nankansi and Ga) (Figures 4-7 -
4-10). It was only the Sefwis and Kusasis whose NDC-NPP vote margins did not widen. For
24 I make a couple of exceptions to this rule by providing results for the following tribes whichnarrowly miss the cutoff: Ga, Asen, and Denkyira/Twifo. First, the Ga somewhat narrowly missthe cutoff in making up 38.1% and 22.1% of the population in two districts, as well as over10% of the population in three others. The Asen make up about 48.4% of the population inone district and 31.9% of the population in a second district. Finally, the Denkyira/Twifo makeup 47.2%, 32.3%, and 29.5% of the population in three respective districts.
25 The Dagarte Presidential vote trend did initially narrow in 2004 and 2008 only tosignificantly widen in the 2008 runoff and 2012 elections.
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the Sefwis, the vote margin narrowed beginning after the 2000 elections. For the Kusasis,
the NDC-NPP margin, decreased from a 66.9 percentage point difference in 2004 to a
46.8 percentage point difference in 2012. Likewise, Kusasi support for the NPP opposition
continuously increased since 2004, from 12.3% to 23.1% in 2012.
The picture is similar for the Parliamentary voting patterns of the NDC-leaning groups
(Figures 4-11 - 4-14). Now the margin between NDC and NPP votes since 2004 narrowed for
two groups: Sefwi and Dagomba. Since 2000, the vote margin of difference widened for two
other groups, Bimoba and Dangme, and was either too close to call or waxed and waned for
the four other groups (Dagarte26 , Nankansi, Kusasi, and Ga). Overall for the NDC-leaning
groups, then, two of the eight groups narrowed their vote margins in Presidential (Sefwi and
Kusasi) and Parliamentary (Sefwi and Dagomba) elections. But only one group (Dagarte)
waxed and waned in its support in the Presidential contest as compared to four groups in
the Parliamentary elections (Dagarte, Nankansi, Kusasi, and Ga). By way of comparison,
differences in the vote margin separating the NDC and NPP decreased for the majority of
NPP-leaning tribes in both Presidential and Parliamentary elections.
As for NPP-leaning tribes, the Presidential elections (Figures 4-15 - 4-17) were slightly
less competitive for more groups overall than the Parliamentary races (Figures 4-18 - 4-20).
First, in presidential contests since at least 2004, four NPP-leaning tribes, the Akuapem,
Boron, Denkyira/Twifo, and Asen, increasingly narrowed the vote margin separating the NDC
and NPP. The Ahanta had stable vote margins separating the NDC and NPP while the Kwahu
generally supported the NPP over the NDC but the estimates had very wide margins of error.
Switching to the Parliamentary races, now 5 out of 6 NPP-leaning tribes (Akuapem,
Boron, Denkyira/Twifo, Ahanta, and Asen) narrowed the margin between NPP and NDC
26 Dagarte Parliamentary votes in 2008 were particularly close between the NDC and NPPin 2008. And, though the margin of difference did widen again in 2012, votes for the NPP in2012 were still higher than they had been since 1996.
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votes, and particularly so since at least 2004. Even the Ahanta which had maintained high
levels of support for the NPP Presidential candidate over the years have seen their party
support wane in Parliamentary races. Again, the Kwahu appear to consistently favor the NPP,
but the margins of error are too wide in the 2008 and 2012 races to make firm conclusions.
Overall, the NPP-leaning tribes appear more willing to vote for the NDC opposition than
NDC-leaning tribes.
4.5.2.3 Unincorporated groups with mixed voting patterns
Figures 4-21 through 4-24 show Presidential and Parliamentary voting trends for
ethno-linguistic groups not known to outright support one party or the other. Gruma votes
in Presidential races have been increasingly competitive since 2004, while Grusi votes have
increasingly tended toward the NDC. Guan votes in Presidential elections are consistently
competitive, save for the 1996 race, while Mande and Other votes in Presidential elections are
erratic and/or too close to call. In the Parliamentary races, Guan, Gruma and Grusi votes have
been very close since at least 2004.
Finally, of the tribes with mixed voting patterns (Figures 4-25 - 4-32), three tribes
(Kasena, Builsa, Sisala) favored the NDC in Presidential voting but exhibited competitive
voting or favored the NPP in Parliamentary elections. Two other tribes (Wasa, Nzema) favored
the NPP in Presidential voting. The Wasa in particular gradually depressed their support
for the NPP over time in both Presidential and Parliamentary elections, whereas the Nzema
somewhat leaned to the NDC in Parliamentary elections, except in 2004. Finally, six tribes
(Chokosi, Guan3, Fante, Guan5, Mamprusi, Kokomba) displayed mixed or competitive voting
patterns in Presidential elections. Two of these tribes, the Chokosi and Guan3, largely favored
the NDC in Parliamentary elections. The Fante strongly favored the NDC in the 2008 and
2012 Parliamentary elections, while the Kokomba strongly favored the NPP in these same
election years. Finally, the Guan5 and Mamprusi tribes exhibited competitive voting patterns in
both Presidential and Parliamentary races.
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Notably, three groups narrowed the difference between NDC and NPP support since 2004
(Wasa, Sisala, and Mamprusi) while two other groups widened their vote margins (Builsa and
Kokomba).
4.6 Presidential Kingmakers
Results from the EI models also highlight the tribes whose changes in voting patterns
were particularly influential in determining the winners of presidential elections. Kufuor
(NPP) won the 2000 and 2000 runoff elections with support from a wide range of groups,
but this wide-based support narrowed in his still successful re-election bid in 2004. In 2008,
Atta Mills (NDC) forced a runoff, against then ahead NPP candidate Akufo-Addo, based on
increased support from both NDC-leaning and NPP-leaning groups. The 2008 runoff election
was secured for the NDC with increased votes from NDC-core and leaning groups and two
NPP-leaning groups. Finally, Mahama’s (NDC) victory in 2012 was largely built upon the
coalitions established in Atta Mills’ 2008 victory, except for two notable increases in NDC votes
from an NPP-core group (Asantes) and an NDC-leaning group (Nankansi).
First, the 2000 and 2000 runoff results demonstrate the strong nation-wide push for the
first alternation of power, from the NDC to the NPP, in Ghana’s Fourth Republic. One of the
NPP-core groups, the Asantes, increased their votes for the NPP Presidential candidate in
2000, as compared to 1996, but so did the Ewes (an NDC core group), 4 of 6 NPP-leaning
tribes (Boron, Denkyira/Twifo, Ahanta, and Asen), and 6 of 8 NDC-leaning tribes (Bimoba,
Sefwi, Dangme, Dagarte, Nankansi, and Kusasi). Further, the Asantes and Akyems increased
their NPP vote percentages in the 2000 runoff as compared to the 2000 election, but again so
did the Ewes, Boron, Denkyira/Twifo, Ahanta, Asen, Kwahu, Bimoba, Dangme, Dagarte, and
Nankansi. Interestingly, four NDC-leaning tribes (Dangme, Dagomba, Nankansi, and Kusasi)
strongly increased their support of the NPP in either the 2000 or 2000 runoff elections, but
then switched back to a majority voting for the NDC in 2004 and every election thereafter.
Clearly the national momentum for the first change in power in 2000 was so strong that it
sometimes meant voting against the home party.
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Though Kufuor (NPP) successfully won re-election in 2004 (52.5% to 44.6%), overall
Akan support for the NPP began to fall in 2004 as compared to the 2000 runoff. The Akyems
(NPP-core) and Borons (NPP-leaning) in particular faltered significantly in their support for
the NPP as compared to the 2000 runoff. On the other hand, the Akuapems (NPP-leaning)
dramatically increased their support for the NPP in the 2004 Presidential election as compared
to the 2000 runoff. As for NDC-leaning tribes, the Bimoba and Dagarte significantly increased
their support for the NPP in 2004 at the expense of the NDC, as compared to 2000, while
other tribes, including the Dangme, Dagomba, Nankansi, and Kusasi began to systematically
decrease their levels of NPP support and increase their NDC Presidential votes beginning in
2004. One notable unincorporated group, the Fantes, did also strongly increase their votes for
the NPP in 2004 as compared to the 2000 runoff. The percentage of Fantes voting for the
NPP increased from 44.9% in 2000 and 57.7% in the 2000 runoff to 64.9% in 2004 (Figure
4-27), resulting in an estimated 244,363 more votes for the NPP (and only 51,656 estimated
more votes for the NDC) as compared to the 2000 runoff election.
In the second alternation of power, from the NPP to the NDC in 2008, the Ewes, Bimoba,
Dangme, Ga, and Nankansi increased their relative support for the NDC from the 2004
Presidential race. While the number of Bimoba, Dangme, Ga, and Nankansi voters who turned
out for the 2008 Presidential election were fewer as compared to 2004, votes for the NDC
increased by 24.7%, 12.9%, 25.1%, and 41.1% for each of these respective groups. That
meant a total of 139,973 estimated more votes for the NDC, and an estimated 65,578 fewer
votes for the NPP, from these four peripheral groups in 2008 as compared to 2004.
Further, all 6 NPP-leaning tribes decreased their NPP votes in the 2008 Presidential
election as compared to 2004. Though a fewer number of voters from these groups turned
out to vote in 2008 as compared to 2004 (except for Kwahu), NDC votes increased by
45.4%, 78.0%, 78.0%, 11.5%, 6.5% and 294.3% by the Ahanta, Akuapem, Asen, Boron,
Denkyira/Twifo, and Kwahu, respectively. Votes for the NPP for these tribes changed by 0.5%,
-12/3%, -25.0%, -10.7%, -7.7%, and -7.5%, respectively. In total, the NPP-leaning tribes
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provided 78,093 more votes for the NDC, and 81,221 fewer votes for the NPP, in the 2008
Presidential election as compared to 2004. Finally, Fante (unincorporated) votes for the NPP
dropped by an estimated 220,708 votes while votes for the NDC increased by an estimated
135,755 votes, as compared to the 2004 election.
Neither NPP candidate Akufo-Addo (49.15%) nor NDC candidate Atta Mills (47.92%)
received greater than 50% of the vote, thus forcing a runoff election. Akufo-Addo only missed
the 50% cutoff point by 73,478 votes. Had the increased 139,973 votes for the NDC by the
NDC-leaning tribes, the 78,093 more votes for the NDC by the NPP-leaning tribes, or the
135,755 more NDC votes by the Fantes not come, Akufo-Addo would have won the 2008
election outright. Significantly, this also would also have reversed Ghana’s second transfer of
power at the national level.
In the subsequent 2008 runoff election, the Ewes (NDC-core), Bimoba, Sefwi, Dagarte,
Dagomba, and Nankansi (each NDC-leaning) increased their relative support for the NDC
as compared to the 2008 regular Presidential race. As mentioned above, only the Akyems
increased their NPP Presidential support in both the 2008 and 2008 runoff elections. Of
the NPP-leaning tribes, 3 of 6 groups (Ahanta, Asen, Kwahu) did increase their levels of
support for the NPP in the 2008 runoff elections as compared to the regular election, but
two others, the Akuapems and particularly the Denkyira/Twifo, actually increased their votes
for the NDC in the 2008 runoff. Finally, four other unincorporated groups (Builsa, Sisala,
Fante, Mamprusi)(Figures 4-25 - 4-28) strongly increased their votes for the NDC in the 2008
runoff, resulting in an estimated 123,564 more votes for the NDC (and 50,271 fewer votes
for the NPP), in comparison to the regular election, in a runoff only decided by 40,586 out of
9,001,478 valid votes cast (0.5%).
In 2012, when John Mahama (NDC) won as the replacement for the recently deceased
President Atta Mills (NDC), the Asantes (NPP-core) and Nankansi (NDC-leaning) were
the only two tribes to increase their level of support for the NDC from the 2008 regular
election. Estimates show that, while turnout was about 35% higher for Asantes in the 2012
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Presidential Election as compared to the 2008 regular Presidential Election, Asante votes for
the NPP increased by 28.9% while Asante votes for the NDC increased by 125.0%. With
the NDC only winning the 2012 Presidential Election by 977,589 votes, the 131,180 more
estimated votes for the NDC by the Asantes in 2012 as compared to 2008 makes up a sizeable
13.4% of the difference separating the NDC from the NPP in the final tally. Further, Ghana’s
first-past-the-post electoral system means the NDC only narrowly avoided a runoff election by
exceeding the 50% mark in 2012 by 231,390 votes, of which the increase in Asante votes for
the NDC from 2008 to 2012 makes up 56.7%. Had the Asantes not increased their votes for
the 2012 NDC Presidential candidate, as compared to their 2008 numbers, Mahama would only
have passed the 50% mark by 100,210 votes out of 32,985,786 (0.3%) valid votes cast.
Conversely, the Akyems (NPP-core), Ewes (NDC-core) and Kusasi (NDC-leaning)
actually increased their support for the NPP Presidential candidate in 2012 as compared to
2008. These increases were not enough to hold John Mahama back from reaching the 50%
first-past-the-post threshold.
4.7 Discussion
The application of Ecological Inference models to estimate votes by ethnic groups can
greatly contribute to voting analyses in countries dominated by ethnic divides. Much of
what we know about ethnic voting in Africa relies on generalities because of the focus on
regional-level voting results or because researchers use national-level analyses of individual
behavior which are forced to collect individuals’ ethno-linguistic identities to ensure a large
enough N, ignoring their tribal backgrounds. As EI estimation techniques become more reliable
and well-known, and as data on sub-Saharan African populations becomes more available,
ecological inference offers a lot of potential to political analysis at the sub-national level in
African countries.
My application of Ecological Inference models to Ghana analyzed national-level voting
trends while maintaining individuals’ tribal group identities vis-a-vis their ethno-linguistic
group identities. Outside of Asantes, Akyems, and Ewes, I presented data on voting trends
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for 8 other NDC-leaning tribes, 6 other NPP-leaning tribes, as well as 11 other tribes who
do not outright support one political party over the other. This analysis demonstrates that
Ghanaians are increasingly willing to vote against their ethnic voting tradition. The propensity
to support the opposition is overall stronger for peripheral support groups rather than core
party supporters. But both the Asantes and Ewes did increase support for the opposition in
recent Presidential and Parliamentary elections. Additionally, it is also clear that NPP-leaning
groups have been more volatile in their votes as compared to NDC-leaning groups. Overall, for
all of the peripheral party supports, 6 out of 14 decreased the vote margins separating the NDC
and NPP in Presidential elections, while 7 out of 14 decreased these same vote margins in
Parliamentary elections. And while all three core party support groups maintained or increased
the vote margins separating the NDC and NPP in Presidential elections, two of three (Asantes
and Ewes) showed some willingness to decrease this vote margin in elections after 2004.
This chapter has demonstrated an increasing level of vote volatility in elections since
2004 for ethnic groups in Ghana. The following chapter provides evidence that this volatility
is directly related to the increased political competition at the local level imposed by Ghana’s
centralized system of government.
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Table 4-1. Ghana’s ethno-linguistic groups and tribes
Ethno-linguisticgroup
Akan Ga-Dangme Ewe Guan1 Gruma Mole-Dagbani
Grusi Mande Other
Tribes Agona Dangme* Guan1 Bimoba* Builsa* Kasena* Busanga insideAhafo Ga* Guan2 Kokomba* Dagarte* Mo Wangara outsideAhanta* Other Ga-
DangmeGuan3* Basare Wali Sisala* Other
MandeAkuapem* Guan4 Pilapila Dagomba* VagalaAkwamu Guan5* Salfalba Kusasi* Other
Grusi1Akyem* Guan6 Kotokoli Mamprusi* Other
Grusi2Aowin Guan7 Chamba NamnamAsante* Guan8 Other
GrumaNankansi,Tal., Gur.*
Asen* Other Guan NanumbaBoron* MosiChokosi* Other Mole-
DagbaniDenkyira/Twifo*EvalueFante*Kwahu*Nzema*Sefwi*Wasa*BawleOther Akan
Party Affili-ation
NPP NDC-leaning
NDC mixed mixed NDC-leaning
mixed mixed mixed
*Refers to tribes included in the Ecological Inference analyses.1Guan tribal categories are made up of several tribes. Guan1=Akpafu, Lolobi, Likpe, Bowiri, Buem, Santrokofi, Akposo; Guan2=Avatime, Ny-ongbo, Tafi, Logba; Guan3=Awutu, Efutu, Senya, Breku; Guan4=Cherepong, Larteh, Anum-Boso; Guan5=Gonja; Guan6=Nkonya; Guan7=Yeji,Nchumuru, Krachi, Nawuri, Bassa Achode; Guan8=Nkomi, Wiase, Dwan.
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Table 4-2. Asante bounds - Amansie West District
Year NDC NPP
1996 Pres.: ndc (.126, .268) npp (.660, .840)2000 Pres.: ndc(.000, .175) npp (.825, 1.00)2000 Runoff: ndc(.000, .145) npp (.855, 1.00)2004 Pres.: ndc (.000, .108) npp (.752, .894)2008 Pres.: ndc (.000, .097) npp (.594, .744)2008 Runoff: ndc (.000., .143) npp (.661, .860)2012 Pres.: ndc (.000, .185) npp (.580, .780)
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CHAPTER 5THE INSTITUTIONALIZATION OF LOCAL-LEVEL COMPETITION IN GHANA
Features of Ghana’s democratic institutions break the cycle of dominant party politics,
neopatrimonialism, and ethnic voting without the coordination struggles inherent in decentralized
institutional configurations which increase the number of political decision makers. I argue
that the central appointment of officials in Ghana’s system of local government actually
institutionalizes political competition at the local-level and has thus contributed to increased
responsiveness on the part of politicians and increased programmatic influences on citizen
votes.
The co-existence of both a centrally-appointed district-level District Chief Executive
(DCE) and a constituency-level elected Member of Parliament (MP) within each constituency
is significant.1 The relationship between DCEs and MPs is naturally competitive, but the
nature of this competition intensifies when these two officials are of different political
parties (‘Unfriendly Pairs’). As power has changed hands at the national-level, the partisan
appointments of DCEs also alternate. Informed by 16 months of fieldwork in Ghana, I use
OLS regressions to model voting effects when the MP and DCE are of the same political party
versus when these politicians are of different political parties. I find that competition produces
increased electoral volatility in constituencies with ‘Unfriendly (DCE-MP) Pairs’ as compared
to those with ‘Friendly Pairs’. In short, even institutionally crafted local-level competition can
contribute to deepened democratic progress.
1 Constituencies fall within Administrative Districts such that one constituency maycorrespond to one district, as is the case in rural areas, one constituency may be paired withanother under a single Administrative District, or two or more constituencies may fall under asingle (Metropolitan) Administrative District. As of 2012, in addition to the centrally-appointedDCE, districts had as little 1 up to as many as 13 MPs (Accra Metropolis District) electedwithin a district’s boundaries.
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Antithetical to decentralized systems where locally officials are solely accountable to the
public, the presidential appointee (DCE) is almost wholly non-accountable to the public.2
The benefits of decentralized systems are widely touted, while centralized local government
structures are condemned as undemocratic and as evidence of a central leader’s interest in
maintaining control at the local level. Less explored, however, are the potential benefits of the
simultaneous institutionalization of both locally-elected and centrally-appointed officials. There
may be good reason for this. Central governments may want to signal democratic progress by
implementing local government reform when, in actuality, such a hybrid system allows power to
remain in the hands of the central government vis-a-vis their centrally appointed officials.
However, in order for a system of Presidential appointments to function at its best
capacity, an alternation of power at the national level is required to induce alternations in
local-level appointments. If local government reform is merely intended to signal democratic
progress, then such a transfer of power at the top is unlikely. Similarly, if central-appointments
of local officials were primarily used to channel patronage (rather than development) down
to the local level to secure the President’s grip on power, then we would not have seen
turnovers in the 2000 and 2008 elections. It is important that Ghana’s centralized system
also incorporates majoritarian electoral rules at the national level, to encourage alternations in
national power-holders and thus alternations in sub-national appointments.
The benefits of decentralization are widely understood, but in this chapter I argue that the
presence of central appointments in Ghana’s system of local government increased local-level
political competition at a surprisingly quick rate for such a new democracy. Local-level political
2 The DCE requires a confirmation vote in the District Assembly prior to his/herappointment. As discussed in Chapter 3, assembly members are heavily pressured to approve ofDCE appointments and district development suffers in the absence of a DCE. After a DCE isconfirmed, the assembly can technically issue a disapproval vote dismissing the DCE, but, giventhe political and developmental problems this entails, a vote for the dismissal of a DCE rarelyoccurs.
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competition has directly contributed to a lessening of neopatrimonial political logics and ethnic
voting in Ghana.
5.1 Hypotheses
As illustrated in Chapter 3, the relationship between DCEs and MPs can be quite tenuous,
particularly if the pair come from different political parties. In this chapter I argue that the
appointment of an DCE of a different political party from the local MP(s) heightens political
competition at the local level. Voters in Ghana, like voters in other African democracies, expect
and respond to provisions of development goods by their politicians. As each of these officials
seek greater constituent support for their parties, this competition is played out in development
goods, and particularly those development goods which are both cheap and highly visible to the
electorate (e.g., water boreholes, connections to the electric grid, primary and secondary school
blocks, etc.). This leads to my principal hypothesis:
Hypothesis 1: Unfriendly3 MP-DCE pairs will cause a greater turnover of votes in thesubsequent Presidential and Parliamentary elections as compared to Friendly MP-DCEpairs.
My research has shown that voters exposed to an Unfriendly MP-DCE pair can compare
the effectiveness of each political party to a greater extent than if an MP and DCE are of the
same political party. That alternations of power have occurred in both 2000 and 2008 means
that both the NDC and the NPP have appointed their own party officials in every district
across the country. The combination of the positioning of DCEs from political traditions
which oppose the locally dominant party as well as the fact that the Fourth Republic’s
local government system is more effective than any past regime, have had big impacts on
individuals’ experience with government. Since voters in African countries are more concerned
with politicians’ abilities to deliver public goods provisions than they are policy agendas
3 Unfriendly Pairs means, in the term prior to the election under analysis, the MP and DCEwere of different political parties. Third party and Independent MPs are excluded from theanalysis because we cannot be sure with whom the MP sat in Parliament.
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(Wantchekon 2003; Baldwin 2013), Unfriendly MP-DCE Pairs are more responsive to citizen
needs and promote greater development initiatives as they work to upstage one another.
Further, in the elections following an Unfriendly MP-DCE Pair, I also expect the direction
of the increased vote volatility to favor the DCE’s party. Not only are some communities
experiencing effective governance from the opposing party (through the DCE) often for the
first time in their localities, but DCEs are also better equipped to provide more effective
development vis-a-vis the MPs. DCEs reside within the communities year-round and are
armed with a significantly greater portion of the District Assembly Common Fund (DACF) as
compared to the Accra-based MPs. As for the MPs, technically they do have the advantage
of being able to lobby ministries to include their constituency within the next planned
national-level development project, but these opposition MPs’ political party membership
puts them at a lobbying disadvantage and they also often have a hard time taking credit for
such national-level initiatives. DCEs should win the unfriendly MP-DCE competition, and, if so,
the evidence will be born out in increased DCE party votes and decreased MP party votes in
elections immediately following the unfriendly pairing. This prediction is captured in Hypothesis
1a:
– Hypothesis 1a: The direction of the increased vote total should favor the DCE’spolitical party
Alternatively, it might be the case that voters actually resent the Presidential appointment
of such a powerful individual in the DCE within their communities. There exists a great deal
of debate in Ghana about whether DCEs should continue to be appointed by the President.
Indeed, both NPP and NDC politicians have encouraged the election of DCEs when they have
been in opposition, but these same officials quickly quiet their tune after their party wins the
Presidential election and hence the right to appoint DCEs. Thus, the presence of an Unfriendly
MP-DCE Pair prior to an election might actually mobilize voters behind their locally-elected
MP and his/her political party, in comparison to areas with relaxed Friendly MP-DCE Pairs.
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Though the analysis covers the 2000-2012 Presidential and Parliamentarian elections, I
expect the effect of Unfriendly MP-DCE Pairs to be less operative in both the elections prior to
2004 and in the Presidential Runoff elections in 2000 and 2008. First, the reason for qualifying
the 2000 elections is because this electoral period was heavily influenced by the longevity
of NDC rule up to that time. President J.J. Rawlings had been the democratically-elected
President since 1992, but he had also ruled as an authoritarian leader of the country since
1982. As demonstrated in Chapter 4, when Rawlings announced that he would abide by the
Presidential two-term limit as stipulated in the 1992 Constitution, Ghana’s voters were heavily
influenced by the possibility of a democratic transfer of power. As such, the effect of Unfriendly
MP-DCE Pairs was less of a driving force in determining votes as compared to the motivations
associated with achieving the Fourth Republic’s first turnover of presidential power with John
Kufuor’s (NPP) victory.4 We thus might expect to see an increase in NPP votes across each
of the districts, but particularly those districts whose constituencies had elected an NPP MP to
power in the prior (1996) election.
Hypothesis 2: The effect of Unfriendly MP-DCE Pairs on increasing support in favor ofthe DCE’s political party should not begin until after the NDC faces its first defeat in the2000 elections. Instead, the 2000 elections should show us that districts with NPP MPs,and thus Unfriendly MP-DCE pairings in the prior term, rallied voters behind the NPPparty in order to force the Fourth Republic’s first transfer of power.
Secondly, as pertains to Presidential Runoff elections, the mechanisms which guide votes
during Presidential Runoffs are less about competition between the MP and DCE over the last
four years and more about each party’s surge of national resources and patronage distribution
to increase both voter turnout and votes for the respective parties. As such, Hypothesis 3
states:
4 Indeed, this was the first time in 21 years that someone of the Danquah-Busia-Dombopolitical tradition, in Kufuor, could be elected President. The last head of state belonging tothe Danquah-Busia-Dombo political tradition was arguably the Supreme Military Council underFred Akuffo. Akuffo was deposed by the Armed Forces Revolutionary Council, of which J.J.Rawlings was a leading member, in 1979.
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Hypothesis 3: The effect of Unfriendly MP-DCE Pairs on changes in votes will bemuted in the Presidential Runoff elections where parties’ national resources mobilize theirrespective political bases.
5.2 Model Overview
5.2.1 Dependent Variable and Primary Independent Variable
In this paper, I use OLS regressions with robust standard errors to predict changes in
party votes in communities where the MP and DCE are of different political parties (Unfriendly
Pairs), as compared to communities where these actors are of the same political party (Friendly
Pairs). To assess the effect of Unfriendly versus Friendly Pairs, my dependent variable is the
constituency-level differences in respective Presidential and Parliamentary party votes from
one election to the next. So, using the 2012 races as an example, four outcome variables are
predicted: 2012 minus 2008 NDC Presidential votes, 2012 minus 2008 NDC Parliamentary
votes, 2012 minus 2008 NPP Presidential votes, and 2012 minus 2008 NPP Parliamentary
votes.
The primary independent variable under investigation is whether Unfriendly MP-DCE
Pairs, as compared to Friendly Pairs, result in increased DCE party votes, increased MP
party votes, or no significant difference in party votes, in the subsequent election. Unfriendly
Pairs are coded dichotomously, where 1 represents an Unfriendly Pair in the prior term and 0
represents a Friendly Pair in the prior term. For instance, NPP candidate John Kufuor won the
2000 Presidential election and subsequently dismissed all of former-President Rawlings’ DCEs.
Kufuor then appointed NPP DCEs in each district.5 If an MP elected in 2000 belongs to
5 Even within opposition party strongholds, the President goes to great ends to find aparty-affiliated individual who would qualify as a DCE. One former DCE explained that (s)hehad been working in Accra prior to her/his appointment. One day this individual received acall from the President’s Chief of Staff who explained that (s)he was needed at the Office ofthe President for a meeting the following day. This individual did not attend party meetingsor openly affiliate with the President’s party but it turns out that her/his name and place ofbirth were discovered on an old party members list from when the individual had attendedthe University of Legon several years prior. This individual was appointed DCE of her/hishometown district after this meeting (Interview 11/07/2013).
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the NPP political party, this will be coded as a Friendly Pair (coded as 0), considering all the
DCEs under Kufuor were also NPP members. This variable is then used in the 2004 elections
analysis.6 Constituencies where NDC MPs were elected in 2000 were coded as ‘Unfriendly
Pairs’ (coded as 1). Finally, I excluded constituencies which had elected 3rd party/Independent
MPs because these MPs may have either remained independent or may have sat with one or
the other party in Parliament (Table 5-1).
5.2.2 Controlling for Structural Conditions Impacting MP-DCE Relationships
Three structural conditions impacting MP-DCE relationships are (1) the Number of MPs
within the District, (2) the Type of District, and (3) whether the district was newly created.
First, as explained in footnote 1 in this chapter, multiple constituencies sometimes
fall within any given Metropolis, Municipality, or District. Since MPs are elected at the
constituency-level, multiple MPs are sometimes elected within one District. In these cases, a
single DCE has to manage relationships with multiple MPs and this may impact the nature of
each MP-DCE relationship. In particular, the competitive nature of an Unfriendly MP-DCE
pair may be dulled or enhanced in the presence of other either Unfriendly or Friendly MP-DCE
pairs. The variable, Multiple MPs, is coded as 1 for constituencies whose MPs are not the only
MP in the district, and 0 for constituencies whose MPs are the sole MPs within the district.
Second, the three types of districts are Metropolises (coded as 3), Municipalities (coded
as 2), and Districts (coded as 1). These district types have decreasing population sizes and
economic bases, and are assigned different weights in the sharing formula used to determine
the DACF. These differences could have an impact on the nature of the relationship between
MPs and DCEs, including the development opportunities available to the DCEs.
6 Remember, we are controlling for the presence of an Unfriendly, as opposed to Friendly,Pair in the prior term. This is in order to test for impact of an Unfriendly Pair in the followingelection.
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Third, when new districts are created it takes time to set up the District Assembly
and to appoint and orient bureaucratic department heads to the new district’s terrain and
particularities. New districts may be less efficient as compared to older districts, and this
may hinder the DCE’s ability to initiate development projects and sway voters. Further, the
creation of narrower administrative units has been known to instigate local conflicts (Lentz
2006), which may preoccupy the attention of the DCE and/or MP(s) and reduce the provision
of development goods. New District⟨04⟩⟨08⟩ is coded dichotomously, where newly created
districts in the prior term are coded as 1 and all other districts are coded as 0.7
5.2.3 Controlling for Structural Conditions Impacting Local Politics
I also control for 8 structural conditions which generally affect local politics and voter
perceptions leading up to an election. First, I use a dummy variable to control for the effect
that the announcement of a new constituency or district might have on voters. Ghana’s
politicians use the creation and upgrading of constituencies/districts to appeal for constituent
votes, even when the structural population and economic activity requirements spelled out in
Local Government Act, 1993 (Act 462) are not met (Ahwoi 2010). The announcement of a
new constituency or district (coded as 1), it is predicted, will correlate with increased votes for
the President’s party in the upcoming election.
Second, I control for the overall competitive nature of the elections within each
constituency. Naturally more competitive constituencies may generally result in greater
vote volatility, outside of MP-DCE pairings. To control for level of competition in the prior
election, I use the Parliamentary winner’s share of votes, in decimal form, at the constituency
7 No new districts were created until 2004, so this variable is not included in Tables 5-2- 5-4. For Tables 5-5 - 5-7, a high degree of collinearity is introduced in the models whencontrolling for both Multiple MPs and whether the district was newly created (ex: NewDistrict08). Including either Multiple MPs or New District did not substantially change theresults. Models controlling for New District are presented in Tables 5-5 through 5-7.
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level in the prior Parliamentary race. An increase in this variable means fewer votes were ‘up
for grabs’ and thus the election was less competitive.
Next, I control for five different demographic characteristics derived from Ghana’s 2010
census which may impact the functioning of local politics.8 These are (a) linguistic diversity,
(b) percentage of agricultural households, (c) education rates, (d) religious demographics, and
(e) ethnic group population percentages.
(a) In global settings, diversity has been linked to lower levels of trust and can thusnegatively impact economic success (Knack and Keefer 1997), the provisions ofpublic goods (Alesina, Baqir, and Easterly 1999; Vigdor 2004), and encouragerent-seeking behavior by politicians (Knack and Keefer 1997; Franck and Rainier2012). Because speaking the same language can play an important role in generatingunderstanding and trust within ethnically-diverse communities (Banerjee, Iyer, andSomanathan 2005, 639), I control for Linguistic Diversity, captured as the inverse of theSimpson’s/Herfindahl-Hirschman Index based on 10 ethno-linguistic categories within theGhana 2010 Population and Housing Census. This index measures the probability thatany two individuals selected at random belong to the same ethno-linguistic group. I takethe inverse of this index so that increased measures of this variable refer to increasedlevels of diversity.9
(b) I use the fraction of households engaged in agricultural practices to control for degreeof ‘ruralness’. Ghana’s 2010 Census does produce a rural and urban indicator, butthis measure is only based on population size (localities with 5,000 or more personsare automatically classified as urban) and does not take into account the level ofdevelopment of the district. ‘Agric rate’ is coded such that a 0.4 means 40% of the
8 The linear regression models presented in Tables 5-2 -5-7 use constituencies as the levelof observation. Ghana’s 2010 census reports data at the district level. As a result, these 5demographic controls are imputed from the district level onto the constituency observation. Forinstance, if a district has more than one constituency within it, the district-level data is appliedto both constituencies. Though this imputation implements an assumption of homogeneitywhich may bias the results, it was deemed more important that these controls be includedwithin the analysis.
9 Alternatively, I also control for Tribal Diversity in case the politically salient groups existwithin language groups (Fearon 1999, 5). Alternating between Ethno-Linguistic and Tribalmeasures of diversity did not have substantive impacts on the models and only the modelscontrolling for Ethno-Linguistic Diversity are presented in Tables 5-2 - 5-7.
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households are engaged in agricultural production activities. These activities include cropfarming, tree planting, fish farming, or animal rearing.10
(c) The more educated a population, the more likely it is that voters are informed aboutlocal and national politics. Alternatively, educational attainment can also signify wealthand individuals with higher educational attainment are sometimes associated with theNPP. This may be because the NPP espouses an ‘elitist’ political tradition or that theparty historically championed a pro-capitalist, rather than socialist, rhetoric. Either way,to control for education, the models include the respective fraction of the population whohave attended primary school (excluded as the reference category), secondary school,post-secondary school, and who have not had any formal education.
(d) In Ghana, Muslims in the southern half of the country often reside in segregatedZongo, or ‘stranger’, settlements within the community. In the North, Muslims oftenmake up the majority of the population and are well-integrated into society. Similarly,the historical forced expulsion of Nigerians by President Busia’s government in 1969particularly terrorized Zongo communities, because they also housed a large percentageof Muslim Nigerians resident in Ghana. This history has trickled its way into politicsof Ghana’s Fourth Republic and Muslims are, on average, more favorable of the NDCand often shy away from the NPP whose political tradition is associated with the Busiagovernment. I thus control for the fraction of residents who are Muslim as derived fromthe 2010 Population and Housing Census.
(e) In both African and Ghanaian politics, ethnicity is consistently the best predictor ofcitizen voting behavior (Fridy 2007a; Bratton, Bhavnani, and Chen 2012). Ghana’sStatistical Services collects tribal data in conducting the 2010 census and collates thosetribes into major ethno-linguistic groups when reporting ethnicity population figures.The fraction of the population falling within these 9 categories (Akan, Ga-Dangbe, Ewe,Guan, Gurma, Mole Dagbani, Grusi, Mande, Others) are controlled for in the models,where Ga-Dangbe serves as the reference category.
5.3 Results
When Jerry John Rawlings transitioned the authoritarian Provisional National Defense
Council (PNDC) to democratic rule (Ghana’s Fourth Republic) in 1992, Rawlings contested
the 1992 elections as the nominee of the National Democratic Congress (NDC) political party.
Rawlings won the Presidential elections in 1992 and 1996 and stepped down from power at the
end of his second term in 2000. The 2000 elections marked the first time a peaceful transfer
10 According to the 2010 Census Report, only about 1% of the households engaged inagricultural activities were involved in fish farming.
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of power via the ballot box had occurred in Ghana’s history. John Kufuor (NPP) was elected
President in two rounds of voting. Kufuor was re-elected in 2004 and stepped down at the
conclusion of his second term in 2008. The 2008 elections marked the second time a peaceful
transfer of power occurred, as John Atta Mills (NDC) won the Presidency in two rounds of
voting. Atta Mills passed away just before the 2012 elections and his Vice President, John
Mahama, was elected President in 2012.
To reiterate, with reference to Hypothesis 1a, I expect that the presence of Unfriendly
Pairs in the prior term should increase votes for the President’s party in the 2004-2012
elections. Specifically, in the presence of Unfriendly Pairs, I expect NPP votes to increase in
2004 and 2008 (when the NPP had appointed all the DCEs in the prior term) and decrease
in 2012 (because the NDC won in 2008 and appointed all the DCEs for the 2008-2012 term).
Similarly, I also expect NDC votes to decrease in 2004 and 2008 and increase in 2012, in
constituencies which have Unfriendly Pairs. Per Hypothesis 2, I do not expect the presence of
Unfriendly MP-DCE Pairs to affect voting until after the 2000 elections. Finally, per Hypothesis
3, the presence of Unfriendly MP-DCE Pairs in the 2000 and 2008 Presidential run-off elections
are not expected to impact vote decisions in the same manner as regular Presidential and
Parliamentary elections.
5.3.1 2000 Elections
Across the elections, the impact of Unfriendly MP-DCE Pairs as compared to Friendly
Pairs, has a significant impact on changes in party votes. The effect is generally weaker for
the restricted models, which only control for the structural conditions impacting MP-DCE
Relationships, as compared to the full models which additionally control for the structural
conditions affecting local politics. Beginning with the 2000 Elections, as predicted in
Hypothesis 2, constituencies which had NPP MPs alongside NDC DCEs had significantly
decreased NDC Presidential (-5.2%, Model 2) and Parliamentary (-8.7%, Model 4) votes
in 2000 from 1996, as compared to constituencies with Friendly Pairs. Similarly, districts
with Unfriendly Pairs had increased NPP Presidential (+3.0%, Model 6) and Parliamentary
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(+11.4%, Model 8) votes in 2000 from 1996, as compared to constituencies with Friendly
Pairs. Other substantive variables significantly correlated with votes were Multiple MPs, Level
of Competition, Secondary School Attendance, Muslims (%) and a few ethnic variables (Table
5-2).
5.3.2 2000 Presidential Runoff Elections
In the 2000 Presidential Runoff election (Table 5-3), the effect of having a NPP MP in the
prior term is correlated with increased NPP Presidential votes by 3.1% (Model 12). The effect
of having a NPP MP in the prior term also corresponds to increased NDC Presidential votes
in the restricted model (Model 9) but this effect was nullified by the introduction of several
structural factors impacting local politics, including level of competition and select religious and
ethnic variables (Model 10). Just as Models 1-8 showed that constituencies with NPP MPs
in the prior term had increased their votes for the NPP, particularly in the Parliamentary race
(+11.4% in Model 8), constituencies with NPP MPs (i.e. Unfriendly Pairs) also increased their
support for the NPP in the runoff election, as compared to constituencies with NDC MPs (i.e.
Friendly Pairs).
5.3.3 2004 Elections
The 2004 elections are the first time we see a shift in the voting pattern (Table 5-4). As
compared to the 2000 elections, votes for the NDC Presidential (-3.7% in Model 14), though
not Parliamentary, race decreased in constituencies which had elected NDC MPs in the prior
term (Unfriendly Pairs). Conversely, votes in the NPP Presidential (+5.7% in Model 18) and
Parliamentary (+7.9% in Model 20) races increased in constituencies which had elected NDC
MPs in 2000 (Friendly Pairs).
With reference to other controls, the structural variables impacting the nature of
the MP-DCE relationship (i.e. Multiple MPs within one district and District Type) were
significant predictors across almost all the restricted models (Models 13, 15, 17, & 19) but
lost significance in the full models (Models 14, 16, 18, & 20). As a constituency’s prior
Parliamentary election became less competitive, votes for the 2004 NDC Presidential and
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Parliamentary candidates decreased. Put differently, increased constituency-level competition in
the 2000 Parliamentary races is correlated with increased votes for the 2004 NDC Presidential
and Parliamentary candidates. As the percentage of agricultural households increased by 10%,
there was a corresponding negative correlation with NDC Presidential votes (-0.91% in Model
14) and a positive correlation with NPP Presidential votes (+0.70% in Model 18).
A 10% increase in Secondary school rates, as compared to primary rates, is correlated with
increased 2004 NDC Presidential votes by 0.78% (Model 14) and decreased NPP Presidential
votes (-1.01% in Model 18). Islam was also a major predictor of votes in 2004. A 10% increase
in the rate of Muslim residents is associated with increased NDC Presidential votes (+1.58%,
Model 14) and NDC Parliamentary votes (+1.86%, Model 16) and decreased NPP Presidential
votes and Parliamentary votes by -1.31% and -1.32%, respectively (Models 18 & 20). Finally,
the most relevant ethnic category is Akan, as a 10% increase in Akan residents correlates with
depreciated NDC Presidential and Parliamentary votes and increased NPP Presidential, though
not Parliamentary, votes.
5.3.4 2008 Elections
In the 2008 Presidential Elections, John Atta Mills (NDC) faced off against Nana Akufo
Addo (NPP). The first round election was very competitive, with both candidates within 3%
of the 50% first-past-the-post mark, forcing a run-off. The NPP had just enjoyed 8 years of
power under President John Kufuor and the NDC was looking to again take the presidency.
In this context, then, it is very curious that the same trends in 2004 continue on into 2008
(Table 5-5). In particular, the Unfriendly Pairs variable is significant across each of the models
and, like 2004, is correlated with depreciated NDC votes and appreciated NPP votes. Those
constituencies which had Unfriendly MP-DCE pairings, meaning they had elected a NDC MP
into office in the prior term, again decreased their NDC Presidential votes (-4.4%, Model
22) and Parliamentary votes (-7.0%, Model 24) as compared to constituencies which had
elected a NPP MP into office in 2004. We would rather expect constituencies which had
both an NPP MP and NPP DCE to decrease their NDC votes in the subsequent election.
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Similarly, constituencies which had elected a NDC MP into office in 2004, increased their NPP
Presidential (+3.7%, Model 26) and Parliamentary votes (+5.3%, Model 28) as compared to
constituencies which had a Friendly Pair (NPP MP + NPP DCE).
For the 2008 elections, District Type was significantly correlated with votes in each of
the models except Model 24. Constituency votes increased for the NDC President by 1.0%
as the type of district in which the constituency was located changed from a District’ to a
Municipality’, and again increased by 1.0% as the district was changed from a Municipality’
to a Metropolis’ (Model 22). Changes in district types were also correlated with decreased
NPP Presidential (-1.4%, Model 26) and Parliamentary (-2.7%, Model 28) votes. For political
competition, a 10% increase in the winner’s share of the vote in the prior Parliamentary
race (i.e. a decrease in the level of political competition), is correlated with decreased
2008 NDC Presidential (-1.39%, Model 22) and Parliamentary (-3.98%, Model 24) votes
and decreased NPP Parliamentary votes (-1.79%, Model 28). In other words, an increased
level of competition in the prior 2004 Parliamentary races is correlated with increased NDC
Presidential, NDC Parliamentary and NPP Parliamentary votes in the 2008 races.
Ethno-Linguistic Diversity is significantly correlated to vote outcomes in Models 22, 24,
and 26. A 0.1 increase in a constituency’s ethno-linguistic diversity measure is associated with
decreased NDC Presidential (-0.11%, Model 22) and Parliamentary (-0.25%, Model 24) votes
and increased NPP Presidential (+0.10%, Model 26), though not Parliamentary votes.
Finally, a 10% increase in the percentage of agric. households in a constituency is
negatively correlated with NDC Parliamentary votes, and positively correlated with NPP
Presidential votes, though this effect was most substantial in the NDC Parliamentary races
(-1.87%, Model 24).
5.3.5 2008 Presidential Runoff Elections
In the party results within the 2008 Presidential Runoff as compared to the 2008 Regular
elections, constituencies with Unfriendly MP-DCE Pairs in 2004-2008 were significantly
correlated with increased NDC votes (+1.7%, Model 30) and decreased NPP votes (-1.2%,
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Model 32), as compared to constituencies with Friendly MP-DCE Pairs. In other words,
constituencies which had elected a NDC MP to office in 2004 increased their NDC votes during
the 2008 Presidential Runoff and decreased their NPP votes. As predicted in Hypothesis 3,
this is reflective of both the NDC and NPP’s attempts to mobilize their respective bases. NDC
areas increased their NDC votes as more voters were mobilized to the cause, while NPP areas
increased their NPP votes. This dynamic is less affected by the nature of the MP-DCE Pair
over the prior 4 years.
Other substantive variables significantly correlated with votes were District Type, Level of
Competition, Linguistic Diversity, and Muslims (%) (Table 5-6).
5.3.6 2012 Elections
The Unfriendly Pair trends established in the 2004 and 2008 Elections are confirmed
in 2012 (Table 5-7). Now, however, constituencies which had elected a NPP MP in 2008
are significantly correlated with increased NDC votes (Presidential: +2.1% (Model 34);
Parliamentary: +7.1% (Model 36)) and decreased NPP votes (Presidential: -2.0% (Model
38); Parliamentary: -2.9% (Model 40)) as compared to the prior 2008 general elections. Like
the 2004 and 2008 elections, the effect of Unfriendly Pairs is stronger for the Parliamentary
races than for the Presidential race. Consistent across the 2004-2012 general elections, then,
constituencies which had an opposing MP and DCE increased their votes for the DCE’s party
significantly more than constituencies which enjoyed a Friendly MP-DCE Pair.
Though constituencies which had voted NPP MPs in office in 2008 increased their NDC
Presidential and Parliamentary votes in 2012, NDC DCEs were apparently less effective within
the 2008 newly-created districts, as NPP Presidential (+1.2%, Model 38) and Parliamentary
(+2.6%, Model 40) votes increased in the 2012 elections as compared to the 2008 races.
A 10% increase in the Parliamentary winner’s share of votes in the 2008 Parliamentary
races is correlated with decreased 2012 NDC Presidential (-0.92%, Model 34) and Parliamentary
votes (-3.38%, Model 36) and decreased NPP Parliamentary votes (-2.06%, Model 40). Put
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differently, increased competition in the prior 2008 Parliamentary races is correlated with
increased NDC Presidential and Parliamentary votes and NPP Parliamentary in 2012.
An increase in the Linguistic Diversity measure is correlated with a significant, though
small, depreciation in NDC Parliamentary (Model 36) and NPP Parliamentary (Model 40)
votes. Finally, increases in the proportion of Muslim residents is correlated with decreased
NDC Presidential and increased NPP Presidential votes, but this variable is not significantly
correlated with either of the Parliamentary races.
5.4 Alternative Explanations
The evidence presented consistently shows that constituencies which had Unfriendly
MP-DCE Pairs were significantly more likely to increase their votes for the DCE’s party, in
both the Presidential and Parliamentary Elections, in the subsequent races. In one sense, this
is a strange result. Why would NPP votes increase in the 2004 and 2008 elections and then
decrease in the 2012 elections in constituencies which had elected NDC MPs in the prior term?
Similarly, why should NDC votes decrease in the 2004 (Presidential only) and 2008 elections
and then increase in the 2012 elections in constituencies which had elected NDC MPs in the
prior term?11 Why do votes for the locally-elected MPs’ party diminish in the next election
when that MP is in an Unfriendly Pair as compared to increased votes for locally-elected MPs’
parties when that MP is in a Friendly Pair? As I have argued, the increased DCE party votes
are due to the effects of local competition engendered by the presence of a MP and DCE of
different political parties, as compared to those districts which had a Friendly MP-DCE pairing
in the prior term. However, it is necessary to address several alternatives to this interpretation
of the regression results.
First, one might argue that constituencies which had voted in an opposition MP
were more likely to have high levels of opposition party votes in both the Presidential and
11 Note that the reverse relationship also holds for constituencies which had elected NPPMPs in the prior term.
170
Parliamentary elections and thus less room to increase support for this party. In other words,
the only direction that the constituency’s level of vote changes could go, in these cases, was
down. Conversely, assuming these constituencies also had low levels of government party
votes, the only direction that the constituency’s level of vote changes could go was up. This
interpretation suggests that the dependent variable is problematic because, though it controls
for changes in party votes, it does not capture party vote starting points.
I highlight a number of points in response to this alternative explanation. First, just
because strongholds have high levels of votes for one particular party does not automatically
mean constituents will increase votes for the opposing party. Second, the vast majority of
Ghana’s constituencies display rather competitive voting patterns. On average, 59.6% of
constituencies in Presidential elections and 74.1% of constituencies in Parliamentary elections
have competitive voting patterns, meaning no party receives more than 65% of the vote
(Tables 5-8 and 5-9). Further, a large portion of party strongholds are located in the Volta and
Ashanti Regions, respectively. Though ideally I would have been able to control for NDC or
NPP votes in each election, this variable correlates too highly with Unfriendly Pairs because
constituencies with high (or low) NDC votes in the 1996 Presidential or Parliamentary election
for example, are less (or more) likely to have voted in an NPP MP (i.e. an Unfriendly Pair).
However, given the territorial concentration of party strongholds, I inserted a dummy variable
for both the Volta and Ashanti Regions within the regressions. If the inability of party votes to
increase in party strongholds really was driving the results, then the inclusion of these regional
dummy variables should have altered the effect of Unfriendly Pairs on party votes. As it were,
the inclusion of these control variables did not substantially effect the significance of Unfriendly
Pairs.
Third, that strongholds already have high levels of voting for one party and can only
decrease their votes for the DCE’s party, in Unfriendly Pairs, does not adequately explain the
systematic pattern of changes in voting results. In the 2004 elections, as compared to the
2000 elections, Unfriendly Pair constituencies increased their NPP votes by 5.7% and 7.9%
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in the Presidential and Parliamentary races, while decreasing their NDC votes by 3.7% in the
Presidential race (Table 5-4). Next, in 2008 (Table 5-5) Unfriendly Pairs further increased
their NPP votes by 3.7% and 5.3% and decreased their NDC votes by 4.4% and 7.0% in the
Presidential and Parliamentary races, despite the NDC winning the Presidential election in
2008. Finally, in 2012 (Table 5-7) Unfriendly Pair constituencies decreased their NPP votes by
2.0% and 2.9% and increased their NDC votes by 2.1% and 7.1% in the respective Presidential
and Parliamentary races. Though ceiling effects might affect votes by a percentage point or
two as it is not the case that the entire voting population of one election carried over to the
next election, ceiling effects cannot explain the systematic vote changes in Unfriendly Pair
constituencies as compared to Friendly Pair constituencies.
A second alternative interpretation of the results is that perhaps what voters really want
is to elect MPs who are of the same political party as the President. As I have argued earlier,
MPs do not receive very much outright development funding and instead have to lobby at
the ministries for their constituency’s inclusion in national development projects. If MPs
belong to the opposition party, however, they may face a harder time gaining access to the
Presidentially-appointed Minister’s ear as compared to MPs of the government’s party. Baldwin
(2013) shows how voters in Zambia pay close attention to the relationship between their local
chiefs and potential Members of Parliament when voting and it is not unreasonable to expect
Ghanaian voters to take into account their MP’s relationship with the President when voting.
Two reasons, however, make it difficult for voters to award or strip the MP of their
title based on his/her belonging to the President’s political party. First, Presidential and
Parliamentary elections are held at the same time in Ghana and, given the overall close
nature of Ghana’s elections in general, voters may have a hard time predicting who will win
the Presidential election. Though constituents have access to the radio and other forms of
media, residents of rural areas are somewhat insulated within their communities and regions
and receive biased news about the state of the nation. For instance, during the course of
my fieldwork, it was not uncommon for residents in NPP areas to explain that they had
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attempted to think about who would win the Presidential election when casting their votes
in the MP election, but that all the information they had received pointed to the (incorrect)
fact that Akufo-Addo (NPP) was going to win the 2012 Presidential election. Similarly, it is
not uncommon to hear constituents back-up their theories of electoral fraud harming their
candidate(s) in past elections by saying something like ‘Everyone knows that no one voted for
[the opposing candidate]’. I have found that these voters’ location and information networks
greatly affect the type of news they receive regarding the generally highly competitive nature of
Ghana’s elections.
Second, while predictions about who is likely to win the Presidency might impact votes
for MP, this mechanism cannot fully explain the outcomes as presented in Tables 5-4 - 5-7,
particularly the switch in voting patterns in the 2012 elections as compared to 2004 and 2008.
First, after John Kufuor (NPP) won the Presidential election in 2000, we could reasonably
expect voters to predict that Kufuor, a popular president with incumbent advantage, would win
his re-election bid in 2004. That constituencies which had voted in NDC MPs in 2000 were
correlated with decreased NDC (Presidential only) and increased NPP votes in 2004, according
to this coattails logic, might not be surprising.
Turning to the 2008 elections (presented in Table 5-5), President Kufuor’s two term
mandate had expired meaning a sitting President was not running in the election. In the battle
for the Presidency, the close election between Akufo-Addo (NPP) and Atta-Mills (NDC) forced
a run-off, which Atta-Mills won. When we look at the 2008 election analysis in Table 5-5,
we see that constituencies which had elected a NDC MP in 2004 decreased their NDC votes
and increased their NPP votes as compared to constituencies which had elected a NPP MP
in 2004. Not only would voters have had a harder time predicting the Presidential winner in
an election without an incumbent candidate, it does not then follow that voters which had
previously elected a NDC MP would be correlated with decreased NDC votes and increased
NPP votes in 2008, as compared to voters which had voted in NPP MPs in 2004. If voters are
making vote choices based on who they think is likely to win the Presidential election, it seems
173
unlikely that voters under NDC MPs would incorrectly predict the future 2008 Presidential
winner as compared to voters under NPP MPs. That voters benefit from the development
works completed by their NPP DCE in 2004, particularly in the context of areas that vote
NDC, is a more plausible explanation.
Finally, after the unexpected death of President Atta Mills in July 2012 barely 4 months
prior to the 2012 elections, no incumbent candidate was again running in the election. Though
it was widely expected that the unpopular Atta Mills’ NDC government was going to be
voted out of power in 2012, the transfer of Presidential authority to the Vice President, John
Mahama, perhaps re-energized the NDC campaign and Mahama narrowly beat Akufo-Addo
(NPP) in the 2012 Presidential elections. As you recall from the 2008 analysis presented in
Table 5-5, constituencies which had Unfriendly Pairs (NDC MP + NPP DCE) were correlated
with decreased NDC votes and increased NPP votes in the subsequent election as compared
to Friendly Pairs (NPP MP + NPP DCE). Now, in 2012 (Table 5-7), constituencies with
Unfriendly Pairs in the prior term (NPP MP + NDC DCE) are correlated with increased NDC
votes and decreased NPP votes in the 2012 elections. With the death of the former President,
and in the context of an, up until then, unpopular NDC government, it would have been
difficult for voters to assume the NDC would again win the Presidency and that they should
thus vote-in a NDC MP. What better explains the correlation of a 2.1% (Pres.) and 7.1%
(Parl.) increase in NDC votes (Table 5-7) in areas with Unfriendly Pairs (NPP MPs + NDC
DCE) is that voters now had a NDC local politician engaging in development works in their
area for the first time since the Rawlings NDC government stepped down in 2000.
5.5 Discussion
Inefficient decentralization systems, where locally-elected politicians’ independence and
authority have been hindered as a result of the severe under-funding of local governments
by central state coffers, have often stifled the extent to which democratic progress has been
made in new democracies. The argument made in this dissertation, that the centralized system
of local government in Ghana, where elected MPs exist alongside centrally-appointed (and
174
well-funded) DCEs, increases political competition at the local level, shows how a theoretically
less democratic institutional framework actually stimulated democratic progress in this case. As
the election of MPs concurs with the central-appointment of DCEs, the political competition
generated when these two officials are of opposing political parties has contributed to deepened
democratic governance and a lessening of neopatrimonial political logics and ethnic voting in
Ghana.
175
Table 5-1. Constituencies under analysis
Year Total constituencies 3rdparty/independentMPs (#)
N
1996 200 constituencies 5 1952000 200 constituencies 5 1952004 230 constituencies 10 2202008 230 constituencies 8 221*2012 275 constituencies 7 267**Note: The 2008 Parliamentary Elections were postponed in Akwatia constituency and isthus an additional constituency missing from the analysis.
176
Table 5-2. Changes in party votes: 2000 - 1996
NDC Pres1 NDC Parl NPP Pres NPP Parl
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Unfriendly96 -0.040∗∗∗ -0.052∗∗∗ -0.068∗∗∗ -0.087∗∗∗ -0.005 0.030∗∗∗ 0.054∗∗∗ 0.114∗∗∗
(0.007) (0.009) (0.013) (0.017) (0.008) (0.008) (0.015) (0.023)Mult.MPs 0.023∗∗ 0.029∗∗ 0.001 0.003 -0.028∗∗∗ -0.017∗ 0.004 0.006
(0.010) (0.011) (0.021) (0.022) (0.011) (0.009) (0.019) (0.017)District -0.001 -0.002 0.007 -0.005 0.012∗∗ -0.004 0.013 -0.007Type (0.005) (0.007) (0.011) (0.014) (0.006) (0.006) (0.010) (0.012)parl96winner -0.069∗ -0.426∗∗∗ 0.013 -0.079
(0.041) (0.087) (0.029) (0.077)Volta 0.043 0.056
(0.028) (0.075)Ashanti 0.004 -0.007
(0.009) (0.022)Ling. Div. -0.006 -0.009 0.017∗∗∗ 0.006
(0.005) (0.012) (0.004) (0.013)Agric rate -0.051∗ -0.008 0.045 0.030
(0.028) (0.063) (0.033) (0.058)Secondary -0.163∗ -0.187 0.198∗∗ 0.481∗∗∗
(0.085) (0.165) (0.078) (0.151)Post Sec -0.037 -0.086 0.054 0.060
(0.114) (0.215) (0.123) (0.273)Muslims 0.040 -0.102 -0.082∗ 0.130
(0.061) (0.122) (0.044) (0.093)No Relig 0.047 -0.123 0.158 0.650
(0.203) (0.600) (0.173) (0.419)Trad -0.071 -0.217 -0.040 0.169
(0.117) (0.213) (0.074) (0.134)other -0.487 -0.319 -1.003 -0.770
(1.361) (1.976) (1.096) (2.491)
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.011Incumbent President in 1996.
177
Table 5-2. Continued
NDC Pres1 NDC Parl NPP Pres NPP Parl
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Akan 0.039 -0.043 -0.029 0.012(0.027) (0.063) (0.033) (0.049)
Ewe 0.103∗∗ 0.055 -0.109∗∗∗ -0.104∗
(0.046) (0.111) (0.032) (0.054)Guan 0.096∗ 0.037 -0.086∗∗ 0.043
(0.052) (0.110) (0.043) (0.137)Gurma -0.032 -0.094 -0.003 -0.025
(0.072) (0.139) (0.042) (0.101)MoleDagbani
-0.027 0.025 -0.022 0.021
(0.048) (0.092) (0.036) (0.076)Grusi 0.084 -0.017 -0.024 0.042
(0.086) (0.102) (0.071) (0.118)Mande 0.294 -0.115 0.438∗ 0.613
(0.354) (0.524) (0.256) (0.706)others -0.379 1.112 -0.546 0.140
(0.652) (1.276) (0.513) (1.541)Non-Ghanaians 0.012 -0.366 0.185 -0.234
(0.455) (1.008) (0.337) (1.313)Constant -0.102∗∗∗ 0.034 -0.076∗∗∗ 0.380∗∗ 0.069∗∗∗ -0.061 0.034∗ -0.252
(0.008) (0.096) (0.015) (0.178) (0.009) (0.088) (0.018) (0.159)Obs. 195 195 195 195 195 195 195 195Adj. R2 0.106 0.271 0.072 0.175 0.028 0.467 0.036 0.177Res. Std.Error
0.059 0.053 0.108 0.102 0.062 0.046 0.109 0.100
(df) (191) (172) (191) (172) (191) (172) (191) (172)Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.011Incumbent President in 1996.
178
Table 5-3. Changes in party votes: 2000 Pres. Runoff - 2000 Pres. ElectionNDC Pres Runoff NPP Pres Runoff
Model 9 Model 10 Model 11 Model 12Unfriendly96 0.014∗∗∗ -0.003 0.053∗∗∗ 0.031∗∗∗
(0.004) (0.004) (0.009) (0.010)Multiple MPs 0.010∗ -0.003 -0.002 -0.013
(0.006) (0.005) (0.013) (0.012)District Type -0.006∗ -0.005 -0.006 0.008
(0.004) (0.003) (0.006) (0.006)parl96winner 0.038∗∗∗ -0.071∗
(0.015) (0.041)Volta 0.020
(0.013)Ashanti -0.009
(0.008)Ling Div. 0.004 -0.016∗∗
(0.003) (0.007)Agric rate -0.026∗ 0.014
(0.014) (0.027)Secondary -0.044 -0.042
(0.044) (0.078)Post Sec 0.021 -0.019
(0.057) (0.122)Muslims 0.004 0.007
(0.024) (0.062)No Relig -0.067 -0.462∗∗
(0.093) (0.186)Trad 0.109∗∗ 0.195∗
(0.052) (0.103)Other 0.268 2.113
(0.557) (1.417)
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Table 5-3. ContinuedNDC Pres Runoff NPP Pres Runoff
Model 9 Model 10 Model 11 Model 12Akan 0.010 -0.014
(0.014) (0.030)Ewe 0.038∗ -0.104∗∗∗
(0.021) (0.031)Guan -0.005 -0.045
(0.024) (0.051)Gurma -0.005 -0.034
(0.025) (0.072)Mole Dagbani 0.043∗ 0.039
(0.023) (0.058)Grusi -0.029 0.151
(0.026) (0.157)Mande 0.320 -1.038∗∗∗
(0.200) (0.390)Others 0.566 1.243
(0.348) (0.823)Non-Ghanaians -0.341 -0.476
(0.272) (0.570)Constant -0.023∗∗∗ -0.030 0.073∗∗∗ 0.188∗∗
(0.005) (0.037) (0.008) (0.073)Observations 195 195 195 195Adjusted R2 0.050 0.565 0.077 0.549Residual Std. Error 0.034 0.023 0.082 0.057(degrees of freedom) (191) (172) (191) (172)Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
180
Table 5-4. Changes in party votes: 2004 - 2000 (reg. election)
NDC Pres NDC Parl NPP Pres1 NPP Parl
Model 13 Model 14 Model 15 Model 16 Model 17 Model 18 Model 19 Model 20
Unfriendly00 -0.021∗∗ -0.037∗∗∗ 0.0001 -0.021 0.069∗∗∗ 0.057∗∗∗ 0.099∗∗∗ 0.079∗∗∗
(0.009) (0.009) (0.015) (0.018) (0.009) (0.009) (0.013) (0.015)Mult.MPs 0.039∗∗∗ 0.004 0.053∗∗∗ 0.021 -0.028∗∗∗ 0.006 -0.017 0.015
(0.009) (0.011) (0.015) (0.018) (0.009) (0.011) (0.014) (0.014)District 0.023∗∗∗ -0.002 0.030∗∗∗ -0.014 -0.019∗∗∗ 0.004 -0.024∗∗∗ 0.006Type (0.008) (0.008) (0.011) (0.014) (0.006) (0.007) (0.009) (0.010)New AA04 0.004 0.004 -0.013 -0.019
(0.010) (0.018) (0.009) (0.015)parl00winner -0.098∗∗∗ -0.273∗∗∗ 0.012 -0.027
(0.035) (0.078) (0.036) (0.073)Volta 0.060∗∗∗ 0.054
(0.022) (0.056)Ashanti -0.005 0.021
(0.011) (0.020)Ling Div 0.0004 0.013 -0.005 0.006
(0.005) (0.010) (0.006) (0.009)Agric rate -0.091∗∗∗ -0.035 0.070∗∗ 0.026
(0.032) (0.055) (0.031) (0.035)Secondary 0.078∗ 0.110 -0.101∗∗ -0.114∗
(0.045) (0.094) (0.044) (0.065)Post Sec 0.075 0.346 -0.114 -0.492∗∗∗
(0.195) (0.314) (0.169) (0.182)Muslims 0.158∗∗∗ 0.186∗∗∗ -0.131∗∗∗ -0.132∗
(0.039) (0.055) (0.045) (0.067)No Relig 0.392∗∗ 0.357 -0.540∗∗∗ -0.802∗∗∗
(0.180) (0.373) (0.174) (0.260)Trad -0.089 -0.082 0.237∗∗ 0.204
(0.072) (0.126) (0.098) (0.140)other -1.028 -2.935 -0.653 -3.597∗
(0.971) (2.239) (1.221) (2.037)1Incumbent President in 2000.
181
Table 5-4. Continued
NDC Pres NDC Parl NPP Pres1 NPP Parl
Model 13 Model 14 Model 15 Model 16 Model 17 Model 18 Model 19 Model 20
Akan -0.107∗∗∗ -0.169∗∗∗ 0.094∗∗∗ 0.056(0.029) (0.042) (0.033) (0.045)
Ewe -0.057 -0.088 -0.035 0.008(0.043) (0.087) (0.038) (0.063)
Guan -0.108∗∗∗ -0.166∗ 0.091∗ 0.097(0.039) (0.089) (0.047) (0.091)
Gurma -0.064 -0.104 -0.006 -0.0001(0.052) (0.075) (0.069) (0.098)
MoleDagbani
0.045 -0.081 -0.022 -0.050
(0.040) (0.066) (0.049) (0.067)Grusi -0.012 -0.150 -0.072 -0.023
(0.069) (0.131) (0.071) (0.134)Mande 0.715∗∗∗ 0.830∗ -1.088∗∗∗ -1.465∗∗
(0.275) (0.445) (0.322) (0.589)others -1.881∗∗∗ -2.896∗∗ 2.299∗∗∗ 2.211∗
(0.583) (1.159) (0.676) (1.265)Non-Ghanaians 0.129 0.227 -0.458 -1.761∗∗
(0.458) (1.055) (0.585) (0.893)Constant -0.042∗∗∗ 0.116∗∗ -0.077∗∗∗ 0.209∗∗ 0.055∗∗∗ 0.026 0.039∗∗∗ 0.153∗∗
(0.011) (0.046) (0.015) (0.083) (0.009) (0.047) (0.014) (0.063)Obs 220 220 220 220 220 220 220 220Adj R2 0.180 0.538 0.095 0.262 0.319 0.563 0.271 0.377Res StdError
0.064 0.048 0.105 0.095 0.063 0.050 0.092 0.085
(df) (216) (196) (216) (196) (216) (196) (216) (196)
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.011Incumbent President in 2000.
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Table 5-5. Changes in party votes: 2008 - 2004
NDC Pres NDC Parl NPP Pres1 NPP Parl
Model 21 Model 22 Model 23 Model 24 Model 25 Model 26 Model 27 Model 28
Unfriendly04 -0.056∗∗∗ -0.044∗∗∗ -0.051∗∗∗ -0.070∗∗∗ 0.059∗∗∗ 0.037∗∗∗ 0.070∗∗∗ 0.053∗∗∗
(0.007) (0.008) (0.013) (0.015) (0.008) (0.008) (0.013) (0.014)District Type 0.017∗∗∗ 0.010∗∗ 0.023∗∗∗ 0.004 -0.021∗∗∗ -0.014∗∗∗ -0.013∗ -0.027∗∗∗
(0.004) (0.005) (0.008) (0.010) (0.004) (0.005) (0.007) (0.010)NewDist.04 -0.009 -0.006 -0.013 -0.005 0.010 0.009 0.018 0.021
(0.007) (0.007) (0.018) (0.015) (0.008) (0.008) (0.013) (0.015)New AA08 0.002 -0.009 0.007 0.003
(0.006) (0.014) (0.007) (0.015)Parl04Winner -0.139∗∗∗ -0.398∗∗∗ 0.036 -0.179∗∗
(0.025) (0.061) (0.029) (0.074)Volta -0.023 0.021
(0.024) (0.048)Ashanti 0.038∗∗∗ 0.007
(0.008) (0.023)Ling Div -0.011∗∗ -0.025∗∗∗ 0.010∗∗ 0.004
(0.005) (0.008) (0.005) (0.009)Agric rate -0.059∗∗ -0.187∗∗∗ 0.109∗∗∗ 0.072
(0.023) (0.051) (0.027) (0.048)Secondary -0.150∗∗ -0.181∗ 0.179∗∗∗ 0.265∗∗
(0.062) (0.099) (0.062) (0.125)Post Sec -0.175∗∗ -0.451∗∗∗ 0.312∗∗∗ 0.496∗∗∗
(0.086) (0.171) (0.094) (0.192)Muslims -0.037 -0.092 0.036 0.081
(0.047) (0.080) (0.049) (0.074)No Relig -0.321∗∗∗ 0.047 0.326∗∗ 0.861∗∗∗
(0.122) (0.277) (0.129) (0.287)Trad -0.146∗ -0.332∗∗ 0.170∗ 0.231
(0.083) (0.136) (0.091) (0.146)Other 2.209∗ -1.543 -2.084∗∗ -5.207∗∗∗
(1.194) (1.954) (1.050) (1.949)1Incumbent President in 2004.
183
Table 5-5. Continued
NDC Pres NDC Parl NPP Pres1 NPP Parl
Model 21 Model 22 Model 23 Model 24 Model 25 Model 26 Model 27 Model 28
Akan 0.033∗ -0.011 -0.061∗∗∗ -0.100∗∗
(0.018) (0.038) (0.022) (0.047)Ewe 0.052 0.122∗ -0.020 -0.061
(0.034) (0.074) (0.024) (0.068)Guan -0.005 0.039 -0.029 -0.012
(0.046) (0.068) (0.040) (0.077)Gurma -0.048 -0.080 0.026 -0.068
(0.052) (0.089) (0.055) (0.084)MoleDagbani
-0.041 0.012 0.058 0.011
(0.037) (0.065) (0.041) (0.075)Grusi -0.050 -0.054 0.018 0.011
(0.063) (0.129) (0.061) (0.099)Mande -0.111 0.454 -0.322 0.222
(0.188) (0.317) (0.236) (0.418)Others -0.616 -1.197 1.532∗∗∗ 1.202
(0.507) (0.749) (0.568) (0.936)Non-Ghanaians 0.556 1.161 -0.659 -0.833
(0.430) (0.750) (0.407) (0.748)Constant 0.029∗∗∗ 0.255∗∗∗ 0.017 0.573∗∗∗ -0.026∗∗∗ -0.243∗∗∗ -0.033∗∗ -0.089
(0.007) (0.050) (0.015) (0.107) (0.008) (0.055) (0.015) (0.110)
Obs 221 221 221 221 221 221 221 221Adj R2 0.298 0.523 0.084 0.341 0.274 0.603 0.130 0.245Res StdError
0.047 0.039 0.095 0.080 0.054 0.040 0.093 0.086
(df) (217) (197) (217) (197) (217) (197) (217) (197)
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.011Incumbent President in 2004.
184
Table 5-6. Changes in party votes: 2008 Pres. Runoff - 2008 Pres. Election
NDC Pres NPP Pres
Model 29 Model 30 Model 31 Model 32
Unfriendly04 0.029∗∗∗ 0.017∗∗∗ -0.016∗∗∗ -0.012∗∗
(0.006) (0.006) (0.006) (0.006)District Type -0.001 0.010∗∗∗ -0.003 -0.005∗∗∗
(0.003) (0.003) (0.003) (0.002)New District04 -0.009 -0.003 0.006 0.005
(0.006) (0.005) (0.006) (0.004)New AA08 0.0005 0.003
(0.004) (0.003)Parl 04 Winner -0.079∗∗∗ -0.001
(0.019) (0.019)Volta 0.001
(0.014)Ashanti 0.019∗∗∗
(0.004)Ling Div -0.004∗ 0.00002
(0.002) (0.001)Agric rate 0.005 -0.018
(0.015) (0.018)Secondary -0.128∗∗ 0.020
(0.051) (0.049)Post Sec -0.041 -0.052
(0.048) (0.054)Muslims -0.103∗∗∗ 0.052∗∗∗
(0.020) (0.019)No Relig -0.156∗ -0.055
(0.088) (0.064)Trad 0.056 0.043
(0.070) (0.038)Other 0.084 1.164∗∗
(0.844) (0.584)
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Table 5-6. Continued
NDC Pres NPP Pres
Model 29 Model 30 Model 31 Model 32
Akan 0.022 0.007(0.015) (0.015)
Ewe 0.001 0.016(0.021) (0.011)
Guan 0.018 -0.020(0.025) (0.019)
Gurma -0.087∗∗ 0.023(0.040) (0.024)
Mole Dagbani 0.040∗ -0.008(0.022) (0.018)
Grusi 0.016 0.006(0.044) (0.030)
Mande -0.054 -0.239∗∗
(0.106) (0.108)Others 0.614∗∗ -0.090
(0.288) (0.310)Non-Ghanaians -0.204 -0.052
(0.234) (0.209)Constant 0.022∗∗∗ 0.139∗∗∗ 0.008 -0.008
(0.007) (0.044) (0.007) (0.039)Obs 221 221 221 221Adj R2 0.096 0.385 0.046 0.089Res Std Error 0.043 0.035 0.033 0.032(df) (217) (197) (217) (197)
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 5-7. Changes in party votes: 2012 - 2008 (reg. election)
NDC Pres1 NDC Parl NPP Pres NPP Parl
Model 33 Model 34 Model 35 Model 36 Model 37 Model 38 Model 39 Model 40
Unfriendly08 0.015∗∗ 0.021∗∗∗ 0.063∗∗∗ 0.071∗∗∗ -0.019∗∗∗ -0.020∗∗∗ -0.025∗∗∗ -0.029∗∗
(0.007) (0.008) (0.013) (0.014) (0.007) (0.007) (0.007) (0.012)District -0.012∗∗ -0.004 -0.024∗∗∗ 0.003 0.009∗∗ -0.001 0.001 -0.009Type (0.005) (0.007) (0.009) (0.015) (0.005) (0.007) (0.005) (0.011)NewDis.08 -0.017∗∗ -0.009 0.003 0.026 0.020∗∗∗ 0.012∗ 0.024∗∗∗ 0.026∗
(0.007) (0.007) (0.014) (0.016) (0.007) (0.007) (0.007) (0.013)New AA12 0.003 0.007 -0.002 -0.003
(0.007) (0.012) (0.007) (0.010)parl08winner -0.092∗∗∗ -0.338∗∗∗ 0.031 -0.206∗∗∗
(0.030) (0.067) (0.042) (0.061)Volta 0.041∗ 0.058
(0.021) (0.059)Ashanti -0.015 0.040∗∗
(0.017) (0.019)Ling Div -0.001 -0.025∗∗ -0.003 -0.014∗
(0.005) (0.011) (0.004) (0.008)Agric rate -0.0002 -0.010 -0.034 0.002
(0.024) (0.051) (0.026) (0.044)Secondary -0.022 0.018 0.009 0.064
(0.067) (0.128) (0.062) (0.106)Post sec 0.009 -0.068 -0.039 0.198
(0.085) (0.164) (0.092) (0.125)Muslims -0.089∗∗ -0.057 0.078∗ 0.069
(0.035) (0.073) (0.046) (0.076)No relig 0.083 0.560∗ -0.085 0.157
(0.164) (0.313) (0.167) (0.235)Trad -0.005 -0.019 0.001 0.029
(0.059) (0.123) (0.075) (0.135)Other -1.624 -0.412 1.935∗ 3.290
(1.061) (1.979) (1.135) (2.135)1Incumbent President in 2008.
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Table 5-7. Continued
NDC Pres1 NDC Parl NPP Pres NPP Parl
Model 33 Model 34 Model 35 Model 36 Model 37 Model 38 Model 39 Model 40
Akan 0.016 0.024 -0.006 -0.038(0.025) (0.048) (0.026) (0.052)
Ewe -0.011 0.057 -0.018 -0.045(0.035) (0.085) (0.026) (0.058)
Guan 0.056 0.230∗∗∗ -0.049 0.016(0.048) (0.078) (0.045) (0.067)
Gurma 0.005 0.127 0.005 -0.024(0.035) (0.090) (0.049) (0.076)
MoleDagbani
0.076∗∗ 0.047 -0.052 -0.031
(0.031) (0.058) (0.036) (0.071)Grusi 0.229∗∗∗ 0.231∗∗ -0.145∗∗ -0.105
(0.049) (0.110) (0.063) (0.094)Mande 0.177 1.036∗∗∗ -0.165 -0.198
(0.229) (0.369) (0.251) (0.478)Others 0.456 -0.460 -0.182 -0.742
(0.568) (0.851) (0.636) (1.151)non-Ghanaians -0.215 0.202 -0.180 1.004
(0.375) (0.968) (0.386) (0.750)Constant 0.053∗∗∗ 0.091∗ 0.035∗∗ 0.149 -0.035∗∗∗ 0.001 -0.009 0.071
(0.007) (0.054) (0.015) (0.113) (0.008) (0.050) (0.008) (0.094)Obs 267 267 267 267 267 267 267 267Adj R2 0.065 0.213 0.088 0.211 0.072 0.123 0.033 0.056Res StdError
0.058 0.053 0.102 0.095 0.057 0.055 0.083 0.082
(df) (263) (243) (263) (243) (263) (243) (263) (243)
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.011Incumbent President in 2008.
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Table 5-8. Number of constituency-level political party strongholds (over 65% of the vote)
1996 2000 2004 2008 2012Pres. Parl. Pres. Parl. Pres. Parl. Pres. Parl. Pres. Parl.
NDC 76 55 41 22 39 27 36 26 65 30VoltaRegion
19 15 19 13 21 14 18 16 22 19
NPP 18 15 40 28 58 39 39 25 43 35AshantiRegion
16 14 24 22 33 26 29 21 34 29
Totalconstit.
200 200 200 200 230 230 229* 229* 275 275
*Note: 2008 Elections were postponed in the Akwatia constituency and are not included
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Table 5-9. Competitive and uncompetitive constituencies
1996 2000 2004 2008 2012Pres. Parl. Pres. Parl. Pres. Parl. Pres. Parl. Pres. Parl.
Comp. 106, 130, 119, 160, 133, 164, 154, 178, 167, 210,% (53%) (65%) (59.5%) (80%) (57.8%) (71.3%) (67.2%) (77.7%) (60.7%) (76.4%)
Uncomp. 94, 70, 81, 40, 97, 66, 75, 51, 108, 65,% 47% 35% 40.5% 20% 42.2% 28.7% 32.5% 22.3% 39.3% 23.6%
Totalconstit.
200 200 200 200 230 230 229* 229* 275 275
*Note: 2008 Elections were postponed in the Akwatia constituency and are not included
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CHAPTER 6SURVEY ANALYSIS OF INDIVIDUALS’ VOTES
Thus far I have traced how the development of Ghana’s centralized system of government
was created with the ethnic configuration of Ghanaian society in mind. The guiding principle,
historically used to justify authoritarian control in Africa, is that centralized control is necessary
to combat the influence of chiefs and ethnic leaders on segmented populations which is
detrimental to national unity. As I argue in Chapters 4 and 5, the particular way in which
the system of centralization was implemented in Ghana’s Fourth Republic contributes to a
depreciation of neo-patrimonial politics and ethnic voting. Put simply, the implementation of
political competition in sub-national districts across Ghana has increased the number of viable
candidate or party options available to Ghanaians in making their vote choices.
I have discussed the ways in which sub-national political competition has increased the
vote opportunities for Ghanaians, but I have not yet tested for the factors which contribute
to individual-level vote decisions. Though the politicization of ethnicity in Ghana is certainly
acknowledged by scholars, studies completed mid-way through the Fourth Republic emphasize
that ideological voting has just as big an impact as ethnic voting in Ghana’s Fourth Republic
(Fridy 2007a; Whitfield 2009). While sometimes explained as an information problem
constraining local voters and resulting in the appearance of ethnic voting (Lindberg and
Morrison 2005; 2008), more recent explanations emphasize that voters have become more
mature democratic citizens over time and now engage in retrospective or prospective voting
(Weghorst and Lindberg 2011; Hoffman and Long 2013). Further, Weghorst and Lindberg
(2011) find that clientelistic inducements are losing their effect in Ghana as voters are now
equipped with retrospective information about both political parties and apply that knowledge
in their voting decisions. Finally, while survey and exit poll evidence points to critical voting
rationales by Ghanaian voters, it is also important to consider that respondents would be
unlikely to admit that ethnicity or clientelistic inducements impacted their votes.
In my analysis I consider three core hypotheses about Ghanaian voting behavior:
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1) Identity-Based Voting: Ethno-linguistic, tribal, hometown, and/or religious identitiesimpact individuals’ votes.
– Identity-Based Voting refers to ethnic, religious and/or particularistic influenceswhich might impact someone’s vote. Ethnic and Religious categories are the sameas those used by Ghana Statistical Services (GSS) in capturing the 2010 census.Particularistic influences are conceptualized as factors related to hometown (e.g.how likely would you be to vote for an MP who was not born in this constituency?)or family influences (e.g. Do members of your immediate family support the samepolitical party as yourself?).
2) Policy-Based or Economic-Based Voting: Political platforms, candidate performance, andperceptions about the state of the economy impact individuals’ votes.
– Policy-Based Voting is conceptualized as votes affected by social and economicpolicies and/or political party ideologies. Social and economic policies encompassboth voters’ prospective beliefs and retrospective judgments about candidateperformance. Distinct from economic policies, economic-based voting refers to theimpact of past and present perceptions about the state of the economy, or futurepredictions about Ghana’s economic well-being, on individuals’ vote decisions.
3) Clientelistic-Based Voting: Individual-level inducements affect individuals’ votes.
– Clientelistic influences on vote decisions are strictly defined as ‘payouts’ or giftsprovided by the political party, candidate, or ‘party boys’ to an individual orindividual’s family in trade for an individual’s vote. Community-level development‘gifts’, such as the building of a water bore-hole, are not included within thiscategory.
Throughout the district-level analysis (Chapters 6-8), I find evidence supporting all three
hypotheses.Yet different analytic tools emphasize different factors. First, the qualitative
explanation of district-level politics emphasized Identity-Based Voting (Hypothesis 1),
albeit limited to local-level identities, Policy or Economic Based Voting (Hypothesis 2),
and Clientelistic-Based Voting (Hypothesis 3), the last of which was heightened in the
competitive districts. Within the survey data, respondents emphasized Policy-Based or
Economic-Based Voting rationales when explaining their reason for voting for President or
MP, or community-members’ top reason for voting for President. Identity-Based factors, and
particularly national-level cleavages, became relevant, while Policy and Economic-Based factors
remained important, when respondents were asked about party ideologies. Further, models
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predicting respondents’ votes also found respondent tribe/ethnic group significantly predicted
vote decisions though, the strength of the ethnic variables waxed and waned for different
groups over time. Finally, as Chapters 7 and 8 will show, respondents do not readily admit
to ethnic or clientelistic impacts on their votes and instead support for these hypotheses is
gathered from indirect questions and list experiments.
6.1 General Conclusions from Chapter 6
In this chapter I first introduce the 3 district pairs (6 districts in total) in which surveys
were collected. Within the district pairs, the districts are demographically similar NPP
strongholds, NDC strongholds, and competitive districts. Though similar in terms of party
strongholds or competitive districts, the voting patterns within district pairs still differ in some
significant way. In the analysis that follows, I first rely largely on interview data to provide
a qualitative explanation of district-level politics and what local factors drive citizen votes. I
then turn to my survey data, analyzing general political behavior via direct survey questions
about political and economic values and vote behavior. First I consider questions where
respondents report reasons for their votes for (1) President and (2) MP as well as (3) their
perception about the top reason for vote decisions within their community. Second, I consider
respondents’ ideological knowledge about the political parties. I ask respondents whether
the party ideologies are different from one another (4) and to identify components of the (5)
NDC’s ideology and the (6) NPP’s ideology.
From the qualitative analysis, identity-based voting (Hypothesis 1) features prominently
in the political explanation in the NPP and NDC strongholds, though not the competitive
districts. However, the identity political cleavages that are galvanized are based on local-level
identities (i.e. tribes, towns, district zones, etc.) rather than historically prominent ethno-linguistic
cleavages. In the competitive districts, however, the absence of a single dominant ethno-political
tradition (i.e. the Fantes are neither exclusively tied to the NDC or NPP) meant politics were
less overtly motivated by identity cleavages and rather featured through the political parties
in terms of citizen approval of campaign promises or perceived government effectiveness
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(Hypothesis 2). Still, local-level identities do play into political party support in these
competitive districts as it is not uncommon to find chiefs publicly aligned with particular
political party traditions.1 Further, there is some suggestion that the degree of Fantes chiefs’
proximity to the Asantehene is related to an increased likelihood of supporting the NPP on the
part of themselves and members of their community.
Turning to the survey data, I generally find support for Hypothesis 2: Policy or Economic-Based
Voting when respondents explain their or their community members’ votes. However,
this portion of the analysis is based on self-report data, which is not likely to pick up on
Identity-Based Voting (Hypothesis 1)2 or Clientelistic-Based Voting (Hypothesis 3).
When explaining the components of the NDC and NPP ideologies, however, support for
Hypothesis 1 increased as respondents were more willing to identify prominent ethnic groups or
religious groups with party ideologies.3 Support for Hypothesis 2: Policy or Economic-Voting
was again high in the political ideology responses, though different districts cited different
versions of a party’s economic and policy ideologies. Finally, there was no evidence of
clientelistic gifts as central to a political party’s ideology.
In the next chapter I use respondents’ self-report voting history (7) to predict votes for
the 2004-2012 Presidential and Parliamentary races using standard demographic variables as
well as variables related to the three core hypotheses. I also analyze swing voting patterns and
use logistic regressions to predict swing voters. Finally, in Chapter 8 I use three different survey
1 In the NPP and NDC strongholds in which I worked, it would be frowned upon to havechiefs come out publicly in favor of one party or another.
2 Support for Hypothesis 1 was low when respondents explained their votes, thoughrespondents in Adaklu Anyigbe and Ketu South, the NDC strongholds, tended to citeparticularistic/ethnic reasons at greater rates than respondents from other districts.
3 Respondents from the NDC strongholds again cited ethnic or religious groups with partyideologies at a greater rate than other districts, though Birim South ranked second in theproportion of respondents who identified Ewes/Muslims/Northerners with the NDC ideology.
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experiments to test for the impact of tribal bias (8), religious bias (9), and clientelistic gifts
(10-11) on vote decisions.
6.2 The Survey
The data analyzed in Chapters 6 through 8 comes from an original survey (N=1,932)
collected in October-December 2013. The survey sample consisted of six purposefully-selected
districts in the southern half of Ghana, whereby three sets of pairs were selected using Mill’s
method of difference (i.e. similar demographic/structural characteristics but differing voting
patterns between pairs) (Lijphart 1971). First, district pairs were selected controlling for similar
demographic and ethnic characteristics and differing levels of electoral competition. One pair
are NPP strongholds with majority Asante/Akyem populations (Bosome Freho and Birim
South); the second pair are NDC strongholds with majority Ewe populations (Adaklu Anyigbe
and Ketu South); and the third pair are electorally competitive districts with majority Fante
populations (Mfantsiman and Asikuma Odoben Brakwa (AOB)).4
Second, the six districts were chosen with an emphasis on variation in voting patterns,
despite their dominant party and structural similarities. In particular, why did one district in
each of the NPP and NDC strongholds elect or narrowly elect an Independent MP while the
4 The unit of analysis for the surveys is the district in order for the analysis to correspondto the 2010 Ghana Census. As discussed in previous chapters, districts are the site ofadministrative local government bodies while constituencies, which either correspond to districtboundaries or fit within districts, are the local-level electoral units. DCEs, for example, governat the district-level while MPs are elected at the constituency-level. Out of the six districtsin the sample, only Mfantsiman had two constituencies within its district boundaries as of2008. Also relevant, Birim South, Adaklu Anyigbe, and Mfantsiman Districts were split intotwo districts in 2012. Because Birim South and Adaklu Anyigbe both existed as a singledistrict and constituency prior to 2012, surveys were conducted according to the 2008 BirimSouth and Adaklu Anyigbe district boundaries. As for Mfantsiman, a clerical error meantsurveys were only collected in the 2008 Mfantsiman West constituency (now MfantsimanDistrict), rather than for the entire 2008 Mfantsiman District. Though census information isgeneralized to the entire 2010 Mfantsiman District, surveys were only conducted in MfantsimanWest constituency rather than Mfantsiman West constituency and Mfantsiman East/Ekumficonstituency.
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member of the pair never swayed from the dominant party? Similarly, given the demographic
similarities, why does one of the districts in the competitive district pair favor the NDC while
the other favors the NPP?
Third, when collecting surveys, a significant effort was made to generate a randomly-selected
representative sample from each district.5 For this purpose the survey team employed Ghana
Statistical Services (GSS) to randomly select 8 enumeration areas (EAs), 4 urban and 4 rural,
within each district.6 Enumeration Areas are the most basic unit of organization (i.e. the
lowest unit above the individual-level) when collecting the census. The average population of
an enumeration area in our sample was 553 residents.7
5 Though random selection procedures were used within each district, it is useful toverify whether the respondents’ demographic characteristics matched those of the districtat-large. Table 6-1 presents comparisons of demographic data collected from the survey andthe census in each district. Overall the survey samples matched the average age, genderdistribution, and ethnic group population percentages very closely. Some areas of concern,however, include the under-sampling of female respondents in Ketu South and general, thoughmoderate, over-sampling of those with higher levels of education across the districts. Finally,significantly greater portions of the survey respondents own cell phones and use the internetthan is reported in the census. However, I point out that the increasingly digitally-connectednature of Ghana’s population likely accounts for some of the differences between the censuscounts of Census Night, September 26, 2010, and the survey collected three years later inOctober-December 2013. Overall, the respondent demographics appear to generally match thecensus demographics.
6 Bosome Freho is a 100% rural district meaning no urban enumeration areas exist.Remember, the 2010 Ghana census classifies any enumeration area with a populationgreater than 5,000 as automatically urban. By necessity, surveys were only collected in ruralenumeration areas in Bosome Freho.
7 The goal was to collect 40 surveys within each Enumeration Area. When the survey teamarrived at the field, we utilized maps to walk the boundary of the entire EA and then surveyenumerators were staggered at different starting points around the boundary. In dense urbanareas we always stuck to the EA boundaries. In rural areas we sometimes found it difficultto randomly select respondents in low-population EAs. When the EA encompassed an entirevillage, we often split the surveys between the selected EA and a neighboring village (i.e.another EA). Still only 40 surveys were distributed in any given site (EA + a neighboringvillage, where applicable).
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6.3 The District Pairs
6.3.1 NPP Strongholds: Bosome Freho & Birim South
Though the dominant tribal population in Bosome Freho and Birim South are different,
both districts’ respective Asante and Akyem groups are strongly associated with the NPP.
Bosome Freho and Birim South are relatively comparable in the presence of a core NPP tribe
in the district, in terms of English literacy rates (48.3% vs. 61.5%) and the percentage of the
population engaged in agriculture (81.6% vs. 78.2%). Bosome Freho is more rural8 , however,
and has fewer cell phone owners and internet users as compared to Birim South (Table 6-2).
Electorally speaking (see Volatility Rates in Table 6-3), both of these areas have voted
for the NPP Presidential candidate with consistency, though the NPP receives between
7-11% fewer votes in Birim South than Bosome Freho. Both districts are relatively stable
in their Presidential voting patterns. In Parliamentary elections, however, Birim South
votes have been very consistent while those in Bosome Freho fluctuated greatly after an
NPP-turned-Independent candidate was elected in 2008 (Table 6-4). Between these two NPP
In order to ensure the random selection of households in each EA, survey enumerators useda ‘daycode’ method whereby the day of the month determined the number of residencesseparating survey respondents. If the day was a double-digit number, the two numbers wereadded together. So, October 13th meant 4 residences separated each respondent, makingsure to count residences on both sides of the path/road. To select a respondent, surveyenumerators first alternated the gender of the respondent in each household. In a householdwhich required a male respondent, for instance, the survey enumerator then collected thefirst names of all the male individuals over the age of 18 who resided in the residence. Eachindividual was assigned a number and a member of the household was randomly selected. Theselected individual would then be given the survey. If the individual selected was not available,one return visit was made. If the individual was still unavailable, the next household on theright would be substituted. If the household or selected respondent refused to participate, thedaycode interval was then used to select another household.
8 That the area is rural is demonstrated by the high degree of familial connections betweenlocal politicians. The NPP Constituency Chairman is the cousin of the 2008-2016 NDC DCE,while the 2004 and 2008 NPP, and later Independent, MP is the brother-in-law to the 2000NDC MP, who is himself also first cousins with both the NPP Constituency Chairman as wellas the 2012 NPP MP.
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strongholds, why was Bosome Freho able to buck the NPP party choice for MP in 2008 while
the voters in Birim South (Akim Swedru) did not follow their NPP Parliamentarian who also
tried to run as an Independent in 2012?
6.3.2 NDC Strongholds: Adaklu Anyigbe & Ketu South
Adaklu Anyigbe and Ketu South are both dominated by Ewe populations and both
are heavily involved in the NDC voting tradition. English literacy rates are also comparable
between the two districts (Table 6-5). While the proportion of households engaged in
agriculture differ for Adaklu Anyigbe (76.7%) and Ketu South (21.4%), Adaklu Anyigbe is
located in the interior of the Volta Region where farm land is more abundant while Ketu South
is along the coast, has sandier soils, and more of its population fishes. Finally, Ketu South
contains the Aflao border town, is less rural, and has a greater proportion of cell phone owners
and internet users than Adaklu Anyigbe, though the former’s numbers are still below national
averages.
Presidential voting patterns in both districts are very consistent over time, with low
volatility rates for both districts (0.98 and 1.08, respectively) (Table 6-6). But Adaklu Anyigbe
is a great deal more volatile in its Parliamentary voting patterns than is Ketu South (14.2 and
7.66, respectively) (Table 6-7). Third party votes were particularly high in Adaklu Anyigbe in
2004 (47.8%) and 2008 (41.4%) but returned to normal levels in 2012, though NDC candidate
Juliana Azumah-Mensah was able to win in all three of the 2004-2012 elections.9 Akin to the
Bosome Freho - Birim South pairing, why were the 2004-2008 MP races in Adaklu Anyigbe
competitive while voters in Ketu South continuously toe the party line?
9 Azumah-Mensah won in Adaklu Anyigbe (Ho East constituency) in 2004 and 2008. Afterthe district and constituency were split in 2012, Azumah-Mensah won in the Agotime-Ziopeconstituency.
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6.3.3 Mfantsiman & Asikuma Odoben Brakwa
About 86% of the population in both the Mfantsiman and Asikuma Odoben Brakwa
(AOB) Districts are Fante speakers (Table 6-8). English literacy rates, proportion of rural
communities and cell phone ownership are also similar between the districts. Mfanstiman
is located on the coast, so more people are engaged in fishing, while AOB is located in the
hinterland and primarily consists of farming communities.
Though both districts are structurally very similar and electorally competitive, voters in
Mfantsiman lean toward the NDC while voters in AOB lean toward the NPP. For Presidential
races (Table 6-9), the NPP won in Mfantsiman in 2004 but lost in 2008 and 2012, while the
NPP won in AOB in 2004 and 2008, but lost in 2012. The Presidential volatility rates for
these two districts are roughly comparable (8.45 (MF) vs. 5.49 (AOB)). In the Parliamentary
races (Table 6-10), Mfantsiman elected an NPP MP in 2004 and an NDC MP in 2008 and
2012 while AOB elected an NPP MP in 2004 and 2008 and an NDC MP in 2012. Again, the
volatility rates were similar, except this time Mfantsiman was lower than AOB (6.05 vs. 8.61,
respectively). In the context of similar demographic characteristics, why do Mfanstiman voters
lean toward the NDC while AOB voters lean toward the NPP?
6.4 Qualitative Explanation of District-Level Politics
In order of relevance, the qualitative explanations emphasize locally-relevant identity
cleavages (Hypothesis 1), though less emphasized in the competitive districts, perceptions
about incumbent performance (Hypothesis 2), and, particularly in the competitive districts,
clientelistic incentives to vote (Hypothesis 3) as drivers of district-level politics.
6.4.1 Bosome Freho
The politically relevant identities in Bosome Freho revolved around four informal ‘zones’
which organized the district population into sectors of political behavior. In order of decreasing
strength of the NPP, the four zones are Abosam Zo/Sunsu Freho Zone, Lake Zone, Bosome
Zone, and Nsuta Zone. Tribal identities play into the politicization of these four zones. For
instance, one interviewee posited that Abosam Zo Zone was the strongest for the NPP because
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it consists of over 90% Ashanti residents (Interview 10/09/2013), while other interviewees
identified the Nsuta Zone as the NDC stronghold because most of the residents are migrant
farmers (Interview 10/14/2013; Interview 11/06/2013). A majority of Bosome Freho’s
population is Asante (72.5%), but different tribes have also migrated to the area for farming
over time, including Fantes, Krobo and Ewes.10
Second, after electing NPP MPs from 1996 to 2004, in 2008 Bosome Freho constituency
elected an Independent MP to office. The primary reasons behind supporting the Independent
candidate over the NPP nominee in 2008 have to do with positive perceptions about the
incumbent’s performance, despite his failure to get re-nominated by the NPP, mixed with
perhaps rural-urban or even class divides. After the NPP MP elected in 2004, Edward
Ofori-Kuragu, failed to get enough NPP Executives’ votes in the 2008 NPP primary to secure
the nomination, he followed the lead of Joseph Osei of Bekwai in opting to leave the party
in order to run as an Independent candidate. Kuragu was successful, along with three other
NPP-turned-Independent MPs in other constituencies in 2008, including Osei.11 Essentially,
Kuragu lost favor with the constituency-level NPP executives but the general public still
approved of him as a candidate and rejected the local NPP party’s decision to back another
candidate, Kwadwo Kyei Frimpong. Kuragu was re-elected in 2008 as an Independent, but
ultimately lost the 2012 race to Frimpong (NPP).
10 The status of migrant farmers is a politicized issue, particularly during election time,because migrants typically occupy land which is owned by the community and maintained bythe chief. In essence, migrant farmers’ claim to the land is tenuous, even if their families hadlived in the area for several generations. As economic resources become tight, the politicizationof insider/outsider differences become more acute.
11 This was not the first time an NPP politician had left the party in Bosome Freho. The1996 NPP Parliamentary candidate, Professor Osei Kweku Agyemang, left the party to becomethe 2000 NDC Parliamentary candidate. Now a chief in Asiwa, Ageymang’s switch left aserious stain on the NPP party within Bosome Freho. Indeed, when Kuragu (Ind.) beatFrimpong (NPP) in the 2008 Parliamentary race, many NDC members opted to vote forKuragu partially because they believed he might join the NDC in Parliament.
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Finally, though local politicians need to curry favor, often with gifts, with the local-level
NPP executives as well as the chiefs, clientelistic quid-pro-quo vote buying did not feature as a
prominent factor determining citizen votes in Bosome Freho.
6.4.2 Birim South
Birim South is a somewhat more diverse district as compared to Bosome Freho, and
politicized identity cleavages exist as allegiance to one of the three Akyem traditional areas
(Bosome, Kotoku, and Abuakwa12 ), between the major towns in the district (Achiase, Swedru,
and Aperade 13 ), and between the majority Akyem population and migrant farmers (e.g.,
Ekumfis, Fantes, Ewes and Krobos), the latter of which tend to support the NDC. All three of
these local identities interact and the political parties make very conscientious decisions about
spreading important government and party posts to candidates from different backgrounds.
Second, like Bosome Freho, Birim South also has a strong tradition of electing NPP MPs
but, unlike Bosome Freho, voters did not follow incumbent MP Joseph Ampomah Bosompem
when he left the NPP party to run as an Independent candidate in 2012. Like Kuragu in
Bosome Freho, Bosompem was not re-elected in the NPP Primary largely because he lost the
support of the local NPP executives, but unlike in Kuragu’s case, the voters instead supported
the NPP candidate, Robert Kwesi Amoah in the 2012 MP race.14
12 Abuakwa is arguably the strongest Akyem paramountcy, as it owns land far from its basein Kyibi, capital of the East Akim Municipal District. Some say that the settlers of townsbelonging to the Kotoku traditional area, which has strong ties to the Asantehene in Kumasi,came to the area prior to the Abuakwas, while others hold that the Kotokus came and beggedfor land from Abuakwas. Locally, this issue causes some tension, particularly as relates to thelocal division of power and distribution of development.
13 Previously the major town rivalry existed between Achiase and Swedru, but in 2012 theAkim Swedru constituency (the constituency that matched Birim South district boundaries)was split into two constituencies, Achiase and Akim Swedru. Now an up-and-coming townaldivision in Achiase constituency exists between Achiase and Aperade.
14 In the new Akim Swedru constituency, a fresh-faced Kennedy Osei Nyarko won in anuncontested NPP primary and won the subsequent MP race.
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Relatedly, however, though Birim South District is a NPP stronghold, local politics
between the NDC and NPP are still divisive. This divisiveness was clearly demonstrated in a
local controversy surrounding the failed confirmation of President John Mahama’s appointment
of Baffour Takyi to DCE on at least 3 occasions.15 That the District went 2.5 years (Jan
2012 - July 2014) without an active DCE, and that it still took two votes to confirm a second
nominee, is suggestive of the level of inter-party contention within the area.
Finally, given the level of political contention both within the NPP and between the NPP
and NDC, clientelistic politics, and particularly paying for individual students’ school fees,
is a dominant political strategy. For instance, very few respondents had negative words to
say about Bosompem as MP, but most people were aware of the development projects and
individual support that Amoah had implemented prior to running in the NPP MP primary.
15 Baffour Takyi, who had run on the NDC ticket for Member of Parliament in 1996 and2004, was President Mahama’s original DCE appointment in 2010. After serving for 2 years,Takyi’s re-nomination failed to receive a 2/3 majority approval vote in the District Assemblyon three occasions. Failing to receive a 2/3 approval vote on two occasions typically meansthe President would have to nominate a new candidate. Yet, a new interpretation of a clausein the Constitution by the 2012 NDC government was taken to mean that the President couldcontinue to nominate the same candidate. As Deputy Eastern Regional Minister Mavis AmaFrimpong put in her own words about the situation after the second vote failed to pass inJuly 2013: “I regretted coming to this meeting. If I knew you were going to vote this way andreject Baffour Takyi the second time, I would not have come at all. But I say to you that thePresident will renominate and renominate and renominate him. No one else will be nominatedso if you continue to reject him, the President will ask him to continue acting as your DCE”(Today’s Ghana 2013).Baffour Takyi was nominated a third time, and again failed to receive a 2/3 majority
vote. Finally, in June 2014, another candidate was nominated who also failed to receive a2/3 majority in his first vote. It was not until a successful second vote in July 2014 that theBirim South District finally had a DCE. That Takyi was still rejected after his 3rd nominationis explained by members of the NDC community as NPP members’ fear of empowering aneffective NDC politician. Indeed, Takyi had garnered 35.3% and 31% of the vote in therespective 1996 and 2004 MP races. Those in the NPP camp point to a conflict betweenthe Achiase chief, who is a divisional chief under the Abuakwa traditional state, and Takyiactively campaigned to destool the chief. Finally, one last argument is that assembly membersrejected Takyi because he is from Achiase and ‘everything’, meaning development and politicalappointments, has gone to Achiase.
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When Amoah announced his NPP candidacy, the public strongly believed that these ‘good
works’ would continue under his watch as MP.
Party politics are more contentious in Birim South than Bosome Freho, yet Bosome Freho
was willing to elect an Independent MP over the NPP MP in 2008. Outside of these qualitative
factors, is there something fundamentally different about allegiance to the NPP among voters
in Bosome Freho as compared to Birim South?
6.4.3 Adaklu Anyigbe
The political cleavages in Adaklu Anyigbe District are based on the three dominant
traditional areas: Agotime (Kpetoe-area), Ziope, and Adaklu. The traditional areas are
generally made up of Ewe-speakers, though the Agotime people have historical Ga-Adangbe
roots but married freely with Ewes in the area since pre-colonial times.16
The competitive MP elections in Adaklu Anyigbe from 2004-2012 were directly linked to
these traditional area rivalries. These divisions laid the groundwork over the creation of the
2004 Adaklu Anyigbe district (Nugent 2010, 142-43) and the placement of the new district
capital in particular. In 2004, the new NDC MP nominee, Juliana Azumah-Mensah, hailed
from Kpetoe and her nomination became entangled with a decision to place the district
16 Ethnically speaking, the Agotime traditional area was settled by Ga-Adangbe traders andmerchants in the early eighteenth century. While some argue that Agotimes were first in thearea, this is considered unlikely by area experts (Nugent 2010, 131). Relying heavily on Nugent(2010) here, Agotimes quickly established their dominance in the area, supported by theiractive role in the slave trade as allies of the Akwamu (an Akan) state. In order to increase theirpopulation numbers in Kpetoe, the present-day capital of Agotime Ziope District, Agotimesincorporated Ewe slaves into their families and particular rules were followed for Ewe absorptioninto kin groups (ibid, 132). After the Akwamu state fell out with the Volta Region states, theAsante invaded the trans-Volta area in 1869. During this invasion, Adaklu Ewes collaboratedwith the Asantes and supposedly directed them straight to Kpetoe. After the Asante and theirAnlo allies withdrew from the area some three years later, Agotime exacted revenge on Adaklu.Later, after the British defeated the Asante in 1874, Anlo traders became regular visitors to thearea and requested permission to settle, despite having allied with the Asante not long before(ibid, 133). And this is how Ziope came to be settled by ‘strangers’ (i.e. Ewes from the Southincluding Anloga, Akatsi, Klikor, etc.).
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capital at Kpetoe instead of Adaklu Waya. A lecturer from Accra, Dr. Steve Buame entered
the scene as an Independent candidate stoking the tribal differences between Agotime and
Adaklu and campaigning that he would return the district capital to Adaklu Waya.17 So, in a
traditional NDC stronghold, Azumah-Mensah (NDC) only won the 2004 Parliamentary election
by 536 votes out of 25,173 total votes and governance thereafter was difficult.18 In 2008,
Azumah-Mensah won by a 3,856 vote margin (with 55.5%), but Buame still received 39.2% of
the vote. There was finally peace when Adaklu and Agotime-Ziope became their own separate
districts in 2012.19
Third, though clientelistic political strategies are generally used in the area, the strong
dominance of the NDC deemphasizes the need to pay for votes. The high levels of competition
between Azumah-Mensah and Buame were stoked by identity-based cleavages and did not
17 When President Kufuor announced that the Ho East constituency would receive its owndistrict in 2004, he also announced that Kpetoe would be the new district capital. Rumorhas it that the then MP, Akorli, and some regional officials conspired to switch the districtcapital to Adaklu Waya. Kufuor overturned this decision but the way it was understood in theAdaklu traditional area was that Juliana Azumah-Mensah, who had just arrived on the scene tobegin campaigning for the MP position, had conspired to move the district capital back to herhometown, Kpetoe.
18 After her election, Adaklu residents boycotted the district assembly, refused to meetwith the MP or dressed in war gear to meet her, and sent back or destroyed developmentgoods sent from the MP or the district. Kufuor wisely appointed a DCE from Adaklu whofortunately was the nephew of the most senior divisional chief in Adaklu as well as the sonof the second-in-command warlord chief. Adaklu never officially declared war on Agotime,but it was certainly threatened and the central government often sent soldiers to the area tokeep the peace. The district’s budget was forced to cover the costs of housing and feedingthe soldiers, and development in the area was delayed. The conflict began to subside becauseAzumah-Mensah, also a Cabinet Minister, promised to get Adaklu its own district. PresidentAtta Mills confirmed her promises when he invited Adaklu chiefs and officials to Osu Castle.
19 With the creation of the new districts, the overall Adaklu Anyigbe budget was simply splitdown the middle, half going to Agotime Ziope and half to Adaklu, without any additionalfunds for paying for the districts’ administration. Now two sets of DCE salaries, administrationsalaries, costs of district assembly and upkeep, sitting fees for assembly members, car and fuelexpenditures and so on have to come from the same amount of money originally delegated toone district, Adaklu Anyigbe, in 2004.
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require additional clientelistic payouts to fuel it. Still, the dominance of the NDC means there
are NDC informants in every town which report to the party officials whenever the NPP tries to
rally support via development projects or handouts in even remote villages. It is then that the
NDC is particularly forced to respond with their own project or clientelistic gifts.
Since Agotime-Ziope and Adaklu received their districts in 2012, voting for the NDC is
again very high. Politicized divides between towns/tribes are now developing in both districts,
with Agotime competing against Ziope for development and with the river size Tordzenu
people against the mountainside Tonu people in Adaklu. Land ownership and sons of soil
status conflates the Agotime versus Ziope controversy, as Ziope’s ‘stranger’ status is now
often brought up in decisions about development allocations. As I will demonstrate, however,
Ketu South has similar tribal-level disputes that are instead filtered through intra-NDC party
competition instead of resulting in competition from independent MP candidates.
6.4.4 Ketu South
Ketu South is known as the ‘NDC World Bank’, and is possibly the most formidable
NDC stronghold in Ghana. Though the area is a very stable NDC stronghold, internal NDC
politics in the area can also be described as intense. The area cuts across three, politicized,
Ewe-speaking traditional areas: Aflao, Klikor, and Some.20
Politicians’ performance is certainly a driver of votes in the area. But the dominance of
the NDC means factions within the party combined with local traditional area rivalries heighten
the sense of competition within Ketu South. The current MP, Fifi Fiavy Kwetey, won the NDC
20 The citizens of each of the traditional areas are all considered Anlo-Ewe, one way oranother. Aflao, the capital of Aflao traditional area, is the largest town in the municipality.It is a border town, and on the other side of the border sits Lome, the capital of Togo. It isalso ethnically diverse while the Some and Klikor traditional areas are more homogeneous intheir Anlo-Ewe background. While the Some and Klikor are close and they intermarry freely,for instance, the Klikor Paramount Chief and the Some Paramount Chief are cousins, thereis a growing divide between Some and Klikor on the one end and Aflao on the other. Thesedifferences are now enmeshed in local politics.
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primary over the sitting candidate primarily because of his resume, his history working with the
NDC party’s founder, and his background which spreads across the three traditional areas.21
Like the Birim South NPP stronghold, local politics created significant controversy
over the appointment and confirmation of the MCE of Ketu South Municipality in 2013.
Eventually Pascal Lamptey of Aflao, and close ally of MP Kwetey, was confirmed in 2013. But
members of the Klikor and Some traditional areas interpreted Kwetey’s push for Lamptey as a
mechanism through which the already power-hungry Aflao traditional area would be favored at
the expense of their areas.22
21 Kwetey’s surname is Adangbe (a Ga tribe), his parents are from the Some traditionalarea, his maternal grandmother is from Klikor traditional area, and he was raised in Aflao. Inaddition to his well-spread indigenous background, Kwetey is nationally prominent as a formerspokesperson for J.J. Rawlings and as the Deputy Minister of Finance and Economic Planningfrom 2009-2012. After his term as Parliamentarian began in 2013, he was appointed asMinister of State in charge of Financial and Allied Institution, Minister of Food and Agriculturein 2014, and Minister of Transport in 2016.
22 First, Kwetey had been Lamptey’s ‘school father’ at Ho Polytechnic and Lampteysubsequently married Kwetey’s cousin. Prior to Lamptey’s nomination, at least two otherindividuals were announced as the government’s nominee. But nomination letters from thePresident were missing and these nominees were later denied by the government. Accordingto several sources, at least one of these individuals was a close ally of the former MP, whoKwetey had defeated in the 2012 NDC constituency primary. Rumor has it that Kwetey workedto block this nominee. With Lamptey’s nomination, several sources suggested that membersof the former MP’s inner circle were working to block Lamptey as retribution and in hopes ofgetting their own candidate into the position. Second, Lamptey previously served as the NDCyouth coordinator within the constituency and it is suggested that he burned bridges with NDCconstituency executives when he publicized the fact that the local NDC office was not payingmembers of the youth who had worked for the party during the election. Third, members ofthe Klikor and Some traditional areas feared Aflao domination and complained that they werenot consulted about the nomination (consulting traditional authorities about DCE nominations,though vague, is stipulated in the Constitution), and they felt Lamptey was being forced onthem.These three levels of controversy (Kwetey vs. the former MP, NDC Executives vs. Lamptey,
Klikor/Some vs. Aflao) surrounding the nomination of Pascal Lamptey all combined to makefor a very eventful nomination process. Like the prior announced nominees, it was difficult toget hold of a nomination letter for Lamptey and when one was finally produced it was printedon ‘Draft’ paper and was addressed to the Regional Minister rather than the Municipality. At
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Finally, though clientelistic campaign strategies are used as a political strategy in Ketu
South, the traditional area rivalries are the primary driver of political cleavages and local vote
decisions. At the national level, the vast majority vote for the NDC regardless.
Again, is there something fundamentally different about allegiance to the NDC among
voters in Adaklu Anyigbe as compared to Ketu South? Does Adaklu Anyigbe’s apparent
willingness to vote against an NDC candidate in favor of an Independent MP suggest
something about their overall attachment to the NDC as compared to Ketu South whose
competition is more strictly within the NDC?
Lamptey’s first confirmation vote he needed 37 votes but only received 33 votes out of 55present members. When Lamptey was not approved, ‘Aflao boys’ arrived on the scene andbegan harassing assembly members who sought refuge in the second floor of the assemblybuilding. There the Minister of Trade scolded the assembly members and tried to force them totake a second vote that very day. Meanwhile, an elected assembly member who is in Kwetey’sinner circle calculated how likely it was that any of the 18 appointed assembly members werepart of the 22 no-votes for Lamptey. It was determined that some appointed members musthave voted against Lamptey. Ten days later, on the last day the second vote was eligible totake place, the majority of government appointees were revoked and new appointees weresworn-in just prior to a vote which approved Lamptey’s nomination, 47 to 8. The Some andKlikor paramountcies had sought injunctions to stop the vote, but these were not approved.The distribution of money to district assembly members was also widely acknowledged to havehad an impact on this second vote.Finally, after Pascal’s second vote, it came out that the appointment letters for the new
nominees was dated October 24th, but the termination letters for the prior appointees wasdated the 28th. The terminated appointees were then given letters that were backdatedto the 21st. This information became public and was announced on the radio, furthersuggesting political manipulations were behind the events. Though some challenged thesecond confirmation vote as invalid on the basis of the mis-matching letter dates, Lampteywas quickly whisked away to M/M/DCE orientation and he currently serves as the MCE underthe Mahama administration. These events made national news and the district assembly voteswere attended by prominent government and NDC officials alike.
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6.4.5 Mfantsiman
The major political cleavages in Mfantsiman exist along political party lines, rather than
identity. Ethnically, the constituency is made up of a majority of Fante speakers, though there
is some diversity in terms of the origins of these Fante speakers. 23
Candidate performance, mixed with partisan preferences, is a driver of vote decisions.
Regionally, the district strongly favored the NPP in the 2004 Presidential election24 and then
increasingly switched to favor the NDC in the 2008 and, even more so, in the 2012 Presidential
contests.25 As far as MP elections, Steven Asamoah Boateng (NPP) was elected in 2004 but
lost in 2008 and 2012 to Aquinas Quansah (NDC). That Boateng lost in 2008 and thereafter is
explained as his ineffective time in office and, more importantly, divisions within the NPP which
Boateng exacerbated.26
23 The word ‘Fante’ itself translates to ‘the part that has moved’ and most Fante speakersoriginate from the Ashanti or Brong Ahafo Regions.A number of communities are made up ofpeople who are originally Gonjas, Guans and Bonos from Techiman in the Brong Ahafo Region.The story goes that people migrated east and then south when the Bono-Techiman Kingdomwas at war with the Asante Kingdom. Denkyiras, also known as Agonas, also originatedadjacent to the Asante Kingdom and after a war with the Asantes, became a tributary stateto the Asante Empire in the early 1700’s. Later, Denkyiras joined with the Fante Confederacyand the British to fight against the Asantes and Dutch in the mid 1800’s. Denkyira, or Agona,communities are generally located along the north side of Mfantsiman constituency.
24 Yet, Mfantsiman was the only Central Region district in 2004 to not surpass the 50%threshold for votes for NPP’s Kufuor.
25 In 2004, the Mfantsiman District was made up of Mfantsiman West and Ekumficonstituencies. As presented in Table 6-9, Mfantsiman West (where the surveys took place)did pass the 50% mark in voting for Kufuor in 2004, but at 54.6% the constituency was stilllow in support for the NPP as compared to other Central Region constituencies.
26 Boateng, affectionately known as ‘Asabee’, was a most controversial candidate forthe constituency. Though he was the only NPP candidate to win the MP spot, he alsowas and continues to be the local NPP branch’s greatest liability. For instance, Boatengis firmly entrenched in the camp of former NPP President John Kufuor. Under Kufuor’sadministration he was appointed Deputy Minister for Information and National Orientation in2004, Minister for Local Government and Rural Development in 2006 and Minister for Tourismand Diasporean Relations in 2007. Yet, Asabee also supported Alan Kyeremantan as Kufuor’s
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That the district leans toward the NDC more than some other Central Regional Districts
can partially be explained as a result of the proximity of former President Atta Mills’ (NDC)
hometown. The present-day Mfantsiman Municipal District was once combined with
Mfantsiman East, known today as Ekumfi, constituency but Ekumfi received its own district
status in 2012. That former President Atta Mills hails from neighboring Ekumfi certainly had
an impact on the perceptions of the NDC in Mfantsiman, particularly when the two areas
belonged to the same district.27
Finally, clientelistic incentives to vote were widely reported during our work in Mfantsiman.
It appears the political parties hold rallies or go door-to-door and offer cash incentives for
voting, and to a much greater degree in Mfanstiman (and Asikuma Odoben Brakwa) than the
other four party stronghold districts. Several interviewees suggested that the NPP engaged in
political rallies in city centers, which were less effective than the NDC’s door-to-door campaign
style. Further, Mfantsiman is known as a ‘prominent’ district and individuals from the area
are typically appointed to high-level positions. As one source put it, “If you don’t give [the]
Mfantsiman area a minister, you don’t understand Ghanaian politics” (Interview 11/17/2013).
This fact is also suggestive of neopatrimonial politicking (i.e. awarding ministerial positions for
party support) in this area.
successor and some sources say he actively campaigns against Akufo-Addo’s presidentialcandidacy. Internal constituency rifts about supporting Akufo-Addo versus Kyeremantin werecompounded by Asabee’s decision to schedule his own constituency primary in 2008. He didnot inform some crucial constituency-level NPP executives of this plan as well as a prospectivecandidate who therefore missed the vote. The absent candidate took the matter to court, andthe local NPP branch had to spend time and resources sorting out the matter during the 2008election year, time which otherwise would have been spent on campaigning. In that electionAsabee, a Minister, was voted out of office. Asabee (unsuccessfully) challenged the results ofboth the 2008 and 2012 parliamentary election results in court.
27 That Ekumfi, and thus Mfantsiman, received their own districts is locally understood asthe result of Atta Mills’ election in 2008, especially considering Ekumfi did not have a largeenough population or the significant amount of commercial activity necessary to become adistrict.
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6.4.6 Asikuma Odoben Brakwa
Though a predominantly Fante district along with Mfanstiman, political cleavages in
Asikuma Odoben Brakwa (AOB) largely revolve around inter-town rivalries coupled with
an urban-rural divide. The name Asikuma Odoben Brakwa refers to the names of the three
urban towns in the district. Ethnically, the area is technically Fante. However, the Breman
traditional state, itself a hybrid of Asante and Fante, identifies as an independent tribe with
its own language, Breman.28 Other tribes in the area include Gomoas, whose people formed
one of the states in the historical Fante Confederacy and are now typically considered Fantes,
Agonas, Akumo/Asantes, Akyems, Ewes, etc, who have largely come to the area for cocoa
farming purposes. Traditional area and town rivalries coincide and, like Ketu South though
with much less intensity, affect local politics. Great efforts have to be taken by the NPP and
NDC to spread the number of government posts and party positions from across the three
towns. Additionally, the NPP is favored within the more urban towns, while the NDC is favored
in rural areas, particularly among migrant farmers.
Electorally, party politics are competitive in the district. AOB was more typical of northern
Central Regional Districts in its hesitation to switch from the NPP in the 2004 Presidential
contest to the NDC in 2008. From a nearly 30% point spread in the 2004 Presidential election,
AOB switched to a less than 2% vote margin in the 2008 and 2012 Presidential elections.
Within MP races, P.C. Appiah-Ofori (NPP) won in 2000 with a 7 point margin, in 2004 with
28 The term Breman is a German-derived word. One person described it as “Bremans areFantes that are from Kumasi. Originally [they are] Asantes from Kumasi but they intermarriedso now we are Fantes” (Interview 11/14/2013). The Ghana Census does not recognizeBreman as a distinct tribe and rather groups it in with Fante. Asikuma-Odoben-Brakwa isalso traditionally under the Breman paramountcy, but at some point a local controversy causedthe Odoben and Brakwa chiefs to secede from the Breman traditional area to join the Ajumakoparamountcy based in the neighboring Ajumako-Enyan-Esiam district.
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a 18 point margin, and in 2008 with a 2 point margin.29 Though she lost in the 2004 and
2008 races, Georgina Nkrumah Aboah (NDC) was appointed DCE in 2009 and won in the
subsequent MP race in 2012. Like Mfantsiman, intra-party rivalries are used to explain why
the NPP was not able to continue it’s hold on the MP seat after Appiah-Ofori retired in 2012.
As Anthony Effah (NPP) has worked systematically to shore up support with the local NPP
executives, the 2016 MP race is likely to be very competitive.
Inter-party rivalries were exemplified in a controversy over the appointment of the DCE,
similar to that of Ketu South but with much less intensity. Out of 15 individuals who applied
for the DCE position locally, three were shortlisted by the Region and their names sent to
Accra. But, instead a name (Samuel Adom Botchway) was sent back which was not on the
original short list.30 Still, unlike the dramatic result of a similar controversy in Ketu South,
Botchway did not get confirmed during the first vote but, after some standard pressure from
the Central Region Deputy Regional Minister, was approved in a second vote held several
months later.
Finally, like Mfanstiman, clientelistic payouts as a political strategy were heightened in
AOB. As interviewees described in Mfanstiman, part of the reason the NDC won the MP spot
29 Though nationally prominent as an anti-corruption crusader, Appiah-Ofori remained acontroversial figure within the NPP and partially explain why he was never appointed to anyMinister post. His forthrightness in announcing corruption led him at times to be criticalof both the NPP and NDC, including in 2009 when he prominently accused NPP MPs ofaccepting $5,000 bribes to approve of telecommunications giant Vodaphone’s 70% acquisitionof state-owned Ghana Telecom.
30 This moved caused great consternation for the local NDC executives who strongly favoreda locally-popular Zenith Bank Operations Manager who had resigned his post knowinghe would get the nod. How Botchway’s name came to be returned when he did not evenapply is unknown, but it is widely believed to have to do with Botchway’s connections andstring-pulling from big wig NDC figures. After all, Botchway was funded to go to Cuba foreducation during Rawlings’ time, is the former administrative manager of Kobina Fosu’s lawfirm in Tema, and was the campaign coordinator for Aboah’s 2012 MP campaign.
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in 2012 was due to it’s door-to-door campaign style as compared to the NPP which more
commonly holds town hall-type rallies.31
What explains Mfantsiman’s preference for the NDC as compared to AOB’s preference for
the NPP? I rule out Mfantsiman’s proximity to former President Atta Mills’ hometown as the
sole causal factor because only 43.9% of Mfantsiman West voters voted for Atta Mills (NDC)
for President in 2004 and because other districts in the southern portion of the Central Region
also display similar NDC-preference voting patterns as Mfantsiman. What explains AOB’s
preference for the NPP, given that the district is also dominated by Fantes? And why does
AOB’s preference for the NPP mimic the voting preferences of other districts in the northern
half of the Central Region?
6.5 Survey Analysis: Political Knowledge and Behavior
As we have seen in the qualitative explanation of politics in each district, each of the three
core hypotheses are supported to varying degrees. Following up on the qualitative analysis,
I test for the three core hypotheses using 11 different survey questions throughout Chapters
6-8. In the reminder of this chapter I begin the survey analysis by analyzing respondents’
reasons for their votes as well as knowledge about party ideologies. In the subsequent chapter
I predict respondents’ votes in multinomial logistic regression models and analyze swing voting
behaviors. Finally in Chapter 8 I separately test for tribal, religious, and clientelistic impacts on
citizen votes through the use of survey experiments.
Overall, I find ample evidence for Hypothesis 2: Policy-Based or Economic-Based
Voting, both when respondents are directly asked for their reasons for their votes, when
using multinomial logistic regressions to test for respondent votes, and logistic models to
test for swing voters in Chapters 6 and 7. I do also find some evidence of Hypothesis 1:
31 One interviewee described the swing-voting tendencies of the area as because “partyexecutives come and don’t tell the truth so the youth switch their votes” (Interview11/14/2013).
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Identity-Based Voting and Hypothesis 3: Clientelistic-Based Voting from indirect questions
and list experiments. Though respondents might not be keen to suggest that identity or
clientelistic factors also impact their vote decisions, it is increasingly clear that each of the
three hypotheses combine with one another to influence citizen votes. This conclusion is drawn
from the presence of all three hypotheses in the qualitative analysis of district-level politics as
well as the support for each hypothesis in different types of survey questions. Finally, given the
unwillingness of voters to share ethnic or clientelistic vote biases, implicit or hidden survey tests
should be used in sub-Saharan African democracies, as they are used in developed democracies,
to test for these biases. Otherwise we risk underestimating and/or ignoring the effect of
identity or clientelsitic inducements on votes.
6.5.1 Biggest Reasons for Your Vote and Votes in the Community
6.5.1.1 Overall results
When asked to report the three biggest reasons for their vote for President or Member
of Parliament in the 2012 contests, without saying whom they voted for, the Candidate’s
Social Policy (76.7%- Pres., 68.0%- MP), Candidate’s Economic Policy (71.2%- Pres., 62.8%-
MP), and Candidate Approval (55.01%- Pres., 70.49%- MP) were the three most popular
responses for both questions (Tables 6-11 & 6-12). Similarly, when asked for the biggest reason
driving Presidential votes within this community (Table 6-13), respondents again pointed to the
Candidate’s Social Policy (41.7%), the Candidate’s Economic Policy (26.5%), and Candidate
Approval (20.16%) (Tables 6-11 to 6-13).32
32 Categories:1) Candidate’s Economic Policy (ex: commodity prices will be moderated, keep inflation
down, etc.)2) Candidate’s Social Policy (ex: youth employment, jobs for women, education, etc.)3) Party Legacy (ex: political party performed well here in the past, party legacy, past
leaders, etc.)4) Candidate Approval (ex: candidate traits/capabilities, believe candidate will help my
community, etc.)
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In all three of these sets of questions identity-based factors (Hypothesis 1) are significantly
downplayed. Only 5.98% (8.07%) of respondents identified a Particularistic or Ethnic reason as
one of their three biggest reasons for voting for President (MP). And, whereas we might expect
respondents to blame ‘un-democratic’ voting habits on others rather than themselves, only
1.1% of respondents said a Particularistic or Ethnic factor was the biggest reason for driving
Presidential votes within the community. Relatedly, less than 1% of respondents identified
clientelistic reasons (Hypothesis 3) for either their votes for President or MP or others’ votes
for President.
It is important to note that less than 1% of respondents cited their disapproval of the
current government or candidate as a reason driving their own or others’ votes. Responses
instead were predominantly forward-looking such as “[to] improve health insurance”, “[for
the] building of more schools in the constituency”, and “to better Ghana”.33 Even those
respondents who referred to the state of the economy as a reason phrased their responses in
forward-thinking ways: “[for the] economic well-being of the community” and “[for] someone
to manage the economy”. Overall, respondents understood their votes and their community
members’ votes as driven by policy and/or economic assessments (Hypothesis 2), with
particular emphasis on prospective social and economic policies as opposed to the social or
economic downfalls of prior candidates/governments.
5) Disapproval of Gov./Candidate (ex: to bring change, gov. didn’t continue past projects,etc.)6) Particularistic/Ethnic (ex: candidate’s tribe/ethnicity, candidate’s religion, candidate’s
home area, etc.)7) Clientelistic (ex: personal help or promise of personal help, landlord asked me to vote)8) Voting as a Right (ex: voting is a constitutional right, vote to be a good citizen, vote to
get voter’s card)
33 Questions 9, 10, and 13 were open-ended response items that were coded by the surveyorat the time of the interview. If surveyors were even slightly unsure of how to code an item,they were instructed to write the response down verbatim. These written responses provide apartial view of the nature of responses overall.
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6.5.1.2 Within district pairs
Turning to the six districts in the sample, there are some interesting points of differentiation
separating Bosome Freho from Birim South, Adaklu Anyigbe from Ketu South, and Mfantsiman
from Asikuma-Odoben-Brakwa when giving reasons for their votes for President and MP, as
well as community members votes for President (Figures 6-1 - 6-9).
First, within the Bosome Freho-Birim South pair, party legacy and candidate approval
were more common explanations of respondents or community members’ votes in Bosome
Freho than Birim South. In Birim South, particularistic/ethnic rationales were cited more
in explanations for presidential votes (Figure 6-1), while economic and social policies were
generally cited more in explanations of votes for MP and community members’ votes for
President (Figures 6-4 and 6-7).34
Next, when comparing the NDC strongholds, Adaklu Anyigbe and Ketu South, against
each other in terms of respondent explanations for their votes, economic and social policies,
party legacy, and particularistic/ethnic reasons were generally cited by more respondents in
Adaklu Anyigbe than Ketu South, across the vote explanation questions. Particularistic/ethnic
reasons for voting for MP were highest in Adaklu Anyigbe (13.5%) and Ketu South (10.4%) in
comparison to the rest of the districts. Candidate approval and voting as a right were generally
higher in Ketu South than Adaklu Anyigbe (Figures 6-2, 6-5, and 6-8).35
Third, among the competitive districts, Mfantsiman and Asikuma Odoben Brakwa, the
districts were particularly similar across the questions. First, in responses explaining their votes
for President and MP, Mfanstiman respondents cited Particularistic/Ethnic rationales with
34 Note that a greater percentage of Birim South respondents (82.5%) cited the Candidate’sEconomic Policy more than any other district in explaining their Presidential votes, while agreater percentage cited both Economic Policy (75.9%) and Social Policy (81.6%) than anyother district when explaining their votes for MP.
35 In Ketu South, however, Candidate’s Social Policy was only given as a reason by 43.8% ofrespondents, far below the sample-wide average of 76.7%.
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slightly greater frequency while candidate approval was cited slightly more in AOB (Figures 6-3
and 6-6). In explaining community members’ votes for President, economic policy was cited
with greater frequency in Mfantsiman while social policy and, to a slight degree, party legacy
was cited more in AOB (Figure 6-9).
6.5.1.3 District-by-district analysis
First, support for Hypothesis 2: Policy-Based or Economic-Based Voting is strong across
the districts, with Social Policy tending to be more cited than Economic Policy. In Ketu
South, however, Candidate’s Social Policy was only given as a reason by 43.8% of respondents,
far below the sample-wide average of 76.7%. Also a greater percentage of Birim South
respondents (82.5%) cited the Candidate’s Economic Policy more than any other district.
Second, though 5.98% of the total sample’s respondents cited a Particularistic/Ethnic
reason for their vote for President, that average was certainly raised by the 13.5% of
respondents in Adaklu Anygibe who gave a Particularistic/Ethnic reason. Ketu South (6.6%)
and Birim South (6.3%) were also above the 5.98% sample average. Finally, clientelistic
reasons for votes (Hypothesis 3) were never cited by more than 1% of respondents in any
district.
Respondents’ explanations of the reasons behind their vote for MP (Figures 6-4 - 6-6)
also provide a lot of support for Hypothesis 2: Policy-Based or Economic-Based Voting with
Candidate’s Economic Policy and Social Policy consistently among the top three answer
choices per district. However, variation across districts exists. For instance, Economic Policy
and Social Policy are very high in Birim South (75.9%, 81.6%) and Adaklu Anyigbe (65.3%,
74%), but are comparatively lower in the other four districts. Yet, only 42.6% of Bosome Freho
respondents cited Economic Policy and 44.5% of Ketu South respondents cited Social Policy,
which are the lowest respective rates across the 6 districts in each case. Finally, about 52%
of respondents cited Candidate’s Economic Policy and Social Policy in both Mfantsiman and
AOB.
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The sample-wide percentage of respondents who cited an Ethnic/Particularistic reason
for their vote for MP (Hypothesis 1) was 8.07%, yet this was again driven by the 13.5% of
respondents from Adaklu Anygibe and 10.4% of respondents from Ketu South who gave an
Ethnic/Particular reason. Again almost no respondent gave a Clientelistic reason for their vote
for MP.
Finally, in comparing respondents’ answers to the question, ‘What Is The Biggest
Reason Driving Presidential Votes within this Community?’ (Figures 6-7 - 6-9), Social Policy
dominates in Bosome Freho, Birim South, Adaklu Anyigbe and AOB. In Mfantsiman, Social
Policy is the third highest category and in Ketu South it is fourth. Economic Policy is the
most cited category in Mfantsiman (31.7%), cited the second most in Bosome Freho, Birim
South, Adaklu Anyigbe, and Ketu South, and the third most cited category in AOB. Overall,
respondents focused on policies in the Bosome Freho and Birim South NPP Strongholds,
whereas Party Legacy and Candidate Approval factored more in the other four districts.
Identity-Based Voting (Hypothesis 1) accounts for very few responses across the districts,
though Particularistic/Ethnic reasons for community-members’ votes were again cited more in
Adaklu Anyigbe and Ketu South than any other district. Finally, almost no respondents cite
Clientelistic Reasons for Community Votes (Hypothesis 3).
6.5.2 Identifying NDC and NPP Ideologies
Respondents were next asked whether Ghana’s political parties have different ideologies
(Q20)36 and to identify components of the NDC’s Political Ideology (Q21) and the NPP’s
Political Ideology (Q22). When respondents cite ethnicity as a part of either party’s ideology,
this suggests that identity information (Hypothesis 1) does matter in the minds of respondents
in terms of how they perceive the political parties. When respondents cite Policy-Based Criteria
36 Respondents were asked if Ghana’s political parties have different ideologies and then werecued with ‘Are the political parties known for different political platforms or policies?’
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of a party’s ideology, this provides evidence for Hypothesis 2. Third, Clientelistic components of
a party’s ideology provides support for Hypothesis 3.
To begin, though political parties in new democracies are characteristically known for their
weak party platforms, 82.48% of the respondents in our sample said that Ghana’s political
parties’ ideologies were ‘Very Different’. Less than 18% of the sample responded that Ghana’s
political parties are ‘Somewhat Different’ or that there is ‘No Difference [between them]’ (Table
6-14).
6.5.2.1 The NDC ideology
The NDC has traditionally been associated with Socialist ideals, first propagated by
Rawlings early in the PNDC regime, and then converted into the concept of Social Democracy
in Ghana’s Fourth Republic. The purging of corrupt political elites in the ‘June 4th Revolution’
by the AFRC regime, including the death by firing squad sentences handed out to several
prominent individuals including three former heads of state, as well as the latter PNDC
regimes’ emphasis on ending corruption and hoarding, both aligned Rawlings with the working
class and the poor. That Rawlings and his comrades were junior officers overthrowing corrupt
senior officers provided symbolism for the movement. The present-day NDC still draws on these
traditions in the Fourth Republic.
As discussed in prior chapters, the NDC is associated with Ewe and Northerner interests,
largely due to the fact that Rawlings is half-Ewe and that Rawlings’ PNDC regime implemented
policies which directly benefited the grossly underdeveloped North of the country (present-day
Northern, Upper East, and Upper West Regions). Finally, the NDC has also been associated
with a development platform called the ‘Better Ghana Agenda’. The term was first used by the
2008 Atta Mills administration and, according to the 2008 and 2012 NDC Manifestos, covers
a wide range of topics including corruption, women’s representation in government and public
service, promotion of lending to businesses, and strengthening of environmental regulations,
among other topics. As explained in these NDC manifestos, the Better Ghana Agenda is a very
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general platform with little effort made to explain how the agenda goals will be accomplished
(National Democratic Congress 2008; 2012).
When asked about the components of the NDC’s Political Ideology (Table 6-15), 72.1% of
respondents cited the NDC’s broad stroke policy agenda, the Better Ghana Agenda. Another
3.72% cited specific social policy/development projects, such as building of roads or schools,
that they said the NDC was known for.37 The second most-cited component was Development
(43.81%) and the third was Socialism/Social Democracy (38.14%). I generally understand
these responses as related to Hypothesis 2: Policy-Based or Economic-Based Voting, because
of their emphasis on social/developmental policies and performance.
In reference to Hypothesis 1: Identity-Based Voting, interestingly, 16.9% of respondents
said that the NDC was for the Ewes and/or for the Muslims/Northerners. This is double the
high of 8.07% who cited a Particularistic/Ethnic reason within the top three biggest reasons
for their vote for MP. This might suggest that respondents are more willing to blame ethnic
galvanizing on the politicians and political parties rather than on themselves or their fellow
community-members.
Finally, only 8.02% of respondents cited the Working Class, Poor, or the Masses when
asked about the NDC’s Political Ideology. This is less than half of the proportion who cited
Ewes, Muslims and/or Northerners. Apparently, ethnicity/region/religion have stronger
associations with the NDC ideology than economic classes.
6.5.2.2 The NPP ideology
While the NDC is sometimes understood as a party born out of the CPP, it is widely
agreed that the present-day NPP is within the same political tradition as the original United
Gold Coast Convention (UGCC), which transformed into the United Party (UP), Progress Party
37 These responses did not converge on any one or two types of development projects.Instead the projects cited were very diverse, even from respondents within the same district.
219
(PP), and the Popular Front Party (PFP), before becoming the New Patriotic Party (NPP) in
the Fourth Republic.
With strong ties to the historical UGCC and UP political traditions, the NPP has
traditionally be associated with capitalism and market-oriented economics, elites, the protection
of cocoa farmers interests, and Asante and Akyem interests. In comparison to the NDC’s
Better Ghana Agenda, and rather than push a general platform, the 2012 NPP national
campaign instead focused on one particular policy: Free Secondary School Education.
In responding to the question asking about the components of the NPP’s Political
Ideology, 77.21% of respondents identified the NPP national platform of Free Secondary
High School Education (Table 6-16). This is by far the most cited category, while the next
is Development with 29.27% of respondents citing it. A close third category is that the NPP
is known for pushing a Market-Oriented or Laissez-Faire Economy (23.58% of respondents).
Respondents are certainly aware of the Policy Platforms for the NPP.
In comparison to the 16.9% of respondents who said the NDC was for the Ewes, Muslims
and/or Northerners, only 11.03% said that the NPP is for the Asantes and/or Akans. Also
interesting is that 13.64% of respondents said the NPP was for the Working Class, Poor
and/or the Masses, in comparison to the 8.02% who cited the NDC. The NPP are historically
associated with educated and elite interests, yet only 8.0% cited the Rich and/or Elite as
associated with the NPP ideology. Clearly the NPP has put in some impressive legwork to alter
its historical associations in the Fourth Republic.
6.5.2.3 Within district pairs
Again, comparing Bosome Freho to Birim South, Adaklu Anyigbe to Ketu South, and
Mfantsiman to Asikuma Odoben Brakwa shows some interesting differences within district pairs
(Figures 6-10 - 6-18).
First, within the Bosome Freho-Birim South pair, a greater proportion of Bosome Freho
respondents said the political parties’ ideologies were Somewhat Different, as compared
to Birim South, while a greater proportion of Birim South respondents reported there
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was No Difference between the parties’ ideologies (Figure 6-10). In describing the NDC
ideology, Bosome Freho residents were more likely to cite Socialism/Social Democracy
while Birim South respondents associated the Better Ghana Agenda, Development, and
Ewes/Muslims/Northerners with the NDC with greater frequency (Figure 6-13). Finally, in
describing the NPP, Bosome Freho respondents cited the working class/poor and development
more while Birim South respondents cited Asantes/Akans and the Free SHS Policy more than
those in Bosome Freho (Figure 6-16).
Next, in comparing whether Ghana’s political parties have different ideologies within the
NDC strongholds, Adaklu Anyigbe respondents cited that party ideologies were Somewhat
Different at a higher rate while Ketu South respondents cited Very Different at a higher
rate (Figure 6-11). When describing the NDC ideology, the Working Class/Poor and
Ewes/Muslims/Northerners were slightly cited more in Adaklu Anyigbe while Socialism/Social
Democracy and development were somewhat higher in Ketu South (Figure 6-14). Finally,
Adaklu Anyigbe respondents were somewhat higher in citing the Working Class/Poor,
Rich/Elite, and Asantes/Akans as associated with the NPP ideology while Ketu South
respondents were somewhat more likely to cite Market-Oriented/Laissez-Faire policies and
Development (Figure 6-17). Adaklu Anyigbe and particularly Ketu South respondents had
some of the highest percentage of respondents cite both Socialism/Social Democracy for the
NDC ideology and Market-Oriented/Laissez Faire economic policies for the NPP ideology.
Third, the competitive district respondents were very similar in whether or not they felt
Ghana’s political parties had different ideologies (Figure 6-12). When explaining the NDC
ideology, responses were again similar, though Ewes/Muslims/Northerners and the Better
Ghana Agenda were cited with slightly higher frequency in Mfantsiman while Socialism/Social
Democracy and Development was cited with slightly greater frequency in AOB (Figure 6-15).
Finally, when describing the NPP ideology, the Rich/Elite were cited somewhat more in
Mfantsiman while the Working Class/Poor and Development were somewhat higher in AOB
(Figure 6-18).
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6.5.2.4 District-by-district analysis
Next I consider the district-level analysis of respondents’ answers about Ghanaian political
party ideologies. In the overall sample we had seen that 82.5% of respondents said that the
political parties were Very Different, 13.3% had said they were Somewhat Different and 4.2%
said there was No Difference. Now considering the district-level responses, respondents from
Mfantsiman (92.6%) and AOB (90.7%), the competitive districts, were more likely to cite the
political party ideologies as Very Different (Figure 6-12), while fewer respondents within Adaklu
Anyigbe (65.7%) said the party ideologies were Very Different (Figure 6-11). Turning to the
No Difference response, Birim South respondents stand out for having the highest percentage
of respondents (11.04%) reporting that there was No Difference in Ghana’s political party
ideologies (Figure 6-10). On the other end of the scale, only between 1-2% of respondents in
Bosome Freho, Mfantsiman, and AOB said there was No Difference between the political party
ideologies.
Analyzing what respondents say about the party ideologies provides an insight into the
information respondents bring with them to vote. In terms of Hypothesis 2: Policy-Based
or Economic-Based Voting, on average 72.1% of respondents in the entire sample cited the
Better Ghana Agenda as part of the NDC’s ideology. The proportion of respondents who cited
the Better Ghana Agenda in Birim South (71.5%), Bosome Freho (68.1%), and Ketu South
(55.6%) were below average while the proportion of respondents citing the Better Ghana
Agenda in Mfantsiman (81.1%), AOB (78.3%), and Adaklu Anyigbe (75.5%) were above
average (Figures 6-13 - 6-15). That Ketu South, one of the NDC strongholds, had the lowest
proportion of respondents cite the Better Ghana Agenda again suggests that respondents in
the ‘NDC World Bank’ are so committed to the party that either politicians do not emphasize
policy platforms or that voters do not pay policy platforms as much heed. It is also interesting
that respondents in the competitive districts had the highest proportion of respondents identify
the Better Ghana Agenda, as well as way above average proportion of respondents who cited
particular social policy projects with the NDC. Clearly the competitive electoral environment in
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these districts contributes to enhanced campaign strategies to differentiate the parties from one
another.
Further, the identification of Socialism or the Working Class as a component of the NDC
ideology can also be considered as support for Hypothesis 2. Here respondents from the NDC
strongholds were more likely to cite Socialism (63.4%- Adaklu Anyigbe, 59.0%- Ketu South),
though 42.0% of Bosome Freho respondents also cited it. Relatedly, 18.5% of Adaklu Anyigbe
respondents identified the Working Class with the NDC’s ideology, while about 7% cited the
working class in Ketu South, Mfantsiman and AOB. Only 0.5% and 3.2% of respondents in
Bosome Freho and Birim South (NPP strongholds) cited the working class as a component of
the NDC ideology.
There is also some evidence supporting Hypothesis 1: Identity-Based Voting in the
identification of the Ewes, Muslims, and/or Northerners with the NDC ideology. The districts
with the highest proportion of respondents identifying these groups with the NDC ideology are
Adaklu Anyigbe (29.6%) and Birim South (22.8%). At 11.1% and 4.9% respectively, Bosome
Freho and AOB respondents had the lowest percentage identifying these identity groups with
the NDC ideology.
In the district-level responses identifying the NPP’s political ideology (Figures 6-16 -
6-18), the NPP’s Free Secondary High School (SHS) is the most commonly cited response in
every district. While an average of 77.2% of respondents in the entire sample gave Free SHS as
a NPP ideological component, about 90% of respondents in both Mfantsiman and AOB, 69 -
84% of respondents in Bosome Freho, Birim South, and Adaklu Anyigbe identified the NPP’s
Free SHS policy. The district with the lowest proportion of respondents identifying the Free
SHS policy was Ketu South at 49.8%.
Laissez-faire economics and elite interests are also historical components of the
NPP’s ideology, or at least the ideologies of past parties which the NPP is a continuation.
Interestingly, a very large 53.4% and 45.% of respondents in Adaklu Anyigbe and Ketu South,
the NDC strongholds, identified laissez-faire or free market economics as a component of the
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NPP ideology. This is in comparison to about 14% of respondents in both Bosome Freho and
Birim South, and less than 7% in both Mfantsiman and AOB. Recall that large proportions
of the NDC strongholds had identified Socialism as a component of the NDC ideology. For
whatever reason, it appears Adaklu Anyigbe and Ketu South residents are well-versed on the
historical economic principles of both parties as compared to other districts. Finally, a greater
proportion of Adaklu Anyigbe respondents (21.2%), as compared to every other district,
identified elite interests as a component of the NPP ideology. In general, a higher proportion of
respondents in each district identified the Working Class, as opposed to the Elite, as a central
component of the NPP ideology.
Finally, a relatively high proportion of respondents in Adaklu Anyigbe (32.5%), Ketu South
(16.5%), and Birim South (11.4%) identified Asantes and/or Akans as a central component of
the NPP ideology. Outside of these three districts, very few respondents in the remaining three
districts cited these identity groups as part of the NPP ideology.
6.6 Discussion
Thus far in the analysis, there is varying yet consistent qualitative evidence for all
three hypotheses. Within the survey analysis conducted thus far, there is some support for
Hypothesis 2: Policy-Based or Economic-Based Voting when respondents explain their own
and other community-members’ rationales for voting. Identity-Based Voting (Hypothesis 1)
and Clientelistic-Based Voting (Hypothesis 3) are significantly downplayed in respondents’
explanations. However, even though policies are the dominant explanation for votes,
Particularistic/Ethnic explanations for votes were higher in Adaklu Anyigbe and Ketu South
(the NDC strongholds) than the other four districts. For all districts, Particularistic/Ethnic
explanations were generally cited more when respondents’ explained their own votes for
President, except for Bosome Freho which cited this explanation more in votes for MP. Finally,
it should be kept in mind that the opinions respondents share are unlikely to be sensitive
or embarrassing, making it inherently difficult to find support for Identity-Based Voting or
Clientelistic-Based Voting in forthright survey questions.
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In assessing respondents’ opinions about political party ideologies, there is a great deal
of evidence that respondents view party ideologies in Ghana as very different. The NDC’s
Better Ghana Agenda was the top response for the NDC’s ideology (though it was beat out
by the Socialism response in Ketu South), while the NPP’s Free Secondary High School
Education policy was the most common response for NPP ideology. Ideological backgrounds
of both parties, such as Socialism in the case of the NDC and Laissez-Faire/Market-Oriented
Economy in the case of the NPP, were also common responses. The ideological responses,
whether put in terms of current policy agendas or background ideological principles,
provide support for policy-based voting (Hypothesis 2). However, support for Hypothesis
1: Identity-Based Voting is still present as a respective 16.9% and 11.0% of respondents cited
the Ewes/Muslims/Northerners as for the NDC and the Asantes/Akans as for the NPP. A
higher proportion of respondents identify ethnic/religious/regional groups with party ideologies
than do respondents that explain vote decisions on the basis of particularistic/ethnic rationales.
There is also a great deal of evidence that respondents from the NPP strongholds, NDC
strongholds, and competitive districts explain their votes in different ways and understand the
NDC and NPP party ideologies differently from one another. Further, there is some evidence
that responses differ within the district pairs and that these differences may be linked to the
variation in voting patterns between district pairs. Interestingly, Bosome Freho and Ketu
South appear to be the strongholds with the most uncriticized allegiance to the respective
NPP and NDC parties, partially because of respondents’ lack of emphasis on policies and
greater emphasis on party legacy and candidate approval. Yet of the NPP strongholds Bosome
Freho was the district that voted in an Independent candidate in 2008, while of the NDC
strongholds Ketu South never considered a party other than the NDC. I interpret this as a
strong commitment to the NPP in Bosome Freho that was not challenged when their NPP
MP lost the NPP primary and switched to Independent status. In other words, NPP voters in
Bosome Freho did not switch their votes to an Independent candidate for ideological reasons,
but rather felt they were still voting for the NPP. Ketu South, on the other hand, is more
225
committed to the NDC than it’s NDC stronghold counterpart, Adaklu Anyigbe, whose residents
were willing to let their local tribal rivalries supersede their love for the NDC. The strong
tribal rivalries that do exist in Ketu South become subsumed in politics leading up to the NDC
primary, rather than translating to tribal support of an Independent candidate or another party.
Further, small discernible differences between responses from the Competitive Districts make
it difficult to pinpoint how respondents from these districts differ. But one notable difference
is that when describing the NPP ideology, respondents from Mfantsiman were more likely
to associate the party with the Rich/Elite while respondents from AOB were more likely to
associate the party with the Working Class/Poor. These perceptions likely explain some of
attachment to the NPP in AOB as compared to Mfantsiman.
Moving forward, the next chapter uses multinomial logistic regression models to predict
respondents’ vote choices and logistic regressions to predict swing voters.
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Table 6-1. Survey population stats vis-a-vis the 2010 Ghana Census
District Datatype
Avg.age(SD.)*
Female Ethnicgroup
Noformalschool
Primaryrate
Sec.rate
Post-sec.rate
Cell own Internetuse
B.F. Survey 39.5(14.8)
52.68% Asante,76.90%
16.04% 26.73% 53.46% 3.77% 69.40% 7.89%
B.F. Census 37.03(16.15)
50.74% Asante,72.50%
30.85% 12.18% 53.53% 3.44% 36.91% 1.90%
B.S. Survey 41.5(15.2)
50.78% Akyem,55.38%
20.82% 23.66% 49.84% 0.63% 82.08% 11.64%
B.S. Census 37.01(17.17)
51.59% Akyem,62.85%
24.99% 14.16% 57.09% 3.76% 47.91% 6.02%
A.A. Survey 40.6(16.3)
49.55% Ewe,94.24%
11.75% 12.65% 65.96% 9.64% 79.03% 14.16%
A.A. Census 40.13(17.87)
51.40% Ewe,88.54%
25.80% 16.07% 53.73% 4.40% 39.20% 2.00%
K.S. Survey 42.6(15.8)
42.63% Ewe,96.81%
13.74% 15.02% 61.98% 9.27% 89.71% 25.81%
K.S. Census 40.13(17.87)
52.94% Ewe,96.89%
33.62% 17.39% 44.92% 4.07% 53.52% 4.25%
Mf.** Survey 37.6(14.0)
53.16% Fante,93.08%
14.20% 33.40% 55.84% 7.57% 78.55% 14.70%
Mf. Census 38.82(17.27)
55.02% Fante,90.82%
33.11% 10.91% 50.51% 5.47% 49.91% 4.82%
AOB Survey 40.3(15.2)
51.13% Fante,67.31%***
13.38% 24.20% 55.10% 7.32% 72.35% 7.72%
AOB Census 38.82(17.27)
51.83% Fante,86.02%
27.81% 13.81% 54.34% 4.04% 42.04% 2.09%
*Census Average Age and Std. Dev. is calculated at the Regional level due to data availability.**The Mfantsiman survey was only distributed in Mfantsiman West, and not the entire Mfantsiman District.***Many respondents in the AOB District identify as Breman, which GSS does not consider as distinct from Fante.If we add Bremans and Fantes survey respondents together, the population percentage increases to 84.6%.Source: 2010 Census, Ghana Statistical Services
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Table 6-2. Bosome Freho & Birim South structural characteristics
District Tribe, % Eng.literacy
Agric.households
Rural Cell phoneownership
Internetuse
BosomeFreho
Asante,71.5%
48.3% 81.6% 100% 36.9% 1.9%
BirimSouth
Akyem,61.6%
61.5% 78.2% 52.5% 47.9% 6.0%
NationalAvg.
62.0% 45.8% 49.1% 56.2% 8.4%
Source: 2010 Census, Ghana Statistical Services
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Table 6-3. Bosome Freho & Birim South presidential vote patterns
2012 Presidential 2008 Presidential 2004 Presidential VolatilityDistrict NDC NPP 3rd NDC NPP 3rd NDC NPP 3rdBosomeFreho
24.9% 73.4% 1.68% 19.3% 78.1% 2.58% 16.8% 82.1% 1.04% 3.75
BirimSouth
32.7% 66.0% 1.26% 31.6% 67.2% 1.25% 25.4% 73.5% 1.11% 0.80
Source: Ghana Electoral Commission
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Table 6-4. Bosome Freho & Birim South parliamentary vote patterns
2012 Parliamentary 2008 Parliamentary 2004 Parliamentary Volatility
District NDC NPP 3rd NDC NPP 3rd NDC NPP 3rdBosomeFreho
22.1% 57.8% 20.1% 11.2% 41.4% 47.3% 17.3% 81.9% 0.84% 24.6
BirimSouth
31.0% 59.8% 9.18% 35.7% 63.6% 0.76% 31.0% 67.4% 1.6% 4.38
Source: Ghana Electoral Commission
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Table 6-5. Adaklu-Anyigbe & Ketu South structural characteristics
District Tribe, % Eng.literacy
Agric.households
Rural Cell phoneownership
Internetuse
AdakluAnyigbe
Ewe,83.3%
56.9% 76.7% 89.4% 39.2% 2.0%
KetuSouth
Ewe,90.8%
57.1% 21.4% 53.4% 53.5% 4.3%
NationalAvgs.
62.0% 45.8% 49.1% 56.2% 8.4%
Source: 2010 Census, Ghana Statistical Services
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Table 6-6. Adaklu-Anyigbe & Ketu South presidential vote patterns
2012 Presidential 2008 Presidential 2004 Presidential VolatilityDistrict NDC NPP 3rd NDC NPP 3rd NDC NPP 3rdAdakluAnyigbe
91.5% 6.80% 1.68% 91.1% 5.91% 2.99% 90.7% 7.53% 1.76% 0.98
KetuSouth
93.1% 5.88% 0.98% 93.8% 4.67% 1.56% 92.4% 6.70% 0.92% 1.08
Source: Ghana Electoral Commission
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Table 6-7. Adaklu-Anyigbe & Ketu South parliamentary vote patterns
2012 Parliamentary 2008 Parliamentary 2004 Parliamentary VolatilityDistrict NDC NPP 3rd NDC NPP 3rd NDC NPP 3rdAdakluAnyigbe
82.7% 8.22% 9.10% 55.5% 3.11% 41.4% 45.1% 7.17% 47.8% 14.2
KetuSouth
88.9% 4.71% 6.37% 89.7% 5.65% 4.66% 68.4% 6.82% 24.8% 7.66
Source: Ghana Electoral Commission
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Table 6-8. Mfantsiman* & Asikuma-Odoben-Brakwa structural characteristics
District Tribe, % Eng.Literacy
Agric.Households
Rural Cell PhoneOwnership
InternetUse
Mfantsiman Fante,88.6%
60.9% 37.9% 49.6% 49.9% 4.8%
AOB Fante,84.2%
62.7% 83.0% 51.9% 42.0% 2.1%
NationalAvgs.
62.0% 45.8% 49.1% 56.2% 8.4%
Source: 2010 Census, Ghana Statistical Services*Note: Due to a clerical error, surveys were only collected in Mfanstiman West, whereasMfanstiman District consists of both Mfantsiman West and Mfanstiman East/Ekumfi.
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Table 6-9. Mfantsiman* & Asikuma-Odoben-Brakwa presidential vote patterns
2012 Presidential 2008 Presidential 2004 Presidential VolatilityDistrict NDC NPP 3rd NDC NPP 3rd NDC NPP 3rdMfantsiman54.7% 42.9% 2.41% 56.5% 40.6% 2.98% 43.9% 54.6% 1.55% 8.45AOB 49.8% 48.6% 1.67% 47.7% 49.5% 2.73% 34.5% 63.9% 1.56% 5.49Source: Ghana Electoral Commission*The electoral data presented here refers to Mfantsiman West, and not the entire Mfantsiman District.
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Table 6-10. Mfantsiman* & Asikuma-Odoben-Brakwa parliamentary vote patterns
2012 Parliamentary 2008 Parliamentary 2004 Parliamentary VolatilityDistrict NDC NPP 3rd NDC NPP 3rd NDC NPP 3rdMfantsiman51.0% 47.2% 1.35% 52.1% 45.6% 2.27% 41.4% 56.6% 2.0% 6.05AOB 51.9% 45.8% 2.27% 47.8% 49.0% 3.22% 40.1% 58.3% 1.63% 8.61Source: Ghana Electoral Commission*The electoral data presented here refers to Mfantsiman West, and not the entire Mfantsiman District.
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Table 6-11. Q9: Three biggest reasons for your vote for President
Responsecategory
Frequency Percent Percent ofcases1
N
Economic Policy 1,285 28.86% 71.19% 1,805Social Policy 1,385 31.11% 76.73% 1,805Candidate/VPApproval
993 22.30% 55.01% 1,805
PoliticalParty/Legacy
601 13.50% 33.30% 1,805
Particularistic/Ethnic
108 2.43% 5.98% 1,805
Voting forvoting’s sake
61 1.37% 3.38% 1,805
Clientelistic 11 0.25% 0.61% 1,805Disapproval ofCurrent Gov.
8 0.18% 0.44% 1,805
Total 4,452 100% 246.64%1Respondents were allowed to give more than one answer for this question. Percent of Casesrefers to the percentage of individuals in the sample who gave that response category.
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Table 6-12. Q13: Three biggest reasons for your vote for MP
ResponseCategory
Frequency Percent Percent ofCases1
N
Economic Policy 1,113 36.22% 62.81% 1,772Social Policy 1,205 39.21% 68.00% 1,772CandidateApproval
1,249 40.64% 70.49% 1,772
PoliticalParty/Legacy
569 18.52% 32.11% 1,772
Particularistic/Ethnic
143 4.65% 8.07% 1,772
Voting forvoting’s sake
35 1.14% 1.98% 1,772
Clientelistic 2 0.07% 0.11% 1,772Disapproval ofCurrent Gov.
6 0.20% 0.34% 1,772
Total 3,073 100% 243.91%1Respondents were allowed to give more than one answer for this question. Percent of Casesrefers to the percentage of individuals in the sample who gave that response category.
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Table 6-13. Q10: Biggest reason driving presidential votes within this community?
Responsecategory
Frequency Percent percent ofcases1
N
Economic Policy 482 26.00% 26.48% 1,820Social Policy 758 40.88% 41.65% 1,820Candidate/VPApproval
367 19.80% 20.16% 1,820
PoliticalParty/Legacy
193 10.41% 10.60% 1,820
Particularistic/Ethnic
20 1.08% 1.10% 1,820
Voting forvoting’s sake
25 1.35% 1.37% 1,820
Clientelistic 6 0.32% 0.33% 1,820Disapproval ofCurrent Gov.
3 0.16% 0.16% 1,820
Total 1,854 100% 101.85%1Respondents sometimes gave more than one answer for this question. Percent of Casesrefers to the percentage of individuals in the sample who gave that response category.
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Table 6-14. Q20: Do Ghana’s political parties have different ideologies?
Response category Frequency Percent
Very different 1,478 82.48%Somewhat different 239 13.34%No difference 75 4.19%Total 1,792 100%
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Table 6-15. Q21: Components of the NDC’s political ideology
Response category Frequency Percent Percent of cases1 N
Socialism/ socialdemocracy
585 19.95% 38.14% 1,534
Working class/ poor/masses
123 4.19% 8.02% 1,534
Rich/elite 39 1.32% 2.54% 1,534Ewes/ Muslims/Northerners
259 8.86% 16.88% 1,534
Better Ghana Agenda 1,106 37.71% 72.10% 1,534Development 672 22.91% 43.81% 1,534Non-policy negative 70 2.39% 4.56% 1,534General party descriptor 18 0.61% 1.17% 1,534Social policy/ particulardev. projects
57 1.94% 3.72% 1,534
Founding leaders/traditions
4 0.14% 0.26% 1,534
Total 2,933 100% 191.20%1Respondents were allowed to give more than one answer for this question. Percent of Casesrefers to the percentage of individuals in the sample who gave that response category.
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Table 6-16. Q22: Components of the NPP’s political ideology
Response category Frequency Percent Percent of cases1 N
Market-oriented/laissez-faire economy
389 14.19% 23.58% 1,650
Working class/ poor/masses
225 8.21% 13.64% 1,650
Rich/ elite 132 4.82% 8.00% 1,650Asantes/ Akans 182 6.64% 11.03% 1,650Free SHS education 1,274 46.48% 77.21% 1,650Development 483 17.62% 29.27% 1,650Non-policy negative 16 0.58% 0.97% 1,650General party descriptor 10 0.36% 0.61% 1,650Social policy/ particulardev. projects
23 0.84% 1.39% 1,650
Founding leaders/traditions
2 0.01% 0.12% 1,650
Economic policy 5 0.18% 0.30% 1,650Total 2,741 100% 166.12%1Respondents were allowed to give more than one answer for this question. Percent of Casesrefers to the percentage of individuals in the sample who gave that response category.
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CHAPTER 7PREDICTING RESPONDENTS’ VOTES AND SWING-VOTING
In this chapter I use respondents’ self-report voting history to predict individual-level votes
and swing voting across the 2004, 2008 and 2012 Presidential and Parliamentary elections.
My overall argument is that the level of political competition at Ghana’s sub-national level is
increasing due to the presence of centrally-appointed DCEs and locally-elected MPs of different
political parties. When these officials are of different political parties, which occurs anytime
the President, and by extension the centrally-appointed DCEs, are of a different political party
than the locally-elected MP, the DCE and MP compete for constituency support. When these
officials are of the same political party, that level of competition is diminished.
Generally speaking, local-level competition is higher in Ghana’s Fourth Republic, and
particularly since the end of Rawling’s presidency in 2000, than in past regimes. Five of
the six districts in the survey have experienced an Unfriendly DCE-MP pair.1 As political
competition increases locally, voters have the opportunity to use contextual candidate and
party evaluations, as opposed to relying on party tradition and ethnic backgrounds, when
casting their votes. Further, when faced with real experiential information about two viable
candidates, increased political competition should also theoretically lessen the extent to which
clientelistic-inducements are effective at persuading citizens for their votes.
The models I present systematically test for Identity-Based (Hypothesis 1), Policy or
Economic-Based (Hypothesis 2), and Clientelistic-Based (Hypothesis 3) voting rationales.
To test for individual votes I use multinomial logistic regressions, where votes for the NPP
1 It is only in Mfantsiman, a competitive district which elected a NPP MP in 2000 and 2004and a NDC MP in 2008 and 2012 which has not experienced a competitive DCE-MP pair sincethe 2000 elections. However, unlike the NPP and NDC strongholds in the sample, local-levelcompetition is likely to be inherently high given the close elections in the constituency and theelection of MPs of different political parties.
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(reference category), NDC, and Third party are predicted.2 To analyze swing voting, I
first provide descriptive analysis of the demographic characteristics linked to swing voting.
I then use Logit Models to predict swing voters as compared to stable voters. Overall, the
analysis presented in this chapter provides support for Hypothesis 1 and Hypothesis 2, but not
Hypothesis 3.
The general findings for individual vote predictions are that respondent ratings of the
current and past government’s handling of the economy and success at bringing development
to the area are strong predictors of respondent votes. Additionally, particular tribes, namely
Asante, Akyem, Other Akan, and Ewe, were consistent predictors of respondent votes,
providing support for Hypothesis 1: Identity-Based Voting. However, when comparing these
variables against one another in terms of changes in predicted probabilities of having voted
for a particular political party, economic and developmental evaluations generally had a larger
effect on vote choice than did tribal or ethno-linguistic group membership. Further, the effect
of tribal group membership on predicted probabilities of voting for the NPP versus the NDC
was significantly diminished for Parliamentary races as compared to Presidential races. The
effect of economic or developmental evaluations on changes in predicted probabilities of voting
for particular political parties was consistent over time.
Of the tribes which did have a large effect on predicted probabilities of having voted for
the NPP versus the NPP were limited to the Asante and Akyem tribes, while the effect of
Fante, Other Akan, Ewes, and Mole Dagbani group membership were much smaller. This
might suggest that the effects of political competition differ across ethnic groups. Finally,
respondents who identified the NDC as the political party most known for giving out more
gifts (i.e. a test for Hypothesis 3: Clientelistic-Based Voting) were significantly associated with
2 Third party votes have become very scarce in Ghana’s two-party dominant system.Throughout the analysis I focus on the likelihood of having voted for the NDC, as comparedto the NPP reference category, rather than the likelihood of having voted for a Third party.
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increased NPP over NDC votes across elections. This suggests that respondents understand
that giving out gifts has negative implications for political parties, thus refuting evidence for
Clientelistic-Based Voting.
The general results for the swing voting analysis shows that overall swing voting occurred
least among respondents in the NDC strongholds. Election-to-election swing voting was
overall more common than skirt and blouse swing voting (i.e. votes for different parties in the
Presidential and Parliamentary elections within the same year). Finally, in the logit models
predicting swing voters, there is some small evidence that identity and clientelistic-inducements
impact swing voting (Hypotheses 1 and 3), and more evidence that Policy and Economic
considerations impact swing voters (Hypothesis 2).
7.1 Predicting Votes
For each election, in Model 1 I test for standard demographic indicators including age,
gender, religion, and three development/class indicators: Internet use3 or cell phone ownership
(cell own)4 , whether water is available inside the home compound (water inside)5 , and
whether farming is a respondents’ primary occupation. I also add dummy variables for the 6
districts in which the surveys were collected. Asikuma Odoben Brakwa is used as the reference
category because, as a competitive district, it was less skewed to one party as were the party
strongholds. Asikuma Odoben Brakwa is slightly more NPP-leaning than its competitive pair
counterpart, Mfantsiman. Note that because districts were selected with an eye to their ethnic
3 For this question, respondents were asked if they ever used the Internet. This variable iscoded dichotomously where 1 refers to Yes and 0 refers to No.
4 In this indicator, 1 refers to respondents who use a mobile phone that they own. 0 refersto respondents who either do not use a mobile phone or use a mobile phone owned by someoneelse. Internet use and Cell Phone Ownership were never included within the same modelbecause they are too highly correlated.
5 Coded dichotomously, 1 refers to respondents whose main source of water is inside thecompound, either from a polytank or pipes, while 0 refers to those whose main source of wateris found outside the home compound.
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population makeup, the district dummy variables are too correlated with ethnic groups to keep
both within the same model.
In the second model (Model 2) of each election analysis, I add ethnic group information
to test for Hypothesis 1: Identity-Based Voting. In particular, I break the Akan ethno-linguistic
group into ‘Asante’, ‘Fante’, ‘Akyem’, and ‘Other Akan’ tribes, so that I can control for
dominant tribal groups in the Bosome Freho (Asante), Birim South (Akyem), Mfantsiman
(Fante), and AOB (Fante) districts. I also include Ewe, the dominant ethno-linguistic group in
Adaklu Anyigbe and Ketu South, Guan, Mole Dagbani, and Others (i.e. Gruma, Grusi, Mande,
and Other Tribes (as captured by the 2010 Ghana Census)). The reference category used is
Ga-Dangme, a group that sometimes leans toward the NDC in its voting patterns, but is not
known for overwhelmingly supporting one party or another.
In Model 3 I added two political behavior controls: whether respondents vote for the same
party all the time (1) or sometimes/always change their votes (0) (vote stays the same) and
whether or not respondents believe Ghana’s political parties have different ideologies (diff.ideo).
In the 2012 models, I also added a political activism measure in whether or not the respondent
watched either of the two Presidential Debates prior to the 2012 election (debate6 ).7
Finally, in Model 4 I add economic perceptions about the present and past regimes’
handling of the economy (2000 NPP Econ.; 2008 NDC Econ.; 2012 NDC Econ.) and
evaluations of how likely the 2012 NDC government would bring development (2012 NDC
6 It is important to note that the phrasing of the question was, “Did you watch either ofthe Presidential debates just before the 2012 election?”. It came to the attention of the surveyteam that respondents may have listened to the debates on the radio, rather than watchedthem on TV. Surveyors were thus instructed to count the question as Yes if the respondentlistened to one of the debates. Overall, about 43.0% of the entire sample said they watched orlistened to at least one of the two Presidential debates.
7 A variable that was excluded from the analysis was whether or not an individual was amember of the NDC or NPP. This variable was excluded because the correlations ran too high(i.e. >0.75).
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Dev.) or how successful past regimes have been at bringing development to the respondents’
area (2000 NPP Dev.; 2008 NDC Dev.). These sets of questions are the closest to estimating
respondent perceptions about the successes or failures of past governments
In addition to the evaluative questions, Model 4 also tests for the impact of family
influences on voting (family votes the same), and whether one party has a bigger reputation for
giving out gifts (NDCgifts, coded as 1 if the respondent identified the NDC and 0 if another
party or no party was identified).
7.1.1 2004 Presidential and Parliamentary Elections
Results from the analysis of respondent votes in the 2004 Presidential (Table 7-1) and
Parliamentary (Table 7-2) elections provide support for Hypothesis 1: Identity-Based voting,
with significant ethnic and family vote predictors. Similarly, evaluations of regimes’ economic
and developmental success were also significantly related to respondents’ votes. Finally,
responses for a question asking about the political party with the biggest reputation for giving
out gifts finds that respondents report the political parties which they do not vote for. Not
only does this fail to provide evidence for Hypothesis 3: Clientelistic-Based Voting, but it
suggests that clientelistic-inducements may even harm a party’s chances on Election Day.
The first two models for both the Presidential and Parliamentary sets of analysis test
for demographic control variables, district controls, and ethnic identities. In both tables, cell
phone ownership is the only significant predictor of votes across both models, with ownership
decreasing the relative risk ratio of having voted for the NDC over the NPP by a factor of .762
(.677) in the 2004 Presidential (Parliamentary) election.8 In both of the 2004 races (Tables
7-1 and 7-2) the district variables in Model 1 show that respondents from the NPP strongholds
(NDC strongholds) were less likely to (more likely to) vote for the NDC over the NPP, in
comparison to the Asikuma Odoben Brakwa reference category. Similarly, the competitive yet
8 Relative risk ratios are calculated by exponentiating the multinomial logit coefficients(ecoef ).
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NDC-leaning Mfantsiman District respondents were more likely to vote for the NDC over the
NPP as compared to the competitive yet NPP-leaning Mfantsiman District reference category.
In Model 2, I evaluate ethnic predictors of vote choice. In the 2004 Presidential election,
the relative risk ratio of having voted for the NDC over the NPP would be expected to
decrease by a factor of 0.059, 0.142, and 0.165 for members of the Ashanti, Akyem, and Other
Akan tribes, and increase by a factor of 7.39 for members of the Ewe ethno-linguistic group, as
compared to the Ga-Dangbe reference category. In the 2004 Parliamentary election, the relative
risk ratio decreased by a factor of 0.057, 0.144, and 0.196 for members of the Ashanti, Akyem,
and Other Akan tribes and increase by a factor of 7.10 for members of the Ewe ethno-linguistic
group, again as compared to Ga-Dangbe respondents. The risk ratios are very similar in both
races.
In Model 3, I add variables for whether respondents say they vote for the same political
party always and whether respondents believe the political party ideologies in Ghana are
different. In both races, Models 3 and 4 show that respondents who say they vote for the same
political party over time are significantly more likely to vote for the NDC over the NPP.
In Model 3, two ethnic variables in the Presidential and Parliamentary analyses became
significantly related to respondent vote choice. First, Fante tribe members were significantly
less likely to vote for the NDC over the NPP in 2004, in comparison to the Ga-Dangbe
reference category, though the coefficient was much smaller than the other Akan tribes.
The effect of this variable dropped out after controlling for additional variables in Model 4.
Members of the Mole Dagbani ethno-linguistic group were also more likely to vote for the NDC
over the NPP, in comparison to the reference category.
Finally, to evaluate the different hypotheses against one another, in Model 4 I test the
ethnic variables (Hypothesis 1) against economic and developmental performance evaluations
(Hypothesis 2) and whether any political party had a reputation for giving out more gifts
(Hypothesis 3). Except in the case of Fantes, the ethnic variables which were significant
in Model 3 were also significant in Model 4, but the strength of the coefficients generally
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lessened. In addition to the ethnic variables I include a family vote variable for whether
members of a respondent’s family vote the same as the respondent. Table 7-1 Model 4 shows
that if a respondent’s family does vote the same as there respondent, the relative risk ratio of
having voted for the NDC over the NPP would be expected to decrease by a factor of 0.631.
This provides some evidence that politics is affected by familial ties, though this variable is not
significant in the 2004 Parliamentary vote analysis.
Second, when asked to rate the past 2000-2008 NPP government’s handling of the
economy, a one-unit increase towards a more positive evaluation decreased the relative risk
ratio of having voted for the NDC over the NPP by a factor of 0.292 in the Presidential
election and 0.304 in the Parliamentary election. Similarly, a one-unit increase in the positive
evaluation of how successful the 2000-2008 NPP government was at bringing development
to the respondent’s area translated to a decreased relative risk ratio of voting for the NDC
over the NPP in 2004 by a factor of 0.497 (Presidential) and 0.487 (Parliamentary), a less
significant effect as compared to the economic evaluation.
Third, when asked if any political party had a reputation for giving out more gifts, if
respondents selected the NDC, they were significantly less likely to have voted for the NDC
over the NPP in the 2004 Presidential elections. In other words, when respondents identified
a political party as giving out more gifts this was more an accusation of corruption than a
positive evaluation of the political party identified.
Finally, Figures 7-1 and 7-2 displays the change in predicted probabilities for having voted
for the NPP (0), NDC (1) or a third party (3) in the 2004 Presidential and Parliamentary
elections using the data from Model 4 in Tables 7-1 and 7-2. The variables being compared are
the significant tribal/ethnic variables and the economic and developmental regime evaluations.
In -1, for instance, moving from a non-Asante respondent to an Asante respondent changed
the predicted probability of having voted for the NPP in the 2004 Presidential election
by about 0.40. Similarly, moving from a ‘Very Badly’ evaluation of the 2000-2008 NPP
government’s handling of the economy to a ‘Very Well’ evaluation, or 0 to 3, changed the
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predicted probability that a respondent voted for the NPP in the 2004 Presidential race by
about 0.65. In general, as pertains to the 2004 Presidential election analysis, the distance
between the NPP and the NDC was is greatest for the economic evaluation. There is a
similar predicted probability distance separating the NPP from the NDC for the developmental
evaluation variable and the Asante, Akyem, and Mole Dagbani tribal variables. The distance
between the NPP and NDC is smallest for Ewe and other Akan respondents. This overall
suggests that at least the economic evaluation had a greater impact on determining respondent
votes than did ethnicity, while the developmental evaluation was about even with three
different tribes.
Turning to the change in predicted probabilities for the 2004 Parliamentary election
(Figure 7-2), however, shows that a respondents’ economic evaluation and developmental
evaluation had a larger impact on votes than did any of the tribal/ethno-linguistic groups.
Only the Mole Dagbani variable comes close to the same distance separating the NPP from
the NDC as the developmental evaluation. Moving from a ‘Very Badly’ evaluation of the
2000-2008 NPP regime’s handling of the economy to a ‘Very Well’ evaluation increased
the probability of a respondent having voted for the NPP by about 0.63 and decreased the
probability of a respondent having voted for the NDC by about -0.66.
Overall, Hypothesis 2 is supported in the multinomial regression models and the predicted
probabilities figures show that developmental and particularly economic evaluations of a
regime are a greater determinant of vote choice than ethnicity. Still, tribal and ethno-linguistic
variables have relationship to vote decisions (Hypothesis 1). Finally, Hypothesis 3: Clientelistic-Based
Voting is challenged in that respondents were significantly more likely to identify the political
parties which they did not vote for as opposed to the parties they favored.
7.1.2 2008 Presidential and Parliamentary Elections
The district variables in Tables 7-3 and 7-4, Model 1 are similar to those predicting NDC
over NPP votes in the 2004 Presidential and Parliamentary elections (Tables 7-1 and 7-2,
Model 1), except the sizes of the coefficients when predicting NDC over NPP votes in the
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2008 Presidential election were generally smaller. The only exception to this is the decreased
likelihood that respondents in Birim South voted for the NDC over the NPP in the 2008
elections as compared to the 2004 elections. Similarly, testing for ethnic variables in Tables 7-3
and 7-4, Model 2 provides similar results as compared to the 2004 Presidential election (Tables
7-2, Model 2), but again the coefficients are smaller.
In Models 3 and 4, for the 2008 Presidential election (Table 7-3) cell-phone owners were
less likely and individuals who vote the same were more likely to vote for the NDC over the
NPP. These two variables are also significant for the 2008 Parliamentary race (Table 7-4),
except now older respondents, those who practice Islam, and those who believe the political
party ideologies in Ghana are very different are also more likely to have voted for the NDC over
the NPP.
Finally, Model 4 tests for Hypotheses 1, 2, and 3 against one another. First, the ethnic
variables in Tables 7-3 and 7-4, Model 1 are similar to those in the 2004 Presidential and
Parliamentary analyses, except now the strength of the coefficients is generally increased. Now,
the relative risk ratio of voting for the NDC over the NPP in 2008 decreased by a factor of
0.047, 0.326, 0.103, and 0.112 (0.045, 0.295, 0.100, and 0.095) for members of the respective
Ashanti, Fante, Akyem, and Other Akan tribes, decreased by a factor of 0.177 (0.144) for
members of the Mole Dagbani ethno-linguistic group, and increased by a factor of 3.22 (3.25)
for members of the Ewe ethno-linguistic groups, in comparison to the reference category, for
the 2008 Presidential (Parliamentary) election. For both elections, in comparison to 2004
the size of the ethnic coefficients increased in 2008 for Ashantis, Fantes, Akyems, and Other
Akans, but decreased for Ewes and Mole Dagbanis. This provides evidence that identity-based
voting is still in effect in 2008, and possibly that tribal identities are becoming more relevant.
Now in Model 4, family voting no longer significantly affects the 2008 vote choices. A
one-unit increase in the rating of the 2008 NDC government’s handling of the economy and
success at bringing development to the area increased the relative risk ratio of having voted
for the NDC over the NPP by a factor of 2.01 and 2.39 in the Presidential elections and 2.23
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and 2.27 in the Parliamentary elections, respectively. Finally, identifying the NDC as the party
with the biggest reputation for giving out gifts decreased the relative risk ratio of having voted
for the NDC over the NPP by a factor of 0.458 and 0.477 in the respective Presidential and
Parliamentary races.
Finally, Figures 7-3 and 7-4 show the change in predicted probabilities for having voted
for a political party in the 2008 Presidential and Parliamentary elections. Now, in the 2008
Presidential election analysis, the developmental evaluation of the 2008 NDC regime has a
larger impact on the change in predicted probability of having voted for the NPP vs. the NDC
than does the economic evaluation. Further, one tribe, the Asantes, has just as big an impact
on the predicted probability of having voted for the NPP vs. the NDC as the developmental
evaluation. Akyems were the tribe with the second largest impact, and about as large an
impact as the economic evaluation, while the effect of Fantes, Other Akans, and Ewes were
smaller than the economic and developmental evaluations.
For the 2008 Parliamentary election analysis (Figure 7-4), the effect of tribal and
ethno-linguistic groups is smaller than both the economic and developmental evaluations.
The impact of being Akyem still has a large effect on the predicted probability of voting for
the NPP (about 0.50) and the NDC (about -0.46). The distances separating the predicted
probabilities of voting for NPP from the NDC is much smaller for members of the Asante,
Fante, Other Akan and Ewe groups as compared to the economic and developmental
evaluations.
In the 2008 voting models, increased support for Hypothesis 1: Identity-Based Voting
comes in the way of increased sizes of the coefficients for the pro-NPP Akan tribal groups
and decreased sizes of the coefficients for the Ewe and Mole Dagbani ethno-linguistic
groups. Support for evaluation-based impacts on voting, per Hypothesis 2: Policy-Based
and Economic-Based Voting, again has support in the 2008 Presidential and Parliamentary
vote models, except now development-evaluations has a larger impact on votes than
economic-evaluations. However, when we look at the change in predicted probabilities for
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these variable simultaneously, we see that the economic, and particularly the developmental,
evaluations of the 2000-2008 NPP government had just as big an impact, and often a larger
impact, than did tribal/ethno-linguistic group membership. Finally, identifying the NDC as the
party with the reputation for giving out the most gifts again decreases the relative risk ratio of
having voted for the NDC over the NPP in 2008, further diminishing support for Hypothesis 3.
7.1.3 2012 Presidential and Parliamentary Elections
Finally, in Model 1 of Tables 7-5 (2012 Presidential) and 7-6 (2012 Parliamentary), the
district-level variables were in the same direction as prior models. In both Models 1 and 2 of
the 2012 Presidential election voting analysis (Table 7-5), cell-phone owners are again less
likely to have voted for the NDC over the NPP, while internet users in Models 1 and 2 of the
Parliamentary election (Table 7-6) also decreased the likelihood of a voting for the NDC over
the NPP. Models 3 and 4 of both the 2012 Presidential and Parliamentary elections also found
that internet users were significantly less likely to vote for the NDC over the NPP in the 2012
Presidential elections.9 Another change is that Model 4 in Table 7-5 (Table 7-6) now shows
that a unit increase in whether a respondent believes Ghana’s political parties to have different
ideologies increases the relative risk ratio of having voted for the NDC over the NPP by a
factor of 1.65 (1.99).
The ethnic variables in the 2012 Presidential and Parliamentary Models 2-4 are again
significant in the expected directions. However, now in Model 4 the size of the tribal
coefficients decreased from the 2008 Presidential and Parliamentary coefficient sizes, while
the Ewe ethno-linguistic variable coefficient increased in both of the 2012 models as compared
to 2008. The Mole Dagbani ethno-linguistic variable is now an insignificant predictor of
votes. Overall, the relative risk ratio of having voted for the NDC over the NPP in the 2012
Presidential (Parliamentary) election decreased by a factor of 0.124, 0.214, and 0.336 (0.
9 The variable ‘Internet Users’ was not significant in past election models, so ‘Cell PhoneOwnership’ was instead used.
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145, 0.183, and 0.326) for Ashantis, Akyems and Other Akans and increased by a factor of
4.53 (4.81) for Ewes, as compared to the Ga-Dangbe reference category. In both of the 2012
elections (Tables 7-5 and 7-6), family-voting now longer significantly predicted respondents’
vote choices.
A unit increase toward more positive evaluations of the 2012 NDC government’s handling
of the economy and success at bringing development to the respondent’s area increased the
relative risk ratio of having voted for the NDC over the NPP in the 2012 Presidential race by
a factor of 2.66 and 2.10, and in the 2012 Parliamentary race by a factor of 2.77 and 2.14,
respectively. Finally, naming the NDC as the political party with the biggest reputation for
giving out more gifts decreased the relative risk ratio of having voted for the NDC over the
NPP by a factor of 0.445 in the Presidential race and by a factor of 0.436 in the Parliamentary
race.
Finally, Figures 7-5 and 7-6 use Model 4 from Tables 7-5 and 7-6 to analyze the change
in predicted probability for having voted for a political party in the 2012 Presidential and
Parliamentary elections. In both the Presidential and Parliamentary election analysis, economic
and developmental evaluations had a bigger impact on the change in predicted probability for
having voted for the NPP vs. the NDC than did any tribal or ethno-linguistic group. The tribe
with the largest effect in the 2012 Presidential election was the Asantes, while there was no
tribe or ethno-linguisitc group even close to the degree of predicted probability change in voting
for the NPP vs. the NDC as the economic and developmental evaluators.
Again, Hypotheses 1 and 2 are supported in the 2012 Presidential voting analyses,
but Figures 7-5 and 7-6 suggest that the economic and developmental evaluations of party
performance actually had greater influence on voting for the NPP versus the NDC as compared
to the tribal and ethno-linguistic groups. Finally, evidence is again lacking for Hypothesis 3.
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7.2 Who Are The Swing Voters?
About 16% of the sample10 voted for two or more different parties some time during the
1996-2012 Fourth Republic elections. Swing voting is defined as votes for different parties in
the Presidential or Parliamentary races in different years (i.e. election-to-election swing voting)
as well as votes for different parties in the Presidential and Parliamentary elections within the
same year (i.e. skirt and blouse swing voting). In this section I analyze identity trends for these
self-admitted swing voters (Hypothesis 1), as well as whether policy or economic performance
(Hypothesis 2) or Clientilestic inducements (Hypothesis 3) impacted a respondents’ decision to
swing their vote.
7.2.1 Demographic Trends
First, as shown in Table 7-7, the district sample with the greatest proportion of swing
voters is Mfantsiman with 21.6%. This makes logical sense in that Mfantsiman is a competitive
electoral constituency. However, AOB is also a competitive electoral constituency yet only
16.8% of respondents from AOB reported swing voting behavior. Indeed this 16.8% is behind
the 18% and 17.8% portion of the Bosome Freho and Birim South respective respondents who
engaged in swing voting behavior. The respondents least likely to report swing voting behavior
were the NDC strongholds, Adaklu Anyigbe with 11.5%, and Ketu South with 9.9%.
Also in Table 7-7, though the vast majority of swing voters are not political party
members (89.6%) but a surprising 10.4% of the self-declared party members did vote for
2 different political parties at some point in their personal voting histories. Further, voters
who only vote for one party do not necessarily consider themselves party members; 61.4% of
non-party members have only voted for 1 political party in their voting history. The largest
10 Respondents were excluded from the swing voter analysis if they had only voted in oneelection or if their voting data was missing. 221 respondents were excluded, leaving 1,711 outof 1,932 respondents for the analysis. 273 of 1,712 (15.96%) reported swing voting.
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percentage of swing voters lies in the non-political party member sample, with 38.6% of
non-party members also being swing voters.
There are no significant differences between gender (Table 7-7) and education (Table 7-8)
groups and swing-voting. And though we might expect swing voters to be more critical of the
overall functioning of democracy in Ghana, swing voters appear only slightly less likely to rate
Ghana a Full Democracy or a Democracy with Minor Problems and slightly more likely to rate
Ghana a Democracy with Major Problems. These differences are significant at the p<0.1 level.
In Table 7-8, while 68.5% of swing voters said their vote Sometimes Changed or
Differed Every Election, a surprising 31.5% of swing voters said that they Vote for One Party.
Unsurprisingly, 93.9% of stable voters said they only Vote for One Party, while an interesting
6.1% of stable voters reported that their vote Sometimes Changed or Differed Every Election.
Swing Voters from our sample also appear to be less trusting of others. When asked “How
Much Do You Trust Your Relatives?”, 37.3% of Swing Voters selected ‘Not at All’ or ‘Just
a Little’, as compared to 25.8% of stable voters. Similarly, 62.6% of Swing Voters selected
‘Somewhat’ or ‘A Lot’ as compared to 74.3% of stable voters (p<0.00, Table 7-9). Swing
Voters were also somewhat less likely to say they trust their neighbors (p<0.1, (Table 7-10).
Finally, when respondents were asked if they trusted people who do not speak their same local
dialect, swing voters were both more likely to respond ‘Not at all’ and ‘A Lot’ as compared to
stable voters.
Finally I consider the timing of swing votes in the sample: skirt and blouse voting as
compared to election-to-election swing voting. Overall, a greater percentage of respondents
engaged in election-to-election swing voting than skirt and blouse voting. First, Table 7-11
shows the number of skirt and blouse swing voters in our sample by district and by year.
For three districts, Bosome Freho, Mfantsiman, and Asikuma-Odoben-Brakwa, the highest
proportion of respondents who engaged in skirt-and-blouse swing voting was in 2012. For two
other districts, Adaklu Anyigbe and Ketu South, the highest proportion of skirt-and-blouse
swing voters was in 2004. Finally, for Birim South, the highest proportion of skirt-and-blouse
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swing voting was in 1996. The average rate of skirt-and-blouse swing voting across the districts
was a high of 3.67% in 2012 and a low of 2.41% in 2008. Overall, the district with the highest
average proportion of respondents was AOB at 4.65% while the lowest was Ketu South at
1.65%.
Looking at election-to-election swing voters in Tables 7-12 and 7-13, the 2008 Presidential
and Parliamentary elections saw the highest average proportion of swing voters in the sample,
with 7.27% and 7.14% respective averages. The district with the highest average proportion
of election-to-election swing voters over time was Mfantsiman (8.83% Presidential, 8.58%
Parliamentary), with Birim South (8.07% Presidential, 8.27% Parliamentary) at a close second.
Ketu South was again the district with the lowest proportion of election-to-election swing
voters (3.81% Presidential, 3.46% Parliamentary).
7.2.2 Logit Models Predicting Swing Voters
Using logit models to predict binary-coded Swing Voters, I test for Identity-Based
(Hypothesis 1), Policy and Economic-Based (Hypothesis 2), and Clientelistic-Based (Hypothesis
3) contributions to vote decisions.11
11 In the course of this analysis you will notice that the original sample of swing voters/stablevoters has 1,712 observations, yet the full logit models’ observation numbers fall to a lowof 1,200. With about 500 observations missing, I was somewhat concerned about missingobservation bias. I generated binary variables for whether or not a response was missingfor the swing voter dependent variable as well as three independent variables with the mostmissing variables (Table D-1 in Appendix D)(Note that the district reference variable for eachmodel was selected based on which district had a median number of missing observationsfor the outcome in question.). Beginning with testing for missing-ness within swing votervariable (Model 1), age is negatively correlated with missing swing voter values. In otherwords, younger respondents had a greater likelihood of missing for the swing voter variable.But this makes sense considering respondents were excluded from the swing voter analysis ifthey did not have a chance to swing vote and this especially impacted first-time (i.e. younger)voters. Next, respondents whose main source of water was found inside the home as opposedto outside the home (water inside) was also positively correlated with missing swing voter data.This finding is perplexing as it suggests that those who are more well-off or live in urban areasare more likely to be excluded from the swing voter analysis, either because the did not respondor only voted in one election in the Fourth Republic. Finally, respondents in Adaklu Anyigbe
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First, Tables 7-14 and 7-15 show the Odds Ratios for the Logit Models predicting Swing
Voters. In Table 7-14, the models test for demographic controls and respondents’ districts in
Model 1, demographic controls and ethnicity in Model 2, and demographic controls, ethnicity,
regime performance indicators, and clientelistic voting indicators in Model 3. In Table 7-15,
Models 4-6 test for demographic controls, ethnicity, reasons for a respondent’s vote for
President (Model 4), for MP (Model 5), and for the community’s vote for President (Model
6), as well as clientelistic voting indicators. Overall, the analysis points to developmental and
economic evaluations of past regimes, as well as whether or not the NDC was identified as the
are more likely to be missing for swing voter and the effect is large. Overall 55 of 220 (25.0%)respondents with missing swing voter data were from Adaklu Anyigbe.Turning to the the party member variable analysis (Model 2) older respondents are less
likely to be missing from the party member variable. Those who attended a political partyrally are more likely to be missing from party member. Third, in Model3, those who attended apolitical party rally are also significantly less likely to be missing from Question 24 which askedif members of the respondents’ family voted for one political party or altered their votes acrosselections (family votes the same). This might mean that respondents with strong political partyinclinations also come from families with strong party ties, making the respondent more openabout talking about their families’ votes. ‘Water inside’ is again positively associated withmissing for Question 24/’family votes the same’. Finally, respondents from Birim South are lesslikely to be missing while respondents from Ketu South are more likely to be missing for thisquestion. Lastly, in Model 4, respondents who attended a political party rally are less likely tobe missing for Question 35: How likely is it that the current 2012 NDC government will bringdevelopment to this area? (2012 NDC Dev.). A district bias also exists for this question in thatthose from Bosome Freho are more likely to be missing while those from Adaklu are less likelyto be missing. Perhaps this can be taken to mean that NPP voters in Bosome Freho did notwant to admit that the NDC government might develop their area while respondents in AdakluAnyigbe, an NDC stronghold, had no problem answering the question.Overall, the swing voter models likely suffer some bias for greater inclusion of politically
active respondents, though those who attended a political rally are more likely to be missingfrom the party member question. Still, attending a political party rally had no significant effecton respondents’ missing from the swing voter data. Similarly it appears that those with accessto water from within their homes are more likely to be missing from the swing voter analysis.This is a surprising result, but perhaps those with greater water access and personal wealth aremore likely to withhold information about their or their families voting patterns (Models 1 and3). Finally, respondents from the NDC strongholds are more likely to be missing in the swingvoter logit models because of their greater missing-ness in the swing voter data and familyvotes data (Models 1 and 3).
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party with the biggest reputation for gifts, as the biggest determinants of swing voting outside
of demographic controls.
Beginning with Table 7-14, respondents who report that they vote for one party, party
members, and respondents who report that they vote the same as their family are each
significantly decrease the odds that a respondent is a swing voter. Further, respondents who
don’t trust their neighbors or who believe that their vote is not secret (e.g. ‘big’ men and
women can find out how they voted) also significantly decrease the odds that the respondent
is a swing voter. Finally, using Ketu South (e.g. the district with the lowest amount of swing
voting) as the reference category, it was only respondents from the NPP strongholds, Bosome
Freho and Birim South, that were significantly more likely to be swing voters. And while
Bosome Freho was selected for having voted in an Independent MP in 2008, its respondents
were less likely to be swing voters as compared to those in Birim South. This could be because
those who voted for Kuragu as an Independent MP in 2008 in Bosome Freho felt they were
voting for the NPP or because, though Birim South is a NPP stronghold, a sizeable population
sometimes votes for the NDC.
Switching out district variables for ethnic variables in Model 212 shows that, in
comparison to the Ga-Dangbe reference category13 , only Guan ethno-linguistic group
12 It is important to note that ethnicity is too highly correlated with district to include bothin the same model. That ethnicity and district are highly correlated is actually somewhatby design.Recall that district pairs were chosen such that they were similar in demographiccharacteristics, including ethnic population make-up, but one of the districts had an unusualvoting history. The Bosome Freho-Birim South pairing particularly matters for this casebecause this was the only district pair in which the dominant tribe was not the same (Asantesdominated in Bosome Freho while Akyems dominated in Birim South). It then makes sensethat Asantes should be more likely to be swing voters as compared to Akyems. However,outside of the Bosome Freho-Birim South pair, the same ethno-linguistic group (Ewes, Fantes)makes up the majority of the district populations, such that each district’s ethnic swing voterscancel out or do not make that ethnic or tribal group more likely to swing vote in general.
13 Though they may slightly favor the NDC, this reference category was chosen becauseGa-Dangbe’s voting patterns tend to be more middle-of-the-road as compared to other groups.
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members were significantly more likely to be swing voters.14 However, after adding regime
performance and clientelistic voting indicators in Model 3, the Guan ethno-linguistic variable
loses its significance. Also within Model 3, a one-unit increase in rating of the 2000-2008
NPP government’s success at developing the respondent’s area increased the odds that a
respondent is a swing voter by 1.43. Further, a one-unit increase in the rating of the 2008
NDC government’s handling of the economy also increased the odds that a respondent is
a swing voter by 1.416. Finally, also in Model 3 the variable measuring whether or not a
respondent identified the NDC as the political party with the biggest reputation for giving out
the most gifts as a significant predictor of a swing voter.
So far, the analysis provides little evidence of ethnicity (Hypothesis 1) having an impact
on swing voting. There is some evidence that swing voters do have more positive performance
ratings of the 2000-2008 NPP government’s development success and the 2008 NDC
government’s economic management success as compared to stable voters. Finally, identifying
the NDC as the political party with the biggest reputation for giving out gifts decreased the
odds that a respondent was a swing voter. This is probably because strong supporters of the
NPP were most likely to identify the NDC as having this gift-giving reputation and would
also be less likely to swing vote. That respondents identify parties which they do not vote
for, and that there was not significant difference in whether respondents felt gifts actually
impacted voters’ vote decisions (gifts voting) provides little overall evidence for Hypothesis 3:
Clientelistic-Induced Voting.
In Table 7-15, Models 4-6 each replicate Model 3 in Table 7-14 except the regime
performance indicators are substituted out for respondents’ reasons for their 2012 Presidential,
2012 Parliamentary and their community members’ votes. In Models 4 through 6, the
14 Though voting data is only available for 12 Guan respondents in the entire sample, 5 ofthem (41.7%) report swing voting. Also important, all 12 of these Guan respondents comefrom the Birim South District.
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demographic and ethnic variables’ significance is similar to that of Table 7-14, except now
Guan ethno-linguistic group members again are more likely to be swing voters as compared to
the Ga-Dangbe reference category.
In Model 4, when explaining their reasons for their vote for President in the 2012
election, respondents who cited the candidate’s Economic Policy, disapproval of the past
candidate/regime, and voting for voting’s sake each significantly increased the odds that
the respondent was a swing voter at some point in their voting history. In Model 5, where
respondents explain their reason for their vote for MP, no explanation significantly predicted
swing voters as compared to stable voters. Finally, in Model 6 respondents’ explanations for
presidential votes in general within the community were included in the model. Respondents
who explained community votes as impacted by the candidate’s economic policy and social
policy increased the odds that the respondent was a swing voter. Finally, also in Model 6, now
a one-unit increase towards the belief that when individuals take gifts from political parties
they still vote the way they want and not necessarily with the party that gave the gift, as
opposed to the belief that individuals vote the way they want regardless of gift inducements,
significantly decreased the odds that a respondent was a swing voter.
In Models 4-6 then, there is some evidence for ethnic impacts on voting (Hypothesis 1)
as Guan voters are more likely to be swing voters throughout. But there is stronger evidence
for Hypothesis 2, Policy or Economic-Based Voting, in that swing voters were more likely to
explain their 2012 Presidential vote with the candidate’s economic policy and disapproval of
the past candidate/regime. Similarly, swing voters were also more likely to explain community
members’ votes for president as the result of the candidate’s economic and social policy. It
appears swing voters are somewhat more critical of policies and past government performance
than stable voters. Finally, as pertains to Hypothesis 3, Clientelistic-Based Voting, swing voters
were more likely to say that voters vote for the party which gives them gifts in Model 6. This
might suggest that swing voters are critical of the voting process in Ghana, such that political
parties can simply pay for votes rather than earn votes, or that swing voters themselves might
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be more likely to have been induced by clientelistic gifts for their votes. Either way, this
variable provides some small support for Hypothesis 3.
7.3 Conclusion
Using respondents’ self-report data about their voting history to test for predictors of vote
decisions finds support for Hypothesis 1: Identity-Based Voting but more so for Hypothesis
2: Policy or Economic-Based Voting, with little evidence for Hypothesis 3: Clientelism-Based
Voting. Further, there is some evidence that economic or policy-based voting impacts swing
voters more than stable voters, with less evidence of identity or clientelistic-inducements of
swing voting.
Throughout the 2004-2012 Presidential and Parliamentary elections, ethnic identities were
consistently strong predictors of vote choice but not swing voters. Using a mix of tribal and
ethno-linguistic groups, the vote choice analysis shows that Ashantis, Akyems, and Other Akan
Tribes, as well as the Mole Dagbani ethno-linguistic group, consistently favored the NPP over
the NDC, while the Ewe ethno-linguistic group consistently favored the NDC over the NPP, in
comparison to the Ga-Dangbe reference category. Fante group membership also significantly
predicted NPP over NDC votes in the 2008 Presidential and Parliamentary elections. In the
swing voting analysis, only members of the Guan ethno-linguistic group were more likely to be
swing voters as compared to the Ga-Dangbe reference category.
However, it should be remembered that the survey sample is not a national representative
sample but is rather a random sample within the 6 purposely selected districts. While the
voting patterns of the Ashantis, Akyems and Ewes are generally in-line with the nation-wide
voting behavior of these groups, Fantes, Other Akan tribes, and Mole Dagbanis’ significance in
the model is not representative of these groups competitive nationwide voting traditions.
Similarly, I also tested for the relationship between respondents’ votes and their immediate
family members’ votes. Respondents who reported that their family votes the same way as
they do were significantly less likely to vote for the NDC over the NPP in the 2004 Presidential
election alone. Yet, respondents who reported that their family members are stable voters were
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significantly less likely to be swing voters. Perhaps swing voting is a trait passed down within
families or perhaps swing voters are more likely to think of their family as swing voters because
they themselves are one.
Second, to test for Hypothesis 2: Policy or Economic-Based Voting, I use respondents’
evaluations of regime’s handling of the economy and success at bringing development to
the respondents’ area in both the vote predictions and swing voter models. Economic
evaluations were a stronger predictor of votes than development evaluations in the 2004
and 2012 Presidential and Parliamentary elections. But, development evaluations were stronger
predictors of votes than economic evaluations in the 2008 Presidential and Parliamentary
elections. When comparing economic and developmental evaluations of regimes against ethnic
coefficients in the changes in predicted probabilities figures, economic and developmental
tended to have stronger effects on the probability of voting for the NPP versus the NDC than
did ethnicity.
In the swing voter analyses, swing voters were more likely to rate both the 2000-2008
NPP government’s development initiatives and the 2008-2012 NDC government’s handling
of the economy in a positive light as compared to stable voters. Further, in the swing
voting analysis, swing voters were also more likely to justify their 2012 presidential votes
with the candidate’s economic policy and as the result of their disapproval with the prior
candidate/regime. Finally, swing voters also believe that presidential votes within their
community are driven by candidates’ economic and social policies. It might be that swing
voters are naturally more critical of policies and performance but it may also be the case
that swing voting is encouraged by the increased policy differentiation between Presidential
candidates in Ghana.
Finally, responses asking about the political party with the biggest reputation for handing
out gifts found that respondents reported political parties which they did not vote for. The
vote choice models show that respondents who identified the NDC as having the biggest
reputation for handing out gifts were significantly less likely to vote for the NDC over the NPP
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in each of the elections. In the swing voter models, if respondents identified the NDC as giving
out the most gifts, they were less likely to be swing voters, again suggesting that partisan
NPP members pointing out the NDC led to this result. That respondents are reporting the
political parties which they do not vote for, suggests either that clientelistic-incentives do not
usually affect voting or that respondents are unwilling to report their or their political party’s
undemocratic behavior.
Overall this analysis within this chapter provides a great deal of support for Hypothesis
2 and some support for Hypothesis 1. However, some constraints exist when testing for
predictors of retrospective vote decisions. Respondents may not remember their votes
accurately or may not be willing to accurately report them to the survey enumerator.
Respondents opinions about past regimes certainly change over time and their current
evaluations about a past regime’s performance might not be the same mindset they had
when deciding which party to vote for in past elections. Finally, direct questions in surveys
may not be very accurate in obtaining sensitive information, such as clientelistic pay-for-votes
behavior.
For these reasons, we cannot solely rely on respondents’ self-report data to predict their
voting decisions. In the next chapter I analyze self-reported swing votes and three survey
experiments to further identify patterns in respondents’ votes.
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Table 7-1. Predicting 2004 presidential votes
Model 1 Model 2NDC Third party NDC Third party
age 0.004 -0.03 0.004 -0.04(0.01) (0.03) (0.01) (0.03)
female -0.04 -2.02∗ -0.04 -2.01∗
(0.15) (1.09) (0.15) (1.09)islam 1.13∗∗∗ 1.46 0.43 1.23
(0.29) (1.14) (0.37) (1.14)otherrelig -0.37 -13.80∗∗∗ -0.17 -13.34∗∗∗
(0.41) (0.0000) (0.38) (0.0000)cellown -0.28 0.21 -0.32∗ -0.02
(0.18) (1.12) (0.18) (1.14)water inside -0.63∗∗ 0.58 -0.26 0.46
(0.28) (0.99) (0.26) (0.96)farmer 0.40∗∗ 0.71 0.03 0.17
(0.18) (0.86) (0.16) (0.86)Bosome Freho -1.63∗∗∗ 12.09∗∗∗
(0.26) (1.03)Birim South -0.60∗∗∗ 12.14∗∗∗
(0.21) (1.01)Adaklu 3.21∗∗∗ 15.51∗∗∗
(0.31) (0.80)Ketu South 3.86∗∗∗ 14.88∗∗∗
(0.37) (1.11)Mfantsiman 0.73∗∗∗ 14.07∗∗∗
(0.22) (0.63)ashanti -2.83∗∗∗ -3.44∗∗∗
(0.53) (0.0000)fante -0.68 11.12∗∗∗
(0.48) (0.64)akyem -1.95∗∗∗ -2.58∗∗∗
(0.51) (0.0000)otherakan -1.80∗∗∗ 11.75∗∗∗
(0.52) (0.79)ewe 2.00∗∗∗ 12.92∗∗∗
(0.50) (0.75)guan -0.17 -8.61∗∗∗
(0.93) (0.00)moledagbani -1.12 -12.60∗∗∗
(0.85) (0.00)other ethnicity 0.11 -8.50∗∗∗
(0.65) (0.00)Constant -0.68∗ -16.04∗∗∗ 0.61 -13.26∗∗∗
(0.38) (1.58) (0.58) (1.39)
N 1279 1277AIC 1,290.20 1,320.76Pseudo R2 0.3292 0.3212Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 7-1. ContinuedModel 3 Model 4
NDC Third party NDC Third party
islam 0.58 1.37 0.51 1.22(0.38) (1.13) (0.45) (1.22)
otherrelig -0.13 -14.84∗∗∗ -0.94∗ -29.84∗∗∗
(0.38) (0.0000) (0.50) (0.00)cellown -0.45∗∗ -0.22 -0.35 -0.19
(0.18) (0.84) (0.23) (0.87)vote stays thesame
0.55∗∗∗ -0.83∗∗ 0.84∗∗∗ -0.87∗
(0.13) (0.38) (0.18) (0.51)diff.ideo 0.02 0.28 0.19 0.59
(0.16) (0.76) (0.20) (0.83)ashanti -3.25∗∗∗ -7.56∗∗∗ -1.98∗∗∗ -0.70
(0.54) (0.0000) (0.76) (135.32)fante -0.92∗ 9.51∗∗∗ -0.27 9.92
(0.48) (0.61) (0.70) (34.56)akyem -2.16∗∗∗ -9.54∗∗∗ -1.60∗∗ -1.73
(0.52) (0.00) (0.74) (145.96)otherakan -2.02∗∗∗ 10.61∗∗∗ -1.52∗∗ 11.11
(0.53) (0.64) (0.75) (34.56)ewe 1.69∗∗∗ 11.40∗∗∗ 1.38∗ 10.72
(0.50) (0.67) (0.72) (34.56)guan -0.33 11.22∗∗∗ 0.42 12.23
(0.93) (1.29) (1.29) (34.58)moledagbani -1.69∗ -11.19∗∗∗ -2.90∗∗ -14.14∗∗∗
(0.90) (0.00) (1.27) (0.0000)other ethnicity -0.01 -7.67∗∗∗ 0.51 -6.32∗∗∗
(0.69) (0.00) (0.96) (0.03)family votes thesame
-0.46∗ -0.94
(0.24) (0.85)2000 NPP Econ. -1.23∗∗∗ -1.18∗∗∗
(0.13) (0.38)2000 NPP Dev. -0.70∗∗∗ -1.10∗∗∗
(0.11) (0.39)NDCgifts -0.78∗∗∗ 0.41
(0.22) (0.79)Constant 0.64 -13.55∗∗∗ 4.38∗∗∗ -8.81
(0.52) (0.80) (0.78) (34.57)
N 1288 1129AIC 1,314.87 914.85Pseudo R 2 0.3331 0.4940Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 7-2. Predicting 2004 parliamentary votes
Model 1 Model 2NDC Third party NDC Third party
age 0.002 0.01 0.002 0.01(0.01) (0.03) (0.01) (0.03)
female -0.04 -0.49 -0.05 -0.67(0.15) (0.66) (0.15) (0.68)
islam 1.05∗∗∗ 0.92 0.23 0.04(0.29) (1.10) (0.37) (1.39)
otherrelig -0.30 -15.29∗∗∗ -0.12 -22.05∗∗∗
(0.40) (0.00) (0.38) (0.00)cellown -0.35∗ 0.03 -0.39∗∗ -0.06
(0.18) (0.84) (0.18) (0.84)water inside -0.39 0.08 -0.05 -0.11
(0.27) (1.11) (0.26) (1.12)farmer 0.51∗∗∗ 0.04 0.14 -0.45
(0.18) (0.77) (0.16) (0.74)Bosome Freho -1.70∗∗∗ 26.53∗∗∗
(0.27) (0.64)Birim South -0.60∗∗∗ 26.08∗∗∗
(0.21) (0.74)Adaklu 3.12∗∗∗ 28.48∗∗∗
(0.31) (0.75)Ketu South 3.72∗∗∗ 15.79∗∗∗
(0.35) (0.0000)Mfantsiman 0.69∗∗∗ 27.13∗∗∗
(0.22) (0.59)ashanti -2.86∗∗∗ 9.59∗∗∗
(0.54) (0.71)fante -0.64 9.60∗∗∗
(0.48) (0.62)akyem -1.94∗∗∗ 9.18∗∗∗
(0.51) (0.96)otherakan -1.63∗∗∗ 10.35∗∗∗
(0.52) (0.72)ewe 1.96∗∗∗ 10.18∗∗∗
(0.50) (0.99)guan 0.08 -10.69∗∗∗
(0.93) (0.00)moledagbani -0.87 -13.17∗∗∗
(0.85) (0.00)other ethnicity 0.39 11.85∗∗∗
(0.66) (1.23)Constant -0.56 -30.72∗∗∗ 0.65 -13.62∗∗∗
(0.38) (1.25) (0.58) (1.34)
N 1277 1176AIC 1,321.17 1,356.15Pseudo R2 0.3209 0.3229Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 7-2. ContinuedModel 3 Model 4
NDC Third party NDC Third party
islam 0.48 0.15 0.27 0.39(0.38) (1.34) (0.46) (1.32)
otherrelig -0.15 -35.45∗∗∗ -1.18∗∗ -9.58(0.38) (0.00) (0.48) (116.04)
cellown -0.51∗∗∗ -0.52 -0.47∗∗ -0.95(0.18) (0.72) (0.22) (0.75)
vote stays thesame
0.61∗∗∗ -0.70∗ 0.83∗∗∗ -0.72
(0.13) (0.37) (0.18) (0.50)diff.ideo 0.08 0.43 0.23 0.30
(0.16) (0.72) (0.20) (0.74)ashanti -3.25∗∗∗ 9.50∗∗∗ -2.01∗∗∗ 9.58∗∗∗
(0.54) (0.76) (0.76) (1.00)fante -0.97∗∗ 9.13∗∗∗ -0.33 9.73∗∗∗
(0.48) (0.75) (0.71) (0.80)akyem -2.22∗∗∗ 9.27∗∗∗ -1.67∗∗ 9.42∗∗∗
(0.52) (0.98) (0.74) (0.98)otherakan -1.92∗∗∗ 10.69∗∗∗ -1.38∗ 11.37∗∗∗
(0.52) (0.67) (0.75) (0.75)ewe 1.68∗∗∗ 10.31∗∗∗ 1.37∗ 10.17∗∗∗
(0.50) (0.99) (0.72) (1.00)guan -0.19 12.54∗∗∗ 0.67 13.09∗∗∗
(0.94) (1.49) (1.30) (1.58)moledagbani -1.56∗ -11.24∗∗∗ -2.67∗∗ -7.74∗∗∗
(0.90) (0.00) (1.27) (0.0000)other ethnicity -0.01 11.84∗∗∗ 0.49 11.64∗∗∗
(0.70) (1.13) (0.96) (1.19)family votes thesame
-0.34 0.06
(0.24) (0.85)2000 NPP Econ. -1.19∗∗∗ -0.90∗∗
(0.12) (0.38)2000 NPP Dev. -0.72∗∗∗ -0.79∗∗
(0.11) (0.39)NDCgifts -0.84∗∗∗ 0.87
(0.22) (0.72)Constant 0.60 -13.45∗∗∗ 4.38∗∗∗ -10.00∗∗∗
(0.52) (0.79) (0.78) (1.16)
N 1277 1127AIC 1,328.92 926.14Pseudo R2 0.3209 0.4863Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
286
Table 7-3. Predicting 2008 presidential votes
Model 1 Model 2NDC Third party NDC Third party
age 0.003 0.003 0.004 0.002(0.01) (0.03) (0.01) (0.03)
female -0.13 -0.16 -0.15 -0.18(0.14) (0.73) (0.14) (0.73)
islam 1.21∗∗∗ -17.91∗∗∗ 0.32 -21.54∗∗∗
(0.27) (0.00) (0.33) (0.00)otherrelig -0.35 0.40 -0.06 0.31
(0.39) (1.30) (0.35) (1.16)cellown -0.33∗ 0.23 -0.36∗∗ 0.13
(0.17) (1.12) (0.17) (1.12)water inside -0.36 -13.47∗∗∗ -0.02 -14.73∗∗∗
(0.25) (0.0000) (0.23) (0.0000)farmer 0.19 -1.26 -0.19 -1.36
(0.16) (1.17) (0.15) (1.13)Bosome Freho -1.36∗∗∗ 24.81∗∗∗
(0.22) (0.93)Birim South -0.81∗∗∗ 24.67∗∗∗
(0.19) (0.96)Adaklu 2.43∗∗∗ 27.56∗∗∗
(0.26) (0.67)Ketu South 3.70∗∗∗ 28.09∗∗∗
(0.38) (0.93)Mfantsiman 0.73∗∗∗ 24.96∗∗∗
(0.20) (0.92)ashanti -2.22∗∗∗ -1.27∗∗∗
(0.46) (0.0000)fante -0.47 10.77∗∗∗
(0.42) (0.71)akyem -1.89∗∗∗ -9.18∗∗∗
(0.46) (0.00)otherakan -1.39∗∗∗ 11.24∗∗∗
(0.46) (0.90)ewe 1.81∗∗∗ 13.26∗∗∗
(0.44) (0.69)guan 1.39 2.48∗∗∗
(1.18) (0.00)moledagbani -0.20 -3.39∗∗∗
(0.81) (0.00)other ethnicity -0.01 -10.84∗∗∗
(0.60) (0.00)Constant -0.14 -29.46∗∗∗ 0.86∗ -14.96∗∗∗
(0.33) (1.45) (0.51) (1.30)
N 1435 1431AIC 1,515.23 1,550.12Pseudo R2 0.2844 0.2714Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
287
Table 7-3. ContinuedModel 3 Model 4
NDC Third party NDC Third party
islam 0.44 -10.39∗∗∗ 0.53 -13.34∗∗∗
(0.34) (0.0000) (0.39) (0.0000)otherrelig -0.06 0.75 0.08 1.03
(0.36) (1.15) (0.47) (1.20)cellown -0.39∗∗ 0.44 -0.49∗∗ 0.35
(0.16) (1.09) (0.20) (1.10)vote stays thesame
-0.50∗∗∗ -1.18∗∗∗ -0.49∗∗∗ -0.89∗
(0.12) (0.44) (0.16) (0.53)diff.ideo 0.09 -0.10 0.30∗ 0.17
(0.14) (0.69) (0.17) (0.73)ashanti -2.75∗∗∗ -12.32∗∗∗ -3.06∗∗∗ -16.09∗∗∗
(0.47) (0.00) (0.61) (0.00)fante -0.68 11.73∗∗∗ -1.12∗∗ 10.09∗∗∗
(0.43) (0.64) (0.56) (0.70)akyem -2.07∗∗∗ -6.96∗∗∗ -2.27∗∗∗ -9.86∗∗∗
(0.46) (0.00) (0.59) (0.00)otherakan -1.66∗∗∗ 12.68∗∗∗ -2.19∗∗∗ 10.91∗∗∗
(0.47) (0.65) (0.60) (0.74)ewe 1.74∗∗∗ 14.11∗∗∗ 1.17∗∗ 12.25∗∗∗
(0.45) (0.57) (0.58) (0.68)guan 0.52 2.32∗∗∗ 0.91 4.66∗∗∗
(0.94) (0.00) (1.28) (0.00)moledagbani -0.77 -1.27∗∗∗ -1.73∗ -1.31∗∗∗
(0.85) (0.00) (0.97) (0.00)other ethnicity -0.19 -4.63∗∗∗ -0.61 -2.97∗∗∗
(0.63) (0.00) (0.79) (0.0000)family votes thesame
0.18 -1.03
(0.20) (0.87)2008 NDC Econ. 0.70∗∗∗ 0.45
(0.10) (0.47)2008 NDC Dev. 0.87∗∗∗ 0.41
(0.11) (0.47)NDCgifts -0.78∗∗∗ -0.27
(0.18) (0.88)Constant 1.38∗∗∗ -15.91∗∗∗ -0.96 -15.11∗∗∗
(0.47) (0.86) (0.64) (1.28)
N 1444 1263AIC 1,512.18 1,149.49Pseudo R2 0.2969 0.4107Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
288
Table 7-4. Predicting 2008 parliamentary votes
Model 1 Model 2NDC Third party NDC Third party
age 0.01 0.05∗∗ 0.01 0.05∗
(0.01) (0.03) (0.01) (0.02)female -0.13 -0.64 -0.16 -0.60
(0.14) (0.71) (0.14) (0.70)islam 1.38∗∗∗ -20.64∗∗∗ 0.41 -14.83∗∗∗
(0.28) (0.00) (0.34) (0.0000)otherrelig -0.12 -20.22∗∗∗ 0.06 -37.77
(0.39) (0.00) (0.36)cellown -0.28∗ -1.24 -0.32∗ -1.15
(0.17) (0.76) (0.17) (0.74)water inside -0.39 -13.90∗∗∗ -0.08 -19.02∗∗∗
(0.25) (0.0000) (0.23) (0.00)farmer 0.25 -1.63∗ -0.12 -1.39∗
(0.16) (0.87) (0.15) (0.82)Bosome Freho -1.41∗∗∗ 26.56∗∗∗
(0.23) (0.55)Birim South -0.80∗∗∗ 24.91∗∗∗
(0.19) (0.91)Adaklu 2.72∗∗∗ 27.35∗∗∗
(0.28) (0.74)Ketu South 3.52∗∗∗ 27.59∗∗∗
(0.36) (1.02)Mfantsiman 0.71∗∗∗ 12.14∗∗∗
(0.20) (0.0000)ashanti -2.35∗∗∗ 10.16∗∗∗
(0.46) (0.56)fante -0.50 8.14∗∗∗
(0.42) (0.90)akyem -1.88∗∗∗ -9.35∗∗∗
(0.46) (0.00)otherakan -1.48∗∗∗ 9.73∗∗∗
(0.46) (0.90)ewe 1.87∗∗∗ 11.12∗∗∗
(0.45) (0.71)guan 1.32 1.95∗∗∗
(1.18) (0.00)moledagbani -0.31 -3.93∗∗∗
(0.81) (0.00)other ethnicity 0.25 -9.83∗∗∗
(0.61) (0.00)Constant -0.36 -30.23∗∗∗ 0.67 -14.03∗∗∗
(0.34) (1.20) (0.51) (1.16)
N 1432 1318Akaike Inf. Crit. 1,489.75 1,524.96Pseudo R2 0.2984 0.2994Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
289
Table 7-4. ContinuedModel 3 Model 4
NDC Third party NDC Third party
age 0.01 0.03 0.01∗∗ 0.03(0.01) (0.02) (0.01) (0.02)
islam 0.63∗ -23.07∗∗∗ 0.73∗ -14.58∗∗∗
(0.35) (0.69) (0.40) (0.0000)otherrelig -0.04 -18.50∗∗∗ 0.18 -19.10∗∗∗
(0.37) (0.00) (0.48) (0.00)cellown -0.41∗∗ -0.97 -0.45∗∗ -1.15
(0.17) (0.71) (0.21) (0.83)vote stays thesame
-0.48∗∗∗ -1.14∗∗∗ -0.55∗∗∗ -1.39∗∗
(0.12) (0.41) (0.16) (0.54)diff.ideo 0.21 0.46 0.33∗ -0.004
(0.15) (0.77) (0.18) (0.82)ashanti -2.82∗∗∗ 9.28∗∗∗ -3.10∗∗∗ 9.45∗∗∗
(0.47) (0.62) (0.61) (0.75)fante -0.74∗ 7.95∗∗∗ -1.22∗∗ 8.45∗∗∗
(0.43) (0.89) (0.56) (0.92)akyem -2.06∗∗∗ -10.77∗∗∗ -2.30∗∗∗ -19.85∗∗∗
(0.46) (0.00) (0.60) (0.00)otherakan -1.82∗∗∗ 9.69∗∗∗ -2.35∗∗∗ 10.36∗∗∗
(0.47) (0.70) (0.61) (0.75)ewe 1.73∗∗∗ 11.13∗∗∗ 1.18∗∗ 11.63∗∗∗
(0.45) (0.67) (0.58) (0.84)guan 1.05 36.59∗∗∗ 0.77 1.91∗∗∗
(1.18) (0.69) (1.30) (0.00)moledagbani -0.93 -8.62∗∗∗ -1.94∗∗ -4.12∗∗∗
(0.86) (0.00) (0.99) (0.00)other ethnicity -0.09 -11.66∗∗∗ -0.48 -9.04∗∗∗
(0.64) (0.00) (0.82) (0.00)family votes thesame
0.23 0.39
(0.21) (0.93)2008 NDC Econ. 0.80∗∗∗ 0.52
(0.11) (0.48)2008 NDC Dev. 0.82∗∗∗ -0.17
(0.11) (0.45)NDCgifts -0.74∗∗∗ 0.88
(0.19) (0.78)Constant 1.07∗∗ -13.81∗∗∗ -1.59∗∗ -14.53∗∗∗
(0.52) (1.17) (0.72) (1.60)
N 1435 1258AIC 1,502.91 1,124.53Pseudo R2 0.3050 0.4240Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
290
Table 7-5. Predicting 2012 presidential votes
Model 1 Model 2NDC Third party NDC Third party
age 0.002 -0.02 0.003 -0.02(0.005) (0.02) (0.005) (0.02)
female -0.12 -0.22 -0.14 -0.32(0.13) (0.56) (0.13) (0.57)
islam 1.12∗∗∗ -14.22∗∗∗ 0.11 -18.14∗∗∗
(0.26) (0.0000) (0.33) (0.00)otherrelig -0.46 1.73∗ -0.28 1.27
(0.37) (0.93) (0.34) (0.90)cellown -0.34∗∗ -0.18 -0.34∗∗ -0.11
(0.16) (0.81) (0.16) (0.82)water inside -0.26 -0.53 0.03 -0.64
(0.22) (1.08) (0.22) (1.08)farmer 0.37∗∗ -1.80∗ 0.03 -1.99∗
(0.16) (1.09) (0.15) (1.08)Bosome Freho -1.58∗∗∗ -13.37∗∗∗
(0.22) (0.0000)Birim South -0.91∗∗∗ 0.38
(0.19) (0.89)Adaklu 2.60∗∗∗ 1.39
(0.24) (1.04)Ketu South 3.13∗∗∗ 0.32
(0.30) (1.38)Mfantsiman 0.72∗∗∗ 0.83
(0.19) (0.87)ashanti -2.08∗∗∗ -4.52∗∗∗
(0.45) (0.0000)fante 0.09 10.50∗∗∗
(0.40) (0.48)akyem -1.37∗∗∗ 10.21∗∗∗
(0.44) (0.65)otherakan -1.08∗∗ 11.20∗∗∗
(0.44) (0.51)ewe 2.30∗∗∗ 11.08∗∗∗
(0.42) (0.62)guan 0.77 -0.77∗∗∗
(0.79) (0.00)moledagbani 0.39 -1.49∗∗∗
(0.75) (0.0000)other ethnicity 0.89 -8.62∗∗∗
(0.57) (0.00)Constant -0.19 -2.72∗∗ 0.20 -13.04∗∗∗
(0.29) (1.31) (0.48) (0.96)
N 1612 1606Akaike Inf. Crit. 1,728.85 1,751.93Pseudo R2 0.2886 0.2816Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
291
Table 7-5. ContinuedModel 3 Model 4
NDC Third party NDC Third party
islam 0.23 -15.48∗∗∗ 0.23 -15.99∗∗∗
(0.33) (0.55) (0.39) (0.65)otherrelig -0.005 0.64 -0.13 0.92
(0.34) (1.11) (0.46) (1.20)internetuse -0.82∗∗∗ 0.05 -0.90∗∗∗ 0.14
(0.20) (0.69) (0.26) (0.81)vote stays thesame
-0.15 -1.56∗∗∗ -0.16 -1.81∗∗∗
(0.12) (0.31) (0.17) (0.41)diff.ideo 0.03 0.26 0.50∗∗∗ 0.41
(0.14) (0.58) (0.18) (0.64)ashanti -2.26∗∗∗ -14.69∗∗∗ -2.09∗∗∗ -16.16∗∗∗
(0.45) (0.00) (0.64) (0.00)fante -0.09 10.42∗∗∗ 0.09 10.98∗∗∗
(0.40) (0.47) (0.58) (0.52)akyem -1.53∗∗∗ 10.17∗∗∗ -1.54∗∗ 10.20∗∗∗
(0.44) (0.64) (0.62) (0.68)otherakan -1.22∗∗∗ 11.37∗∗∗ -1.09∗ 11.56∗∗∗
(0.44) (0.51) (0.63) (0.63)ewe 2.22∗∗∗ 11.48∗∗∗ 1.51∗∗ 10.72∗∗∗
(0.42) (0.56) (0.60) (0.73)guan 0.73 28.40∗∗∗ 0.03 28.09∗∗∗
(0.79) (0.55) (1.00) (0.65)moledagbani -0.01 -2.90∗∗∗ -1.12 -2.63∗∗∗
(0.77) (0.00) (1.00) (0.00)other ethnicity 0.82 -7.05∗∗∗ 0.36 -13.42∗∗∗
(0.60) (0.00) (0.84) (0.00)family votes thesame
0.21 0.15
(0.21) (0.70)2012 NDC Econ. 0.98∗∗∗ 0.76∗∗
(0.11) (0.38)2012 NDC Dev. 0.74∗∗∗ 0.71∗∗
(0.08) (0.33)NDCgifts -0.81∗∗∗ 0.35
(0.19) (0.69)debate -0.10 0.09
(0.17) (0.67)Constant 0.30 -13.84∗∗∗ -1.93∗∗∗ -15.95∗∗∗
(0.42) (0.46) (0.62) (0.88)
N 1433 1329AIC 1,686.20 1,147.39Pseudo R2 0.2962 0.4547Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
292
Table 7-6. Predicting 2012 parliamentary votes
Model 1 Model 2NDC Third party NDC Third party
age 0.001 0.02 0.001 0.03(0.005) (0.02) (0.005) (0.02)
female -0.07 0.98∗ -0.09 0.94∗
(0.13) (0.56) (0.13) (0.56)islam 1.22∗∗∗ 1.04 0.22 0.19
(0.26) (0.83) (0.33) (1.15)otherrelig -0.23 1.08 -0.05 0.46
(0.37) (1.09) (0.35) (1.11)internetuse -0.61∗∗∗ 0.66 -0.64∗∗∗ 0.71
(0.22) (0.73) (0.21) (0.73)water inside -0.11 0.11 0.18 0.06
(0.23) (0.83) (0.22) (0.83)farmer 0.39∗∗ 0.13 0.06 0.03
(0.16) (0.57) (0.15) (0.56)Bosome Freho -1.59∗∗∗ 0.39
(0.22) (0.88)Birim South -1.07∗∗∗ 0.55
(0.19) (0.83)Adaklu 2.65∗∗∗ 2.06∗∗
(0.25) (0.96)Ketu South 3.22∗∗∗ -10.74∗∗∗
(0.31) (0.0000)Mfantsiman 0.61∗∗∗ 0.29
(0.19) (1.04)ashanti -1.93∗∗∗ 10.79∗∗∗
(0.45) (0.62)fante 0.16 10.43∗∗∗
(0.40) (0.61)akyem -1.46∗∗∗ 10.45∗∗∗
(0.44) (0.72)otherakan -0.98∗∗ 11.78∗∗∗
(0.44) (0.52)ewe 2.46∗∗∗ 11.31∗∗∗
(0.42) (0.77)guan 0.77 -12.01∗∗∗
(0.80) (0.00)moledagbani 0.31 13.16∗∗∗
(0.76) (1.30)other ethnicity 1.05∗ 12.24∗∗∗
(0.59) (1.06)Constant -0.34 -6.05∗∗∗ -0.04 -16.49∗∗∗
(0.25) (1.14) (0.44) (0.87)
N 1597 1590AIC 1,713.03 1,736.63Pseudo R2 0.2944 0.2869Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
293
Table 7-6. ContinuedModel 3 Model 4
NDC Third party NDC Third party
islam 0.38 -0.01 0.44 -0.17(0.33) (1.08) (0.40) (1.08)
otherrelig 0.004 -20.94∗∗∗ -0.11 -31.61∗∗∗
(0.35) (0.00) (0.47) (0.00)internetuse -0.74∗∗∗ -0.12 -0.77∗∗∗ 0.23
(0.20) (0.69) (0.26) (0.74)vote stays thesame
-0.22∗ -0.95∗∗∗ -0.16 -0.91∗∗
(0.12) (0.30) (0.17) (0.39)diff.ideo 0.16 0.86 0.69∗∗∗ 1.28∗
(0.14) (0.69) (0.18) (0.74)ashanti -2.17∗∗∗ 10.78∗∗∗ -1.93∗∗∗ 11.40∗∗∗
(0.45) (0.60) (0.64) (0.62)fante -0.11 10.12∗∗∗ 0.05 10.76∗∗∗
(0.40) (0.65) (0.59) (0.68)akyem -1.65∗∗∗ 10.28∗∗∗ -1.70∗∗∗ 10.47∗∗∗
(0.44) (0.75) (0.63) (0.77)otherakan -1.22∗∗∗ 11.63∗∗∗ -1.12∗ 11.58∗∗∗
(0.44) (0.57) (0.64) (0.70)ewe 2.30∗∗∗ 11.54∗∗∗ 1.57∗∗∗ 11.35∗∗∗
(0.42) (0.76) (0.60) (0.78)guan 0.60 13.32∗∗∗ -0.17 12.95∗∗∗
(0.79) (1.29) (1.01) (1.37)moledagbani -0.25 13.00∗∗∗ -1.49 12.19∗∗∗
(0.79) (1.24) (1.02) (1.29)other ethnicity 0.72 12.41∗∗∗ 0.27 12.19∗∗∗
(0.60) (1.02) (0.84) (1.11)family votes thesame
0.25 -0.06
(0.21) (0.63)2012 NDC Econ. 1.02∗∗∗ 0.92∗∗∗
(0.11) (0.32)2012 NDC Dev. 0.76∗∗∗ 0.62∗∗
(0.08) (0.29)NDCgifts -0.83∗∗∗ -0.07
(0.19) (0.55)debate -0.16 -0.71
(0.17) (0.59)Constant 0.23 -14.59∗∗∗ -2.16∗∗∗ -16.53∗∗∗
(0.42) (0.68) (0.63) (0.95)
N 1445 1326AIC 1,713.46 1,174.17Pseudo R2 0.2919 0.4484Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
294
Table 7-7. Swing Voters
District1 Party member2 Female3
Swingvoter
BosomeFreho
BirimSouth
AdakuAnyigbe
KetuSouth
Mfant. AOB Partymember
Non-partymember
Women Men
1 52, 53, 32, 28, 60, 48, 135, 113, 126, 145,17.99% 17.79% 11.47% 9.89% 21.58% 16.84% 10.41% 38.57% 14.77% 17.01%
0 237, 245, 247, 255, 218, 237, 1,162, 180, 727, 703,82.01% 82.21% 88.53% 90.11% 78.42% 83.16% 89.59% 61.43% 85.23% 82.90%
Total 289 298 279 283 278 285 1,297 293 853 8481Pearson chi2 (5): = 20.3209; Pr = 0.0012Pearson chi2 (1): = 143.957; Pr = 0.0003Pearson chi2 (1): = 1.7202; Pr = 0.190
295
Table 7-8. Swing Voters2
Education1 Democracy rating2
Swingvoter
Low edu. Med. edu. High edu. Total Fulldemocracy
Dem.w/minorproblems
Dem.w/majorproblems
Not ademocracy
Total
1 99, 147, 27, 273, 83, 118, 66, 3, 270,36.3% 53.8% 9.9% 100% 30.74% 43.7% 24.4% 1.1% 100%
0 553, 780, 98, 1,431, 498, 638, 253, 26, 1,415,38.6% 54.5% 6.8% 100% 35.2% 45.1% 17.9% 1.8% 100%
1Pearson chi2 (2): = 3.2496; Pr = 0.1972Pearson chi2 (3): = 7.2573; Pr = 0.064
296
Table 7-9. Swing Voters3
Vote stays the same1 Trust relatives2
Swingvoter
Vote staysthe same
Sometimeschanges
Differseveryelection
Total Not at all Just alittle
Somewhat A lot Total
1 85, 101, 84, 270, 48, 51, 48, 118, 265,31.5% 37.4% 31.1% 100% 18.1% 19.2% 18.1% 44.5% 100%
0 1,314, 47, 38, 1,399, 200, 163, 237, 811, 1,411,93.9% 3.4% 2.7% 100% 14.2% 11.6% 16.8% 57.5% 100%
1Pearson chi2 (2): = 650.7776; Pr = 0.0002Pearson chi2 (3): = 19.6563; Pr = 0.000
297
Table 7-10. Swing Voters4
Trust neighbors1 Trust other dialects2
Swingvoter
Not atall
Just alittle
Somewhat A lot Total Not atall
Just alittle
Somewhat A lot Total
1 86, 51, 93, 31, 261 127, 48, 61, 25, 261,33.0% 19.5% 35.6% 11.9% 100% 48.7% 18.4% 23.4% 9.6% 100%
0 372, 312, 475, 234, 1,393, 623, 319, 360, 79, 1,381,26.7% 22.4% 34.1% 16.8% 100% 45.1% 23.1% 26.1% 5.7% 100%
1Pearson chi2 (3): = 7.3867; Pr = 0.0612Pearson chi2 (3): = 8.5630; Pr = 0.036
298
Table 7-11. Skirt-and-blouse swing voters
District 2012 2008 2004 2000 1996 District Avg.
Bosome Freho 13, 9, 5, 7, 6,4.68%* 3.32% 1.99% 3.17% 3.37% 3.31%
Birim South 12, 5, 9, 7, 9,4.78% 2.05% 4.17% 3.83% 5.59% 4.08%
Adaklu Anyigbe 11, 11, 12, 9, 8,4.09% 4.21% 5.45% 4.76% 4.88% 4.68%
Ketu South 6, 3, 6, 2, 2,2.24% 1.13% 2.63% 1.04% 1.20% 1.65%
Mfantsiman 13, 8, 6, 2, 3,4.76% 2.97% 2.45% 0.93% 1.48% 2.52%
AOB 4, 2, 1, 2, 2,1.49% 0.77% 0.42% 0.96% 1.01% 4.65%
Yearly avg. 3.67% 2.41% 2.85% 2.45% 2.92*Total number of swing votes are divided by the total number of eligible swing voters per district per year.
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Table 7-12. Presidential election-to-election swing voters*
District 2012** 2008 2004 2000 District Avg.
Bosome Freho 15, 15, 9, 17,5.40%*** 5.54% 3.59% 7.69% 5.56%
Birim South 19, 22, 15, 16,7.57% 9.02% 6.94% 8.74% 8.07%
Adaklu Anyigbe 12, 13, 13, 10,4.46% 4.98% 5.91% 5.29% 5.16%
Ketu South 12, 10, 10, 5,4.48% 3.77% 4.39% 2.60% 3.81%
Mfantsiman 25, 36, 13, 16,9.16% 13.38% 5.31% 7.48% 8.83%
AOB 18, 18, 16, 18,6.72% 6.90% 6.69% 8.65% 7.24%
Yearly average 6.30% 7.27% 5.47% 6.74%*Respondents’ votes were collected from 2012 through 1996**Data in table reflects the year the vote change was made***Total number of swing votes are divided by the total number of eligible swing voters per district per year.
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Table 7-13. Parliamentary election-to-election swing voters*
District 2012** 2008 2004 2000 District Avg.
Bosome Freho 25, 17, 12, 18,8.99%*** 6.27% 4.78% 8.14% 7.05%
Birim South 20, 23, 15, 16,7.97% 9.43% 6.94% 8.74% 8.27%
Adaklu Anyigbe 8, 11, 14, 8,2.97% 4.21% 6.36% 4.23% 4.44%
Ketu South 10, 11, 10, 3,3.73% 4.15% 4.39% 1.56% 3.46%
Mfantsiman 25, 33, 11, 18,9.16% 12.27% 4.49% 8.41% 8.58%
AOB 18, 17, 16, 17,6.72% 6.51% 6.69% 8.17% 7.02%
Yearly average 6.59% 7.14% 5.61% 6.54%*Respondents’ votes were collected from 2012 through 1996**Data in table reflects the year the vote change was made***Total number of swing votes are divided by the total number of eligible swing voters per district per year.
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Table 7-14. Logit model odds ratios- predicting swing voters across electionsDependent variable: swing voter (0 or 1)
Model 1 Model 2 Model 3age 1.008(0.994,1.022) 1.009(0.995,1.023) 1.006(0.990,1.022)vote stays the same 0.154∗∗∗ (0.110, 0.213) 0.163∗∗∗ (0.117, 0.223) 0.167∗∗∗ (0.114, 0.238)partymember 0.271∗∗∗ (0.171, 0.427) 0.291∗∗∗ (0.185, 0.458) 0.260∗∗∗ (0.152, 0.444)family votes the same 0.555∗∗∗ (0.411, 0.756) 0.569∗∗∗ (0.426, 0.769) 0.596∗∗∗ (0.431, 0.835)trust neighbors 0.728∗∗∗ (0.593, 0.890) 0.742∗∗∗ (0.604, 0.907) 0.826(0.656,1.037)vote isn’t secret 0.823∗∗ (0.694, 0.970) 0.838∗∗ (0.707, 0.989) 0.789∗∗ (0.650, 0.950)Bosome Freho 2.182∗ (1.014, 4.887)Birim South 2.290∗∗ (1.061, 5.155)Adaklu 0.521(0.217,1.258)Mfantsiman 1.440(0.663,3.226)AOB 1.703(0.779,3.856)ashanti 4.609(0.655,101.643) 3.300(0.420,76.868)fante 4.415(0.655,95.723) 2.837(0.386,64.676)akyem 3.810(0.516,85.780) 2.540(0.316,60.310)otherakan 5.340(0.733,119.536) 3.148(0.378,75.419)ewe 1.819(0.263,39.759) 1.290(0.172,30.040)guan 17.902∗∗ (1.313, 510.189) 6.319(0.258,230.695)moledagbani 5.362(0.209,178.233) 2.857(0.084,103.763)other ethnicity 2.754(0.229,75.240) 1.900(0.143,56.016)2012 NDC Dev. 1.192(0.910,1.567)2008 NDC Dev. 0.774(0.558,1.074)2000 NPP Dev. 1.430∗∗ (1.061, 1.952)2012 NDC Econ. 1.174(0.843,1.629)2008 NDC Econ. 1.416∗∗ (1.036, 1.954)2000 NPP Econ. 1.117(0.823,1.531)MP Election change 1.349(0.815,2.225)NDCgifts 0.606∗ (0.349, 1.026)gifts voting 0.941(0.738,1.209)Constant 1.790(0.643,4.952) 0.624(0.028,4.689) 0.289(0.009,3.799)
Obs. 1,358 1,354 1,122Log Likelihood -360.021 -359.785 -284.200AIC 744.042 749.569 616.400Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 7-15. Logit model odds ratios- predicting swing voters across electionsDependent variable: swing voter (0 or 1)
Model 4 Model 5 Model 62012 Pres. 2012 Parl. Pres. votes by community
age 1.012(0.996,1.027) 1.011(0.996,1.027) 1.009(0.993,1.024)vote stays the same 0.138∗∗∗ (0.093, 0.200) 0.181∗∗∗ (0.125, 0.256) 0.148∗∗∗ (0.100, 0.214)partymember 0.222∗∗∗ (0.129, 0.380) 0.231∗∗∗ (0.137, 0.387) 0.211∗∗∗ (0.122, 0.362)family votes the same 0.631∗∗∗ (0.452, 0.896) 0.573∗∗∗ (0.415, 0.802) 0.662∗∗ (0.472, 0.945)trust neighbor 0.790∗∗ (0.628, 0.989) 0.793∗∗ (0.636, 0.985) 0.787∗∗ (0.629, 0.980)vote isn’t secret 0.784∗∗ (0.646, 0.945) 0.823∗∗ (0.682, 0.987) 0.789∗∗ (0.649, 0.952)ashanti 5.502(0.616,147.404) 4.740(0.614,111.221) 6.138(0.667,168.023)fante 5.415(0.631,143.234) 4.083(0.552,94.496) 5.779(0.658,155.789)akyem 3.615(0.383,99.029) 3.465(0.431,82.873) 3.575(0.372,99.552)otherakan 5.587(0.593,153.100) 5.179(0.643,124.022) 5.547(0.576,154.809)ewe 1.734(0.194,46.376) 1.802(0.237,41.960) 2.131(0.236,57.865)guan 14.947∗ (0.814, 551.638) 14.865∗ (0.957, 468.313) 26.285∗∗ (1.302, 1, 054.050)moledagbani 2.930(0.070,131.630) 3.946(0.116,142.015) 4.179(0.107,178.182)other ethnicity 3.506(0.217,121.375) 2.521(0.165,77.783) 4.280(0.264,149.648)Econ Policy 3.827∗∗∗ (2.014, 7.647) 1.617(0.870,3.025) 2.417∗∗∗ (1.410, 4.260)Social Policy 1.725(0.893,3.454) 1.100(0.587,2.068) 1.711∗ (0.982, 3.073)Party Legacy 1.364(0.822,2.251) 0.928(0.394,2.101) 0.980(0.587,1.622)Gov Disapproval 596.646∗∗∗ (19.928, 18, 024.530)Partic Ethnic 1.465(0.498,3.973) 0.613(0.024,5.534) 0.737(0.274,1.830)Clientelistic 1.436(0.048,17.036)Votings Sake 5.128∗∗ (1.016, 19.870) 3.973(0.525,22.083) 1.149(0.123,6.194)NDCgifts 0.607∗ (0.356, 1.011) 0.636∗ (0.380, 1.042) 0.697(0.411,1.155)gifts voting 0.826(0.651,1.053) 0.904(0.720,1.142) 0.814∗ (0.642, 1.039)Constant 0.263(0.008,3.403) 0.839(0.032,8.766) 0.536(0.017,6.550)
Obs. 1,197 1,184 1,183Log Likelihood -293.840 -309.493 -294.118AIC 635.681 662.985 634.237Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01In Table 7-15, Models 4-6 test for reasons for a respondent’s vote for President (Model 4), for MP (Model 5), and for the community’s votefor President (Model 6).
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Figure 7-1. Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2004 Pres. race
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Figure 7-2. Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2004 Parl. races
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Figure 7-3. Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2008 Pres. race
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Figure 7-4. Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2008 Parl. races
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Figure 7-5. Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2012 Pres. race
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Figure 7-6. Change in probabilities for voting for NPP(0), NDC(1), or a third party (3) in the2012 Parl. races
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CHAPTER 8SURVEY EXPERIMENTS
If the development of a competitive political environment at the local level actually has
had an impact on citizens’ vote decisions, which I argue is the reason behind the break down
of national-level ethnic voting since the 2000 elections, then we should see more evidence of
voting based on performance or economic evaluations rather than identity or clientelistic-based
voting in the survey sample. Further, given the differences in voting records within the 3
district pairs (NPP strongholds, NDC strongholds, and competitive districts), we should also
see differences in support for Hypothesis 2: Policy or Economic-Based Voting as compared to
Identity-Based Voting (Hypothesis 1) or Clientelistic-Based Voting (Hypothesis 3) between
district pairs.
Thus far in the survey analysis there has been strong support for Hypothesis 2: Policy or
Economic-Based Voting when respondents explain their reasons for their votes. There is also
some evidence for Hypothesis 2 in respondents’ rating of past regimes success at development
or handling the economy, though opinions about past regimes have no doubt been altered by
time. Aside from Hypothesis 2, there is also some support for Hypothesis 1: Identity-Based
Voting, and less support for Hypothesis 3: Clientelistic-Based Voting. Correlations between
ethnicity and vote choice are somewhat high, but few explain community votes for President
with ethnic/particularistic reasons and even fewer explain their own vote with these rationales.
Further, almost no respondent explained either their or their community members votes as
clientelistic-induced, except perhaps for one respondent who said she voted for the candidate
because her landlord asked her to.
Within district pairs, differences separating Bosome Freho from Birim South and Ketu
South from Adaklu Anyigbe appear to revolve around the former districts’ respondents focusing
on party legacy and candidate approval while the latter districts’ respondents focused on
ethnicity and policies in their vote decisions. The more homogeneous ethnic populations in
both Bosome Freho and Ketu South likely have something to do with the strong respective
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attachment to the NPP and NDC. However, it is also the case that political competition in
terms of MP races is heightened in Birim South and Adaklu Anyigbe, as compared to their
counterparts (and despite Bosome Freho having elected an NPP-turned-Independent candidate
in 2008), which likely is related to the focus on policies in these districts.
In this chapter, I turn to survey experiments to test for the isolated effects of identity
and clientelism on political behavior. In all, a total of three survey experiments were run. The
first experiment presents each of the respondents with an identical description of a political
candidate for Member of Parliament, while altering the candidate’s and the candidate’s
parent’s names to reflect differing tribal backgrounds. Respondents were then asked to rate the
candidate, whether or not they would vote for the candidate, and an open-ended response to
explain their reason to vote/not vote for the candidate.
The second experiment is a list experiment testing for religious biases on the part of
respondents. Respondents were asked how many of the following items upset them and
then half were given a list of four items and half were given a list of five items. The fifth
experimental item said ‘Having a Muslim as President of Ghana’. If the average number of
items selected for the five item respondents was significantly higher than the average number
of items selected for the four item respondent, we would know that experimental item had an
impact on the number of items selected.
Finally, the third experiment was also a 2 question list experiment asking about
Presidential and Parliamentary votes. Respondents were asked to select the number of
items from the list which affected their Presidential (Question 31) and Parliamentary (Question
32) votes in 2012. The fifth experimental item was ‘Payouts, in the form of money or other
gifts, provided by the candidate or his party boys’. Again, if the average number of items
selected was higher to a statistically significant degree in the 5-item version of the question
as compared to the 4-item version of the question, we would know that payouts affected
respondents votes.
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As presented in greater detail below, evidence of a tribal bias was mixed, evidence
of religious bias against Muslims was mixed, while evidence of clientelistic-based voting
was supported in the competitive districts. Within the district pairs, none of the district
respondents favored the insider candidate over the outsider candidate in terms of candidate
ratings. Further, in one district, Bosome Freho, the outsider candidate was given higher ratings
than the insider candidate. But when asked if they would vote for the candidate, respondents
from both of the NDC strongholds’ respondents reported that they were more likely to vote for
the insider candidate than the outsider candidate. As far as the list experiments, three districts
(one from each pair) did show statistically significant results suggesting that their respondents
were upset at the thought of a Muslim President of Ghana. Finally, in the clientelism list
experiments, it was only respondents from the competitive districts, Mfantsiman and AOB,
which significantly selected more items on the 5-item version of the question, suggesting
clientelistic-inducements did have an impact on their votes in both the 2012 Presidential and
Parliamentary races.
8.1 Identity Bias Voting Experiment
Since respondents may be either unwilling to admit or are unaware of ethnic or tribal
biases in their voting habits, I employ an experimental survey question to test for these biases
in perceptions of a hypothetical candidate for MP. Every respondent was read the same
fictional description of a parliamentary candidate for their constituency1 , and then were asked
1 The description of the candidate reads as follows: “ is a school teacherand district assembly member who is interested in running for Parliamentary Office in yourconstituency. He was born on September 15, 1968 to , a farmer andcarpenter, and , a seamstress. He is the third of his parent’s five children.Mr. was an excellent student in school and dazzled his audiences withhis superb debating skills as a member of his secondary school’s debating team. He wasawarded the prize of Best Overall Student in Form 3. Mr. also had a keeninterest in sport ans was team captain of his Football team in SS. After Secondary School,Mr. attended university at the University of Ghana- Legon. He undertookpolitical and economic studies, and completed his degree in 1993. Having been inspired byhis teachers growing up, Mr. has always wanted to be a teacher. When his
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in Questions 2-4 to rate the candidate, whether they would vote for the candidate, and an
open-ended question asking why they would or would not vote for the candidate. Though
each respondent was read the same description of the candidate, the candidate’s name was
changed to reflect different tribal backgrounds. Half of the respondents in each district were
read the candidate description with a name indigenous to the dominant tribal group in the
area, while the other half were read the same description but for a candidate whose name
referenced a tribe which is not indigenous to the area. One shortcoming is that respondents
were not tested to see if they were aware of the candidate’s ethnic background. However,
to ensure that respondent’s understood the candidate’s ethnic background, the candidate’s
mother’s and father’s names were also given and also reflected the same tribal background as
the candidate.2
mother fell sick, he returned to his mother’s house to care for her, and began working as ateacher. taught senior secondary school in this constituency for fifteen years.During that time Mr. ’s interest in politics led him to run for the position ofDistrict Assemblyman. He has served in that position for five years, and now believes he isqualified to run for the position of Member of Parliament in 2016.”
2 Names used for each district are as follows:(1) Bosome Freho - Insider (Asante): Joseph Kwabena Opokuware, Mother: Sarah Akua
Prempeh, Father: John Kweku Opokuware;- Outsider (Akyem): Joseph Kwabena Attafuah, Mother: Sarah Akua Akyea, Father: John
Kweku Attafuah;(2) Birim South - Insider (Akyem) : Joseph Kwabena Kwakye, Mother: Sarah Akua Akyea,
Father: John Kweku Kwakye;- Outsider (Asante): Joseph Kwabena Opokuware, Mother: Sarah Akua Prempeh, Father:
John Kweku Opokuware;(3) Adaklu Anyigbe - Insider (Vedome Ewe): Joseph Etornam Agbesi, Mother: Sarah Esinam
Kwashie, Father: John Senyo Agbezuge;- Outsider (Anlo Ewe): Joseph Etornam Dogbatse, Mother: Sarah Esinam Amegashie,
Father: John Senyo Dogbatse;(4) Ketu South - Insider (Anlo Ewe): Joseph Etornam Dogbatse, Mother: Sarah Esinam
Amegashie, Father: John Senyo Dogbatse;- Outsider (Vedome Ewe): Joseph Etornam Agbesi, Mother: Sarah Esinam Kwashie, Father:
John Senyo Agbezuge;
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Names were chosen to emphasize tribal differences between the two candidates. The
candidate, the candidate’s mother, and the candidate’s father were each given an English
name, a Day name3 , and a Tribal Surname. For most of the districts, the candidate’s and
candidate’s parent’s day names conveyed the individuals’ ethno-linguistic group, while the
tribal surname conveyed the tribe and/or part of the country the individuals are from. For
instance, in Bosome Freho the insider candidate was Asante and the outsider candidate was
Akyem. Asantes and Akyems are both part of the Akan ethno-linguistic group, and as such
their day names are virtually the same. In this case the candidate’s and mother’s surnames
convey the tribe of the candidate, while the candidate’s, mother’s and father’s day names
convey membership in the Akan ethno-linguistic group. The same is true of Ewe candidates in
Adaklu Anyigbe and Ketu South where the candidate’s and mother’s surname conveyed either
Vedome-Ewe or Anlo-Ewe membership while the candidate’s, mother’s and father’s day names
connoted membership to the broader Ewe ethno-linguistic group.
In the case of Mfantsiman and AOB, the tribal differences separating Fantes (the insider)
from Asantes (the outsider) also allowed me to manipulate the individuals’ day names to reflect
their tribal identities. Thus, for Mfantsiman, the insider candidate is Joseph Ebo Robertson
while the outsider candidate is Joseph Kwabena Opokuware. While the other districts’
candidates and family names convey tribal information with two names, the candidate and the
(5) Mfantsiman - Insider (Fante): Joseph Ebo Robertson, Mother: Sarah Kukua Eshun,Father: John Kweku Robertson;- Outsider (Asante): Joseph Kwabena Opokuware, Mother: Sarah Akua Prempeh, Father:
John Kweku Opokuware;(6) Asikuma Odoben Brakwa - Insider (Fante): Joseph Ebo Robertson, Mother: Sarah
Kukua Eshun, Father: John Kweku Robertson;- Outsider (Asante): Joseph Kwabena Opokuware, Mother: Sarah Akua Prempeh, Father:
John Kweku Opokuware.
3 A Day name is a name given to a child based on the day of the week on which they wereborn. Day names generally differ for males and females, but are often phonetically related (e.g.Kwabena (male) and Abena (female) Akan day names for those born on Tuesday). Day namesdiffer by ethno-linguistic group and sometimes tribe in Ghana.
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mother’s respective surnames, in Mfantsiman and AOB the candidate and family convey tribal
information with five of their names: all three individuals’ day names and the candidate’s and
mother’s surnames.
The results from this test are mixed and surprising. When comparing average candidate
rating, Question 2, for insider and outsider candidates, the outsider candidate received a higher
average rating than the insider candidate for every single district. Further, in Bosome Freho,
Agotime Ziope, and AOB, which also happen to be the three districts selected for their unusual
voting behaviors, the differences between candidate ratings were significant at a p<0.1 level or
better (Table 8-1).
Probing further to Question 3, whether or not the respondent says they would vote for the
candidate, the treatment effect on the candidate’s name no longer significantly predicts the
response except for in one district. Ketu South respondents now strongly say they will vote for
the Anlo Ewe (insider) candidate (0.927) as compared to the Vedome Ewe (outsider) candidate
(0.688) (Table 8-2).
To better understand what is happening here, I use linear regressions to predict
respondents’ ratings of candidates, logistic regressions to predict respondents’ answers about
whether or not they will vote for the candidate, and district-level bar charts to decipher
patterns in respondents’ open-ended explanations about why they will or will not vote for the
candidate.
8.1.1 Linear Regressions Predicting Candidate Ratings
In Tables 8-3 - 8-5 I present linear regressions predicting candidate rating within each
district. I run two models for each district, rather than an overall model for the entire sample,
because the different candidate names paired with the unique tribal histories and circumstances
in each district requires separate tests to determine why a candidate was or was not favored in
each place. In each model, outsider candidates are controlled for, as well as an array of controls
relating to political participation, trust, xenophobia, ethnicity, and political and economic
perceptions.
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First, I control for age because of the possibility that respondents of different ages might
respond to the experiment differently, though I do not have any particular expectations about
the direction of this potential effect. I next control for whether respondents’ attended a
political rally (rally) in the 2012 campaign cycle to control for level of political participation.
Those respondents who are more interested in politics might be more critical or more accepting
of the candidate as compared to those who are less interested. Third, I control for whether
the respondent is a member of the NDC because this was likely to impact respondents’
impressions of a NPP candidate in the NPP strongholds, and a NDC candidate in the NDC
strongholds and competitive districts. Fourth, I control for whether respondents view their
living conditions as better or worse than other Ghanaians across the country as both an
individual wealth indicator as well as a control for the extent to which the respondent feels
government intervention and/or effective leaders are necessary.
Fifth, I control for whether or not the respondent feels Ghana’s political parties have
different ideologies (diff.ideo), partially because the fictional candidate is attached to a
particular political party and because this question is reflective of the degree of cynicism with
which the respondent engages with Ghana’s political system. Whether or not the respondent
views themselves as a consistent or swing voter (vote stays the same) could potentially impact
whether or not the respondent would be open-minded about supporting the fictional candidate.
The degree of trust of speakers of different dialects is controlled for because the outsider
candidate speaks the same language as the insider candidate, but a different local dialect.
Eighth, I control for whether or not respondents feel they are likely to vote for a MP not born
in the area (MP born) as a control for the willingness of the respondent to accept outsiders.
Education is controlled for next because individuals with higher levels of education tend to
be more politically informed and/or engaged with politics. The tribal groups dominant in the
districts under analysis are controlled for to test for whether it is respondents of the insider
group who have particular opinions about the insider versus outsider candidate. Finally, a last
control is whether or not the respondent agrees that the election of the MP brings change
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within the community (MP Election change). The more the respondent disagrees with that
sentiment, the higher the response on a 1 to 4 scale.
What the results generally show is that, after controlling for other factors, a candidate’s
outsider status is not a significant predictor of candidate rating in five of the six districts. It is
only in Bosome Freho where the respondents who received the outsider candidate significantly
increased their ratings of the candidate. That a candidate’s outsider tribal background did
not result in lower candidate ratings in any of the districts, and that the outsider identity
resulted in higher candidate ratings in one of the districts, runs counter to the expected effect
of outsider candidates.
In addition to the effect of candidate outsider on Bosome Freho respondents’ candidate
ratings, older respondents, those who believe the political parties have different ideologies
(diff.ideo), those who vote for one political party (vote stays the same), those who are
more likely to vote for a MP who was not born in the area (MP born), medium educated
respondents (as opposed to low education respondents) (mededu), Asantes, and those who do
not believe the election of the MP brings change within the community (MP Election change)
are all significantly more likely to have given the candidate a higher rating. Variables associated
with significantly lower ratings in Bosome Freho include those from NDC members, those
whose living conditions is worse than other Ghanaians, and respondents who do not trust
speakers of different dialects (Table 8-3).
As for Birim South respondents, while outsider candidates were not a significant driver
of respondent candidate ratings, older respondents, those with self-described worse living
conditions, those who admit to being less likely to vote for a MP who was not born in the
area (MP born), Akyems, and respondents who do not believe MP elections bring change
(MP Election change) were all significantly associated with higher candidate ratings (Table
8-3).
In Adaklu Anyigbe and Ketu South, outsider candidates were not a significant driver
of candidate ratings (Table 8-4). As a respondent gave a more positive rating for the 2008
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NDC government’s handling of the economy, the respondent was significantly associated with
increased candidate ratings in Adaklu Anyigbe and decreased candidate ratings in Ketu South.
Respondents who negatively rated the 2000 NPP government’s handling of the economy,
Ewes, and those who only vote for one political party (vote stays the same), are all significantly
associated with higher candidate ratings in Adaklu Anyigbe but not in Ketu South. Finally,
respondents who were more likely to say they would vote for a MP who was not born in the
area (MP born) were significantly associated with lesser candidate ratings in Adaklu Anyigbe
but higher candidate ratings in Ketu South.
Finally, outsider candidates were not significantly associated with candidate ratings
in either Mfantsiman or AOB (Table 8-5). First, in Mfantsiman’s full model, those with
better living conditions and who vote for one party were significantly associated with
decreased candidate ratings, while those who gave positive ratings of the state of the current
economy, and those who believe MP elections do not bring change (MP Election change) were
significantly associated with increased candidate quality ratings. As for AOB, NDC members
and those who believe MP elections do not bring change (MP Election change) were also
significantly associated with higher candidate ratings. Respondents who trust speakers of
different dialects, and those who are more likely to vote for an MP who was not born in the
area were significantly associated with depreciated candidate ratings.
In conclusion, because an outsider candidate was only a significant predictor of candidate
ratings in Bosome Freho, there is likely something to be said about Asantes feelings about
Akyems in Bosome Freho. I cannot easily explain why Asantes in Bosome Freho would favor
Attafuah for MP over Opokuware for MP. Opokuware is a very prominent Asante name in
Ghana, and it was the surname of the Asantehene who ruled from 1970 to 1999. Perhaps there
is some underlying relationship with Bosome Freho residents and the name Opokuware that
biases respondents against the insider candidate. Or perhaps, for whatever reason, Bosome
Freho residents are more trusting of outsiders and/or Akyems than Asantes.
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Still, it is amazing that no district favored a ‘son of the soil’ in terms of candidate ratings.
That the candidate description depicted a person who had lived and worked in the constituency
for 15 years as a teacher and an assemblyman was apparently enough to surpass any effect
the candidate’s tribal background had on respondents’ assessments of him as a resident of the
district.
8.1.2 Logistic Regressions Predicting Candidate Votes
Though t-tests of difference showed higher candidate ratings for outsider candidates rather
than insider candidates (Table 8-1), only in Ketu South did t-tests of difference significantly
show a strong preference for the insider candidate when respondents were asked if they would
vote for the candidate (Table 8-2). In Tables 8-6 through 8-8 I present odds ratios for logit
models which predict whether respondents would vote for the candidate within each district.
Across all the districts, it is only in Adaklu Anyigbe and Ketu South that outsider
candidates change the odds of a respondent voting for the candidate. In both of these
districts, outsider candidates decreased the odds of a respondent saying they would vote for the
candidate by 0.259 in Adaklu Anyigbe and 0.313 in Ketu South.
In Bosome Freho (Table 8-6), NPP members and Asantes were significantly more likely to
increase the odds of voting for the candidate, while respondents with better living conditions
and those who suggested it was likely the 2012 NDC government would develop the area
significantly decreased the odds of the respondent having voted for the candidate. For Birim
South, Model 4, older respondents and NPP members increased the odds of saying they would
vote for the candidate, while those with better living conditions, whose vote stays the same,
who is likely to support an MP not born in the area, and who believes Ghana’s political parties
ideologies are more different decreased the odds of a respondent saying they would vote for the
candidate.
The odds of voting for the candidate decreased when a respondent was exposed to an
outsider candidate and if the respondent attended a political rally in 2012 in both Adaklu
Anyigbe and Ketu South. Respondents with better living conditions and Ewes increased the
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odds of a respondent voting for the candidate in Adaklu Anyigbe while only those who said
they would vote for an MP not born in the constituency significantly increased the odds of a
respondent voting for the candidate in Ketu South (Table 8-7).
Finally, Table 8-8 displays the odds ratios for respondents saying they would or would not
vote for the candidate in Mfantsiman and AOB. Outsider candidates were not a significant
driver of changes in the odds ratios for either Mfantsiman or AOB. For Mfantisman, those who
had attended a rally, those who would vote for an MP not born in the area, and those who
feel it is likely that big men and women can find out how they voted significantly decreased
the odds of a respondent voting for the candidate, while saying that MP elections do not bring
change significantly increased the odds of voting for the candidate. For AOB, respondents
whose votes stay the same and those who would not vote for an MP not born in the area
significantly decreased the odds that a respondent would vote for the candidate, while Fantes,
those who feel it is likely that big men and women can find out how they voted, and those
who say MP elections do not bring change significantly increased the odds of voting for the
candidate.
Overall, though candidate ratings may have been in the favor of outsider candidates
in Bosome Freho and AOB, these effects faded away when respondents were asked if they
would vote for the candidate. In the logit models presented it is only respondents in Adaklu
Anyigbe and Ketu South whose odds of having voted for the candidate significantly decrease
when the candidate is an outsider. That Ewes are often said to be more ethnic-oriented
than other groups in Ghana may help explain this result. But it is interesting that tribal
differences between candidates was only significant in the two districts dominated by the Ewe
ethno-linguistic group whose tribal differences are not captured by the Ghana census.
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8.1.3 Categorical Analysis
Finally, in this last section I present bar charts depicting the categories of open-ended
responses used by respondents to explain why they would or would not vote for the candidate.4
Question 4 open-ended responses are divided into 8 categories:
(1) I will vote for him because of what the candidate can do; his qualities, past work,development evidence, etc.(2) I will vote for him because he is my party member(3) I will not vote for him because he is not my party member(4) I will vote for him because of who he is/he knows us/he came back and stayed here(5) I will not vote for him because he is doesn’t know us/hasn’t stayed long enough/wedon’t know him(6) I will vote for him because I know the candidate5
(7) I will vote for him for some other reason(8) I will not vote for him for some other reason
4 I also used Word Tag Clouds (not shown) to qualitatively analyze the open-endedresponses. The overall results show that respondents were generally interested in what thecandidate can do. Party membership matters more in the NPP strongholds. Within theNDC strongholds, ‘community’ and ‘development’ were stated with greater frequency inAdaklu Anyigbe, whereas fewer words stood out from responses from Ketu South, though theprominence of ‘educated’ was relatively unique to the two NDC strongholds. Finally, whetherthe candidate can ‘help’ is of greater concern in the competitive districts, Mfantsiman andAOB, with ‘community/area’ and ‘develop’ not lagging far behind.The word tag clouds are interesting, first, because they are generally positive in their
outlook. ‘Can’ is a dominant word used across the districts as opposed to can’t or can not.As the districts whose residents were significantly less likely to Vote for candidate outsiders,Adaklu Anyigbe and Ketu South’s word tag clouds were also largely positive in their outlook.Adaklu Anyigbe respondents focused on community and development, while Ketu Southrespondents were more varied in their word choices (i.e. not many words stood out for theircommon usage). Prior work in the Volta Region has alerted me to the fact that Ewes generallyvalue education and it is thus not surprising that respondents in both of these districts moreoften noticed and reverberated that the candidate was educated.
5 A number of respondents within each district felt that, after the candidate description wasread, that they knew the imaginary candidate. Respondents were only told after the surveythat the candidate was imaginary. Still, this was an unexpected result. That some respondentsfelt they knew the candidate may be because there are only so many elites in districts outsideof major cities, because small district populations mean particularly prominent residents arerarely ‘unknown’, or because the candidate’s name or description was similar enough to anexisting person that respondents decided they probably knew him.
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From Figure 8-1 above, it is clear that most respondents (59.5%) said they would vote
for the candidate because of his potential effectiveness/what he can do (i.e. his qualities, work
and educational background, past developmental work, etc.). The next most commonly cited
response (17.8%) cited something about the fact that the candidate is living in the area or is
from the area as making him an ideal candidate. 9.9% said they liked the candidate because
he is their party member, 3.7% believed they personally knew the candidate, and 4.4% made
another sort of positive statement about the candidate. Overall only 13.1% said they would
not vote for the candidate because he was not their party member (6.9%), is unknown in the
community (1.8%), or some other sort of negative statement about the candidate (4.4%).
In Bosome Freho (Figure 8-2), respondents who received the candidate insider (control)
treatment were less likely to say they would vote for the candidate based on his qualifications
and more likely to say they would vote for the candidate because of his political party, despite
the fact that an equal number of self-identified NPP members received both the candidate
insider and candidate outsider groups in Bosome Freho. Perhaps something about the heavy
Asante traditions associated with the name Opokuware (insider candidate) made people
more likely to cite the party legacy. Similarly, a greater proportion of respondents receiving
the insider treatment were more likely to say they would not vote for the candidate because
the candidate is not in my party. However, looking back at the sample, 23 of 35 (65.7%) of
self-identified NDC members happened to receive the candidate insider treatment in Bosome
Freho, which may account for this difference.
As far as the candidate’s identity, here’s where things get interesting. 26.2% of those
receiving the candidate insider treatment said that the candidate would be effective because
of who he is (i.e. he lives in the area and/or is from the area) as compared to 31.8% of
respondents receiving the candidate outsider treatment. This suggests two possibilities. First,
the respondents may not have recognized the tribal identities of the candidates. While it is
virtually impossible for a Ghanaian not to know that Opokuware is an Asante name, other
Akan names are perhaps less famous and possibly less recognizable for that reason. So it
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is possible that Bosome Freho respondents did not recognize Attafuah as an Akyem name
or, though much less likely, as a non-Asante name. However, 5.2% of respondents receiving
the candidate outsider treatment said they would not vote for the candidate because ‘we
don’t know him’, ‘he hasn’t stayed here long enough’, etc, as compared to 0% of respondents
receiving the candidate insider treatment.
This leads to a second possibility: that respondents may or may not have recognized
Attafuah as an Akyem, but the fact that he had stayed in the community for a substantial
period of time and that his mother lived there were more important than the candidate’s
particular tribal background.
In comparison to Bosome Freho, respondents in Birim South (Figure 8-3) were more likely
to justify their support of the candidate using the candidate’s qualifications (i.e. what he can
do). Interestingly, despite the fact that both self-described NPP members and NDC members
were virtually split between the two treatments (95 respondents versus 97 respondents; 45 and
40 respondents), a greater proportion of respondents receiving the candidate insider treatment
said they wouldn’t vote for the candidate because he was not in their party (13.1% versus
10.0%) while almost twice the proportion of respondents receiving the candidate outsider
treatment said they would vote for the candidate because he was their party member. Again,
for NPP members, that the outsider candidate is named Opokuware might emphasize the
importance of the Asante-NPP party legacy, even for non-Asantes. Alternatively, it might be
that Birim South residents have to use his party status to justify their support of the outsider
candidate since they cannot justify their support based on his being a native of the area.
Finally, that the candidate stays in the area and/or is from the area is of comparatively
less importance to Birim South respondents. Still, at 11.9%, a greater proportion of
respondents receiving the candidate outsider treatment said they would vote for the candidate
because of where he stayed/was from, as compared to 8.1% receiving the insider treatment.
Again this suggests that the candidate stayed in the community for such a long time, and
worked as a teacher, overcame the outsider candidate’s Asante background.
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Responses were even less varied in Adaklu (Figure 8-4) as compared to Birim South.
The vast majority of respondents in either treatment group cited the candidate’s abilities as
the reason for their vote for him. And, despite the fact that 12 out of 21 NPP members in
Adaklu received the candidate insider treatment, that the candidate was not a member of the
respondent’s political party was only cited twice (1.3%) by respondents receiving the candidate
outsider treatment. That the candidate was a member of the NDC was not given as a reason
for supporting him by any respondent in either treatment group. Third, that the candidate
lived in the area or was from the area was cited by even fewer responses in Adaklu Anyigbe,
with virtually no difference in the proportion of responses in either the candidate insider or
candidate outsider treatment group. Further, a similar proportion of respondents in both
groups said they wouldn’t vote for the candidate because the community didn’t know him or he
had stayed outside for too long (5.2%- candidate insider; 4.6%- candidate outsider).
Of all the districts, Ketu South (Figure 8-5) respondents were the most likely to be
missing in their explanation for why they would or would not vote for the candidate. Whereas
39 respondents in all 5 other districts were missing for Question 4, another 39 respondents
within Ketu South alone were also missing for Question 4. Of these, 26 of 39 responses
(66.6%) were missing from the candidate outsider treatment.
In Ketu South, a greater proportion of respondents in the candidate insider treatment
justified their support of the candidate based on his capabilities (78.8% vs. 51.5%) as well
as on the fact that he lives in the area and/or is from the area (9.6% vs. 2.3%). Finally, a
relatively high proportion of respondents gave positive-other and negative-other rationales for
voting or not voting for the candidate. The majority of the ‘positive-other’ responses in Ketu
South are statements qualifying the respondent’s support, such as I will vote for him ‘if he can
develop the community’, ‘if he will deliver’, ‘provided his mother’s character’, etc. Similarly, the
‘negative-other’ responses were largely made up of respondents who said they wouldn’t vote
for the candidate because they personally do not know him and/or haven’t seen him as well as
respondents who expressed preference for the current MP or another candidate.
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In comparison to the other districts discussed thus far, Mfantsiman respondents’ rationales
for supporting or not supporting the candidate (Figure 8-6) are almost as varied as Bosome
Freho. About 50% of respondents in the treatment and control group cited the candidate’s
capabilities as their reason for voting. A higher proportion of respondents in the candidate
outsider treatment group said they would vote for the candidate because he is in their political
party. But, for Mfantsiman, 61 out of 114 (53.5%) self-declared NDC members happened to
be exposed to the outsider treatment, as compared to 46.5% of the candidate insider control
group, which probably accounts for some of that difference.
Importantly, Mfantsiman respondents who cited the candidate living in the area or
being from the area as their reason for their vote for him is about 10% higher for the
candidate insider control group than it is for the candidate outsider treatment group. Of
all the candidates’ identities who could be mis-identified, the Robertson (Fante) - Opokuware
(Asante) candidate pairing in Mfantisman and AOB are the least likely to be confused.
But, having voted in an Asante MP (Asamoah Boateng) in the recent past, it perhaps also
makes sense that almost no respondents challenged the outsider candidate as unknown in the
community.
The responses from AOB (Figure 8-7) are very similar in proportion to those from
Mfantsiman. Around 50% of respondents in both the candidate insider control group and the
candidate outsider treatment group cited the candidate’s effectiveness/capabilities as their
reason for voting for him. The next largest category were respondents who would vote for
the candidate because he would be effective because of who he is (i.e. he lived in and/or
was from the area). Like Mfantsiman, about 10% more respondents in the candidate insider
control group cited this reason as compared to the candidate outsider treatment group. Again,
like Mfantsiman, no respondent challenged the candidate as being unknown in the area. For
AOB, about 40% of each group’s respondents were self-declared NPP members and a similar
proportion of respondents cited the candidate’s party as the reason for voting for him. About
30% of each group’s respondents were self-declared NDC members yet about 9.0% of the
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candidate insider control group respondents cited the candidate’s political party as the reason
for not voting for him as compared to 14.2% for the candidate outsider treatment group.
In conclusion, that Bosome Freho respondents were more likely to give the outsider
candidate higher ratings in comparison to the insider candidate, even after holding for
other factors in the linear regressions, is difficult to understand. Further, that no districts’
respondents were more likely to give the insider candidate higher ratings is surprising. But,
when we turn to whether or not a district’s respondents would vote for the candidate, two
districts respondents stand out for being more likely to vote for the insider candidate. That
these two districts, Adaklu Anyigbe and Ketu South, are dominated by Ewes would initially
be unsurprising to some who consider the Ewes more ethnically-oriented than other tribes.
However, the candidate names being tested were both Ewe names as the test was rather
a tribal test than an ethno-lingusitic bias test. If Ewes were more ‘inward-looking’ as is
sometimes said, then we might expect that these two districts’ respondents would be the least
likely to differentiate between an insider and outsider candidate so long as both candidates
are Ewes. Instead what we see is that Adaklu Anyigbe residents are less likely to vote for a
candidate from the south of the Volta Region while Ketu South residents are less likely to
vote for a candidate from the middle of the Volta Region/northern Ewe territory. That tribal
differences within the Ewe ethno-linguistic group are not captured by the Ghana census is
surprising because, as is clear from my research and as this test result emphasizes, there are
politicized differences between Ewe tribes.
Finally, it was clearly important to respondents that the candidate had such a robust
education and work background, as answers like these were used by 59.5% of respondents to
explain why they would vote for the candidate. However, the second category used by 17.8%
of the sample to explain why they would vote for the candidate was that the candidate would
be effective because of his identity (i.e. that he was from the area, lived in the area, knew
the people and their problems, etc.). So the candidate’s status as an insider or outsider did
matter, but apparently respondents in four of the districts did not define that insider/outsider
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status solely based on the candidate’s tribal background. In the two districts where the
candidate’s name did matter, it was not insider/outsider status defined based on Ewe-ness
but rather intra-Ewe tribal identities which are not captured in Ghana’s Census and are largely
misunderstood by Ghanaians from other ethno-linguistic group backgrounds.
8.2 List Experiments to Hide Undemocratic Beliefs/Behaviors
To further test for Hypothesis 1: Identity-Based Voting and Hypothesis 3: Clientelistic-Based
Voting, I employed three list experiments. List experiments are used such that the response
being tested is not immediately clear to the respondent when answering a question. Respondents
are ideally supposed to feel more comfortable sharing sensitive beliefs or behaviors in list
experiments since neither the survey administrator delivering the questionnaire nor anyone else
will know whether any individual respondent identified the sensitive item of interest on the list
as their own belief/behavior. The list experiments I ran tested for (a) Religious Biases, against
Muslims in particular, in voting for the President of Ghana and (b) Clientelism impacts on
respondents’ 2012 votes for President or Vice President.
The entire survey sample was split into two, such that half received the control and half
received the experimental manipulation. Version A delivered 5 items in the list experiment on
religious bias (the manipulation) and 4 items each in the two clientelism list experiments (the
control). Version B presented 4 items in the religious bias list experiment (the control) and 5
items on the two clientelism list experiments (the manipulation). For the Religious Bias List
Experiment, respondents were told: “I’m now going to read a list of five things that sometimes
make people angry or upset. After I read all five statements, just tell me how many of them
upset you. I don’t want to know which ones, just how many.” Version A respondents were then
read a list with 5 items:
a The way gasoline prices keep going upb The amount of money Parliamentarians receivec People’s preference for hospitals over traditional medicined That policemen and women carry guns
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e Having a Muslim as President of Ghana6
Respondents who received Version B were read the same information, excluding item e,
“Having a Muslim as President of Ghana”. Testing for biases against Muslim politicians is
an increasingly relevant question in Ghanaian politics. The politicization of religious divides
has consistently been a close secondary to ethnic or class divides. But, with the election of
Vice President Alhaji Aliu Mahama, who is Muslim, during Kufuor’s NPP regime, and the
nomination of Mahamudu Bawumia as the VP on the NPP Presidential ticket in 2008 and
2012, have meant the possibility of having a Muslim President of Ghana is increasingly likely.
However, comments made by politicians in the media suggest that this possibility is still
controversial.7
If having a Muslim as President of Ghana upset some respondents, then we should see
a significant difference between the average number of items selected in sub-samples Version
A and Version B. When comparing the average number of items selected that upset the
6 It is important to note that the items on the list were selected such that at least one itemwould be very unlikely to upset a respondent. This is done to increase the chances that norespondent is upset by all 4 or 5 items, thus canceling out their anonymity in answering thequestion. In this case, the two questions that were not expected to make respondents upset areItem c: people’s preference for hospitals over traditional medicine and Item d: That policemenand women carry guns. That people prefer hospitals over traditional medicine is not such ataboo subject in Ghana that respondents would be likely to be upset about it. Secondly, whilerespondents in the United States might say they are upset that police carry guns due to thepoliticization of police violence against citizens, this topic is not politicized in Ghana as thereare very few events where police use their guns against citizens. As such, that police men andwomen carry guns is unlikely to make respondents upset.
7 For instance, in the 2011 Wikileaks release, Fiifi Fiavi Kweetey, then Deputy Ministerof Finance and Economic Planning, was exposed for having explained to officials of the USembassy that a Mulsim could never become the President of Ghana. Kwetey later defended hiscomments explaining that the NPP would use Muslim VPs to attract Muslim voters but wouldnever nominate a Muslim/Northerner VP to succeed to the Presidential nomination. Further,since holding the VP slot on the NPP Presidential ticket, Bawumia receives a great deal ofcriticism from fellow NPP members, and derogatory comments about his Muslim/Northernerbackground are sometimes made.
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respondent, the average for Version B (4 items) was 1.771 while the average for Version A
(5 items) was 1.777 (Table 8-9). The difference between these two means is not statistically
significant and thus suggests that including item e on the Question 29’s List Experiment
did not have a statistically significant effect on how many items were selected. Put simply,
this sample’s respondents did not appear to get upset at the thought of having a Muslim as
President of Ghana.
However, Table 8-10 presents the district-level results from the Muslim bias list
experiment. The differences in mean item responses selected were significant and in the
correct direction for Bosome Freho (p<.01), Adaklu Anyigbe (p<0.1), and Asikuma Odoben
Brakwa (p<0.05). In the case of Mfantsiman, the average number of items selected was
actually higher for the 4-item questions versions than the 5-item versions. So it appears that
the having a Muslim as President of Ghana did have a statistically significant effect in Bosome
Freho, Adaklu Anyigbe and AOB.8
Turning to the Clientelism List Experiments (Table 8-11), respondents who received
Version A of the survey were read four items for Questions 31, how many items affected the
respondents’ vote in the 2012 Presidential election, and Question 32, how many items affected
the respondents’ vote in the 2012 Parliamentary election. Respondents who received Version B
of the survey were read five items:
a The height of the Presidential (Parliamentary) candidateb The policies of the Presidential (Parliamentary) candidatec The likelihood of the Presidential (Parliamentary) candidate winningd Your family’s opinion about the Presidential (Parliamentary) candidate
8 These three districts, Bosome Freho, Adaklu Anyigbe, and Asikuma Odoben Brakwa, eachrepresent a NPP stronghold, a NDC stronghold, and a competitive district, respectively. As myresearch was primarily concerned with politicized ethnicity rather than religion, I do not have aclear sense about why respondents in these three districts would have a greater sensitivity to aMuslim President as compared to the other three districts. More tests should be done to verifythis result and identify the causal link between respondents’ sensitivity to this idea in somedistricts rather than others.
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e Payouts, in the form of money or other gifts, provided by the Presidential (Parliamentary)candidate or his party boys9
If Item e: payouts provided by the candidate or his party boys, affected respondents’ votes
for President or MP, we should see a statistically different average number of items selected
in Question 31 and Question 32. As Table 8-11 demonstrates, the difference in the average
number of responses selected for Version A and B is significant for Question 31 (p<0.05)
and Question 32 (p<0.1). In Question 31, on average, respondents who received Version A
(4 items) selected 1.543 items as compared to 1.615 items in Version B (5 items). Similarly,
in Question 32, respondents with Version A (4 items) selected an average of 1.507 items as
compared to 1.570 items selected by respondents with Version B (5 items). It appears then
that Ghanaians may not hold secret politicized biases against Muslims, but that they will admit
to clientelistic payouts having impacted their votes when it is indirectly asked in an anonymous
list experiment.
However, in Tables 8-12 and 8-13 I consider the district-level responses for the Clientelism
List Experiments. The district-level results pertaining to the 2012 Presidential election shows
that the significantly different mean number of responses presented in Table 8-11 is actually
triggered by the statistically significant greater number of responses for the 5-item versions
in Mfantsiman (p<0.000) and AOB (p<0.000), the competitive districts. Though this result
could mean that respondents in the competitive districts are simply more honest, what is more
likely is that clientelistic payments or gifts are more common in these areas where the MP seat
is more up for grabs. Secondly, a very similar result is presented in Table 8-13, but this time
for the 2012 Parliamentary races. Here again it is only the competitive districts (Mfantsiman-
9 As was the case with the Religious Bias List Experiment, one of the responses should haveaffected very few respondents’ votes. In this case the unlikely item was Item a: The heightof the candidate. Though candidate height may play a part in peoples’ perceptions aboutpoliticians in some contexts, candidate height appears unpoliticized in Ghana, particularly sincethe 2008 and 2012 NPP Presidential candidate, Nana Akufo Addo, is relatively short.
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p<0.000; AOB- p<0.001) whose respondents are significantly more likely to select more items
on the 5-item version than the 4-item version of the list experiment.
This list experiment bolsters the findings from Question 34, where respondents were
asked if they more strongly agreed that ‘When individuals take gifts from party officials and
party ‘boys’, they vote for that political party during the election’ as compared to ‘When
individuals take gifts from party officials and party ‘boys’, they sill vote the way they want, and
not necessarily with the political party that gave the gift’. As presented in Table 8-14, about
81% of respondents in the sample agreed with Statement 2, that individuals still voted the way
they wanted even if they took gifts from a political party. Yet about 19% of the sample still
agreed that gifts during election time affected people’s votes. Between the list experiment and
this indirect question, it does seem that clientelistic gifts have somewhat of an effect on voting
behavior, though this may be limited to areas with competitive MP races.
8.3 Discussion
In conclusion, even when testing for the isolated effects of ethnic or religious biases, or the
effects of clientelistic-inducements, the results are mixed. Within the tribal experiment, one
district favored the ethnic outsider candidate in candidate ratings, while all the others did not
show a difference in candidate ratings when controlling for other factors. But when asked if
the respondent would vote for the candidate, two districts’ respondents, the NDC strongholds,
responded that they would vote for the insider candidate by a statistically significant margin
over the outsider candidate. Second, there appeared to be no support for biases against Muslim
candidates by the overall sample, but when broken down to the district level, three districts’
respondents did appear to be upset by the idea of a Muslim President of Ghana. Finally,
the list experiments testing for the effects of clientelistic-inducements on respondents’ votes
found a significant difference in both the Presidential and Parliamentary questions. However,
when broken down to the district level, it was actually only respondents from the competitive
districts which fueled this outcome.
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Given that it was difficult to ascertain support for Hypothesis 1 (Identity-Based Voting)
even via indirect means or hidden list experiments, it is difficult to tell whether competitive
local politics is having a positive or negative effect on tribal/ethnic or religious biases. The
results suggest that further implicit tests should be conducted to verify the effect of these
factors on voting. That the candidate experiment employed in this survey did not have the
expected effect might mean that respondents are not biased against candidates who are not
‘sons of the soil’ or that the fact that the hypothetical candidate had lived and worked in the
areas as a teacher and assemblyman for 15+ years allowed respondents to largely overlook the
candidate’s tribal background. Further, it is interesting but unclear why bias against a Muslim
President would appear to be a factor in only half of the districts: one NPP stronghold, one
NDC stronghold, and one competitive district.
Finally, the results from the clientelistic list experiment suggests that clientelistic
inducements are more common in constituencies which have a history of voting in MPs of
different political parties. This finding demonstrates the importance of testing for sensitive
behavior with list experiments, considering the very small support for Clientelistic-Based Voting
(Hypothesis 3) in the analysis of more direct survey questions in Chapters 6 and 7. Though
this result needs to be verified, if true on a national-level, it also suggests that the level of
political competition between DCEs and MPs does not drive up clientelistic-inducements as
compared to constituencies with hotly contested battles for MP and Presidential votes. Of
course, each of the results from the tests showcased in this chapter should be verified with
further implicit tests of tribal/ethnic voting bias, religious bias, and clientelistic-inducements in
Ghana and other sub-Saharan African nations.
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Table 8-1. Average candidate ratings t-test per district
District x, y mean of x mean of y t df p-value
BosomeFreho
outsider,insider
7.369 6.755 -2.159 298 0.032**
Birim South outsider,insider
7.145 6.816 -1.203 315 0.230
AgotimeZiope
outsider,insider
7.637 7.147 -1.798 260 0.073*
Ketu South outsider,insider
6.877 6.641 -1.052 306 0.294
Mfantsiman outsider,insider
7.255 7.497 1.044 316 0.298
AsikumaOdobenBrakwa
outsider,insider
7.570 7.031 -1.829 317 0.068*
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-2. Vote for candidate? t-tests
District x, y mean of x mean of y t df p-value
BosomeFreho
outsider,insider
0.903 0.852 -1.371 314 0.172
Birim South outsider,insider
0.875 0.855 -0.513 317 0.609
AgotimeZiope
outsider,insider
0.919 0.877 -1.137 261 0.257
Ketu South outsider,insider
0.688 0.927 3.509 287 0.001***
Mfantsiman outsider,insider
0.861 0.890 0.780 319 0.436
AsikumaOdobenBrakwa
outsider,insider
0.859 0.880 0.545 318 0.586
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-3. Linear regression predicting candidate rating
Dependent variable:q2
Bosome Freho Birim South(1) (2) (3) (4)
candidateoutsider 0.846∗∗∗ 0.496∗ 0.252 0.282(0.258) (0.270) (0.276) (0.293)
age 0.008 0.018∗∗ 0.024∗∗ 0.023∗
(0.008) (0.008) (0.011) (0.012)rally 0.733∗∗∗ 0.284
(0.248) (0.296)NDCmember -2.133∗∗∗ -1.643∗∗∗ -0.415 -0.231
(0.395) (0.374) (0.316) (0.353)living condition -0.700∗∗∗ -0.729∗∗∗ -0.559∗∗∗ -0.557∗∗∗
(0.171) (0.174) (0.123) (0.148)diff.ideo 0.707∗∗ -0.168
(0.277) (0.250)vote stays thesame
0.555∗∗ -0.177
(0.256) (0.274)trust diffdialect -0.317∗∗ -0.104
(0.138) (0.150)MP born 0.436∗∗∗ -0.289∗
(0.095) (0.152)highedu 0.580 -0.428
(0.608) (0.714)mededu 0.777∗∗∗ -0.364
(0.246) (0.327)asante 1.047∗∗∗
(0.291)akyem 0.730∗∗
(0.306)MP Election change 1.373∗∗∗ 0.685∗
(0.330) (0.364)Constant 5.665∗∗∗ 2.942∗∗∗ 5.688∗∗∗ 6.212∗∗∗
(0.415) (0.591) (0.543) (0.733)Observations 62 205 282 253Adjusted R2 0.271 0.515 0.093 0.121Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-4. Linear regression predicting candidate rating
Dependent variable:q2
Adaklu Anyigbe Ketu South(1) (2) (3) (4)
candidateoutsider 0.059 0.004 0.335 0.384(0.307) (0.319) (0.286) (0.289)
age -0.005 0.001 0.011 -0.0001(0.009) (0.010) (0.009) (0.009)
rally -0.003 0.183(0.317) (0.283)
NDCmember 0.446 0.340 -0.327 -0.103(0.375) (0.399) (0.373) (0.392)
living condition 0.233 0.364∗ 0.080 0.066(0.202) (0.215) (0.144) (0.157)
trust diffdialect -0.220 -0.036 0.196 0.127(0.230) (0.237) (0.144) (0.151)
econ current -0.051 -0.097(0.139) (0.122)
ewe 2.167∗∗∗ 0.178(0.778) (0.824)
vote stays thesame
0.425 -0.264
(0.278) (0.233)MP born -0.221 0.566∗∗∗
(0.149) (0.130)Constant 7.350∗∗∗ 4.990∗∗∗ 6.237∗∗∗ 5.629∗∗∗
(0.592) (0.900) (0.514) (0.925)Observations 211 200 250 227R2 0.021 0.082 0.027 0.120Adjusted R2 -0.008 0.038 0.003 0.083Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-5. Linear regression predicting candidate rating
Dependent variable:q2
Mfantsiman AOB(1) (2) (3) (4)
candidateoutsider -0.337 -0.209 0.412 0.527(0.253) (0.253) (0.343) (0.330)
age -0.001 -0.013 -0.001 0.004(0.009) (0.009) (0.011) (0.011)
rally -0.269 -0.395(0.259) (0.320)
NDCmember 0.312 0.298 1.121∗∗∗ 0.895∗∗
(0.267) (0.266) (0.367) (0.360)living condition -0.217 -0.295∗ -0.023 -0.086
(0.137) (0.156) (0.180) (0.210)trust diffdialect -0.347∗∗ -0.060 -0.642∗∗∗ -0.451∗∗∗
(0.140) (0.150) (0.159) (0.161)econ current 0.427∗∗∗ 0.320
(0.129) (0.228)fante 0.104 0.290
(0.481) (0.318)vote stays thesame
-0.286 -0.396
(0.181) (0.286)MP born -0.015 -0.364∗∗∗
(0.108) (0.127)MP Election change 1.595∗∗∗ 1.308∗∗∗
(0.274) (0.351)Constant 7.558∗∗∗ 7.535∗∗∗ 7.345∗∗∗ 7.356∗∗∗
(0.446) (0.678) (0.570) (0.717)Observations 272 244 255 232R2 0.044 0.206 0.107 0.250Adjusted R2 0.022 0.172 0.085 0.216Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-6. Logistic regressions (odds ratios) predicting votes for the candidateq3
Bosome Freho Birim South(1) (2) (3) (4)
candidateoutsider 2.384∗(0.944, 6.514) 1.828 (0.462, 7.987) 0.812 (0.346, 1.871) 0.583 (0.212, 1.522)age 0.986 (0.959, 1.014) 1.007 (0.970, 1.049) 1.034∗(1.000, 1.072) 1.035∗(0.996, 1.080)female 1.478 (0.596, 3.783) 0.912 (0.244, 3.303) 0.679 (0.292, 1.555) 0.648 (0.241, 1.695)rally 1.490 (0.613, 3.736) 1.261 (0.368, 4.500) 0.623 (0.248, 1.515) 0.848 (0.292, 2.415)NPPmember 6.700∗∗∗(2.550, 21.029) 4.767∗∗(1.158, 22.406) 11.256∗∗∗(4.531, 32.585) 14.215∗∗∗(5.024, 47.065)living condition 0.420∗∗∗(0.247, 0.691) 0.376∗∗(0.168, 0.776) 0.619∗∗(0.393, 0.952) 0.543∗∗(0.310, 0.913)2012 NDC Dev. 0.377∗∗∗(0.176, 0.718)vote stays the same 0.813 (0.204, 2.598) 0.205∗∗(0.033, 0.674)MP born 0.421∗∗∗(0.251, 0.668)akyem 0.966 (0.357, 2.558)trust diffdialect 1.298 (0.611, 2.853) 0.795 (0.516, 1.222) 0.823 (0.492, 1.378)vote isn’t secret 0.914 (0.469, 1.755)MP Election change 0.845 (0.135, 6.017)Asante 3.620∗∗(1.105, 12.476)diff.ideo 0.457∗(0.182, 1.000)Constant 1.844 (0.441, 7.901) 2.348 (0.152, 42.323) 1.620 (0.246, 10.983) 38.110∗∗(2.700, 797.811)
Observations 273 196 275 253Log Likelihood -73.098 -45.222 -77.064 -60.338Akaike Inf. Crit. 160.195 116.445 170.127 144.676Note: ∗p < 0.1;∗∗ p < 0.05;∗∗∗ p < 0.01
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Table 8-7. Logistic regressions (odds ratios) predicting votes for the candidateq3
Adaklu Anyigbe Ketu South(1) (2) (3) (4)
candidateoutsider 0.818 (0.294, 2.241) 0.340∗(0.091, 1.166) 0.294∗∗∗(0.131, 0.639) 0.313∗∗(0.124, 0.749)age 0.986 (0.956, 1.017) 0.989 (0.955, 1.027) 1.007 (0.985, 1.032)female 1.807 (0.640, 5.613) 1.666 (0.527, 5.752) 1.490 (0.758, 2.986)rally 0.330 (0.072, 1.096) 0.251 (0.034, 1.092) 0.513 (0.215, 1.158) 0.367∗∗(0.142, 0.881)NDCmember 2.109 (0.693, 6.012) 1.898 (0.452, 7.403) 0.526 (0.162, 1.451) 0.757 (0.191, 2.466)living condition 2.141∗(1.027, 4.996) 2.236∗(0.981, 5.701) 1.013 (0.693, 1.480) 0.942 (0.587, 1.516)trust diffdialect 1.094 (0.511, 2.769) 1.380 (0.507, 4.905) 1.388 (0.890, 2.329) 1.237 (0.756, 2.154)diff.ideo 1.219 (0.420, 3.328) 0.404 (0.095, 1.202)vote stays the same 1.284 (0.419, 3.437) 0.743 (0.298, 1.558)MP born 1.482 (0.824, 2.929) 1.804∗∗∗(1.243, 2.663)ewe 15.216∗∗(1.591, 126.200) 0.729 (0.030, 7.652)econ current 1.087 (0.652, 1.820) 1.081 (0.752, 1.575)Constant 30.356∗∗∗(4.117, 288.502) 2.486 (0.142, 55.507) 10.813∗∗∗(2.496, 54.363) 22.632∗(1.327, 845.097)
Observations 213 192 236 203Log Likelihood -57.182 -47.762 -107.740 -89.935Akaike Inf. Crit. 130.365 121.524 231.481 201.870Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-8. Logistic regressions (odds ratios) predicting votes for the candidateq3
Mfantsiman AOB(1) (2) (3) (4)
candidate outsider 0.797 (0.390, 1.612) 1.011 (0.421, 2.433) 0.735 (0.336, 1.626) 1.013 (0.365, 2.910)age 0.992 (0.968, 1.018) 0.988 (0.954, 1.024) 0.973∗∗(0.946, 1.000) 0.974 (0.939, 1.008)female 0.695 (0.333, 1.415) 0.477 (0.189, 1.142) 0.671 (0.307, 1.443)rally 0.426∗∗(0.196, 0.884) 0.269∗∗∗(0.101, 0.658) 0.453∗∗(0.207, 0.963) 0.575 (0.197, 1.620)NDCmember 1.105 (0.535, 2.343) 1.472 (0.586, 3.883) 7.489∗∗∗(2.461, 29.624) 1.873 (0.509, 8.645)living condition 1.004 (0.677, 1.526) 1.039 (0.651, 1.704) 0.664∗∗(0.442, 1.000) 0.947 (0.513, 1.758)trust diffdialect 0.591∗∗∗(0.401, 0.862) 0.689 (0.412, 1.158) 0.572∗∗∗(0.380, 0.840) 0.649 (0.352, 1.154)diff.ideo 0.605 (0.101, 2.162) 1.530 (0.242, 6.603)vote stays the same 0.620 (0.244, 1.298) 0.284∗(0.045, 0.941)MP born 0.700∗(0.484, 1.000) 0.576∗∗(0.365, 0.881)fante 2.132 (0.407, 9.165) 2.6724∗(0.990, 7.911)econ current 1.506 (0.533, 5.927)vote isn’t secret 0.621∗∗(0.411, 0.917) 1.481∗(0.990, 2.286)MP Election change 3.177∗∗(1.146, 10.045) 5.259∗(1.182, 38.778)Constant 30.418∗∗∗(7.339, 142.037) 101.291∗∗∗(7.157, 2, 037.215) 34.337∗∗∗(7.066, 193.741) 96.651∗∗(3.074, 5, 918.055)
Observations 273 224 255 217Log Likelihood -105.606 -74.563 -91.313 -59.206Akaike Inf. Crit. 227.211 177.125 198.625 146.412Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
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Table 8-9. Q29: Muslim president list experiment
Obs Mean SD 95% CIQ29
4 items 888 1.771 0.753 (1.722, 1.821)5 items 951 1.777 0.785 (1.727, 1.827)
t = -0.1582, df = 1837, p-value = 0.8743
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Table 8-10. Q29: Muslim president list experiment- by district
Obs Mean SD 95% CIBosome Freho1
4 items 155 1.548 0.704 (1.437, 1.660)5 items 106 1.802 0.653 (1.676, 1.928)
Birim South2
4 items 158 1.835 0.647 (1.734, 1.937)5 items 154 1.708 0.840 (1.574, 1.841)
Adaklu Anyigbe3
4 items 163 1.926 0.920 (1.784, 2.069)5 items 164 2.079 0.726 (1.967, 2.191)
Ketu South4
4 items 155 2.116 0.756 (1.996, 2.236)5 items 149 2.121 0.744 (2.000, 2.241)
Mfantsiman5
4 items 165 1.885 0.768 (1.767, 2.003)5 items 155 1.432 0.603 (1.337, 1.528)
AOB6
4 items 155 1.335 0.617 (1.238, 1.433)5 items 160 1.5 0.624 (1.403, 1.598)
1t = 2.9399, df = 259, p-value = 0.00362t = -1.5065, df = 310, p-value = 0.13303t = 1.6685, df = 325, p-value = 0.09624t = 0.0544, df = 302, p-value = 0.95675t = -5.8360, df = 318, p-value = 0.00006t = 2.3521, df = 313, p-value = 0.0193
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Table 8-11. Clientelism list experiments
Obs Mean SD 95% CIQ31- President1
4 items 961 1.543 0.772 (1.494, 1.592)5 items 894 1.615 0.746 (1.566, 1.664)
Q32- MP2
4 items 961 1.507 0.720 (1.461, 1.552)5 items 892 1.570 0.705 (1.523, 1.616)
1t = 2.0398, df = 1853, p-value = 0.04152t = 1.8928, df = 1851, p-value = 0.0585
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Table 8-12. Clientelism list experiments- 2012 Presidential election by district
Obs Mean SD 95% CIBosome Freho1
4 items 105 1.790 0.631 (1.668, 1.913)5 items 157 1.089 0.414 (1.024, 1.154)
Birim South2
4 items 154 1.494 0.669 (1.387, 1.600)5 items 157 1.287 0.520 (1.205, 1.369)
Adaklu Anyigbe3
4 items 167 1.976 0.768 (1.859, 2.093)5 items 165 1.6 0.861 (1.468, 1.732)
Ketu South4
4 items 156 2.045 0.806 (1.917, 2.172)5 items 158 1.829 0.839 (1.697, 1.961)
Mfantsiman5
4 items 154 1.123 0.367 (1.065, 1.182)5 items 166 1.687 0.659 (1.586, 1.788)
AOB6
4 items 158 1.291 0.611 (1.195, 1.387)5 items 158 1.753 0.922 (1.608, 1.898)
1t = 10.8662, df = 260, p-value = 0.00002t = 3.0490, df = 309, p-value = 0.00253t = 4.2006, df = 330, p-value = 0.00004t = 2.3241, df = 312, p-value = 0.02085t = -9.3431, df = 318, p-value = 0.00006t = -5.2519, df = 314, p-value = 0.0000
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Table 8-13. Clientelism list experiments- 2012 Parliamentary elections by district
Obs Mean SD 95% CIBosome Freho1
4 items 104 1.75 0.570 (1.639, 1.861)5 items 157 1.089 0.398 (1.026, 1.152)
Birim South2
4 items 153 1.471 0.618 (1.372, 1.569)5 items 158 1.278 0.516 (1.197, 1.360)
Adaklu Anyigbe3
4 items 166 1.898 0.719 (1.787, 2.008)5 items 165 1.606 0.881 (1.471, 1.742)
Ketu South4
4 items 155 1.942 0.766 (1.820, 2.064)5 items 159 1.818 0.786 (1.694, 1.941)
Mfantsiman5
4 items 154 1.110 0.405 (1.046, 1.175)5 items 164 1.652 0.661 (1.551, 1.754)
AOB6
4 items 160 1.288 0.618 (1.191, 1.384)5 items 158 1.582 0.707 (1.471, 1.693)
1t = 11.0212, df = 259, p-value = 0.00002t = 2.9793, df = 309, p-value = 0.00313t = 3.2986, df = 329, p-value = 0.00114t = 1.4182, df = 312, p-value = 0.15715t = -8.7500, df = 316, p-value = 0.00006t = -3.9599, df = 316, p-value = 0.0001
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Table 8-14. Q34: Choose the Statement Which Is Closest To Your ViewResponse category Frequency Percent
Agree very strongly w/statement 1 153 8.54%Agree w/statement 1 189 10.55%Agree w/statement 2 576 32.16%Agree very strongly w/statement 2 873 48.74%Agree with neither 0 0.00%Total 1,791 100%Statement 1: when individuals take gifts from party officials and party ‘boys’, they vote for that political party during the election.Statement 2:when individuals take gifts from party officials and party ‘boys’, they still vote the way they want, and not necessarily withthe political party that gave the gift.
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CHAPTER 9CONCLUSION
This work has made the argument that Ghana’s national-level institutions have encouraged
competitive national elections while its centralized system of local government induces
real political competition at the grassroots level, and thus contributes to a lessening of
neopatrimonialism and ethnic voting. The first chapter introduced the overall argument,
and the second chapter traced the historical development of centralized institutions and
the ethnic reactions they provoked. The third chapter shows how the institutions of the
Fourth Republic continue the centralized reforms of past regimes, except now political
competition is institutionalized at the local level via the competitive relationship between
the centrally-appointed DCE and locally-elected MP(s).
Chapters 4 and 5 use Ecological Inference models and OLS regressions to analyze
vote volatility in the Fourth Republic. In particular, the EI models in Chapter 4 show that
ethno-linguistic groups, and particularly the Akans, are not unified in their voting patterns, and
that ethno-linguistic and tribal votes for opposition parties have been on the rise. Chapter 5
then showed statistically significant differences in voting patterns in districts with high levels of
local competition as compared to those with low levels of local competition. When the party
of the centrally-appointed District Chief Executive differed from the party of the locally-elected
Member of Parliament, votes for the DCE’s party increased in the next election as compared
to districts where the DCE and MP were of the same political party. This effect was significant
across presidential administrations.
Finally Chapters 6-8 presented the analysis of a survey conducted in 6 purposefully-selected
districts in Ghana. Three competing factors are thought to contribute to citizens’ votes: (1)
Identity-Based Voting; (2) Policy or Economic-Based Voting; and (3) Clientelistic-Based
Voting. These hypotheses are tested in the 3 district pairs (a NPP stronghold, a NDC
stronghold, and a competitive district pair), where evidence supporting each hypothesis is
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found via qualitative analysis of district-level politics and survey analysis of self-report vote data
and survey experiments across Chapters 6-8.
9.1 The Mixed-Methods Research Design
This dissertation utilized a number of analytic tools to understand political and vote
dynamics in Ghana’s Fourth Republic. The combination of these tools (historical analysis, over
140 interviews of formal and informal political elites, census and electoral data, qualitative
data, and survey data) has many benefits in terms of the type of analytic inferences it allows.
The data I use include historical data (including archival research), national-level data on
institutions and vote behavior, sub-national-level data on institutions and vote behavior, and
finally individual-level data on vote behavior.
By engaging in a mixed-methods research design, I intend to acknowledge that each
method offers different potential contributions to achieving causal inference. By using historical
data, I tease out the ways in which centralized institutions and ethnic politicization developed
in conjunction with one another throughout Ghana’s history. In the past, Ghana’s centralized
institutions both produced and responded to broad-based national-level ethno-linguistic
cleavages. Knowing this history then highlighted the notable ways in which the current system
of centralization in Ghana was instead producing divisions and complexities within national-level
ethno-linguistic groups. In Chapter 3 I detail the dynamics of the Fourth Republic institutions
and theorize how the centralized appointment of a DCE coupled with local-level elections of
MPs creates a competitive dynamic previously missing from the past centralized democratic
and authoritarian regimes in Ghana. Essentially, by granting districts local representation in
Parliament and well-funded district assemblies headed by Presidential appointees, local-level
politics is of greater importance and relevance in terms of tangible outcomes than it had been
in prior times.
In Chapter 4, I then test that theoretical framework using Ecological Inference models for
a national-level analysis of ethno-linguistic and tribal level voting patterns. That analysis shows
that core party supporters and particularly peripheral party supporters are increasingly willing to
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vote against their ethnic group voting tradition. In Chapter 5 I then tie that volatility in ethnic
votes to the institutional mechanism of Unfriendly DCE-MP pairs using constituency-level
voting data, essentially finding that vote volatility increases in the elections after the presence
of an Unfriendly DCE-MP pair as compared to Friendly Pairs.
The analysis through Chapter 5 has focused on historical, national, district, and
constituency-level trends of group behavior. If competitive subnational political environments
are lessening neopatrimonial and ethnic voting incentives then on-the-ground research should
bear some of this out. In Chapter 6 I present a qualitative analysis of district-level politics in 6
purposefully selected districts in southern Ghana. Districts were selected on the basis of similar
population, including ethnic, demographics and electoral voting patterns but with significant
differences in volatility in at least one election. The qualitative analysis, based on interviews
with district political elites at both the national and local level, as well as local-level traditional
elites and community leaders, demonstrated that explanations of Identity-Based factors,
Economic or Policy-Based factors, and Clientelistic-Based factors each had some traction at the
local level. Interestingly, however, the identity-based cleavages which were relevant were not
based on ethno-linguistic cleavages but rather existed on the basis of tribe, town, or traditional
area.
Finally, the survey analysis of individual-level vote incentives also provided varying degrees
of support for identity-based, economic or policy-based, and clientelistic-based voting. Different
survey questions provided evidence for different voting rationales. Economic or Policy-Based
Voting received the strongest support, particularly when individuals were actively describing
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their or their community-members’ reasons for voting. It was only within the less direct or
hidden questions that identity-based1 or clientelistic-based voting incentives were isolated.2
Overall, the mixed-methods research design was used to provide evidence of the underlying
causal mechanism that Ghana’s centralized system had increased political competition and
1 The tribal experiment which manipulated candidate names to represent different tribalidentities did not provide consistent results either for or against Hypothesis 2. However, whenasked if they would vote for the fictional candidate, respondents in the NDC strongholdsdid favor the insider candidate to a statistically significant degree more than the outsidercandidate. It is interesting that the only districts in which the insider candidate was favoredwere dominated by Ewes, whose tribal difference are not captured by the Ghanaian census.These experimental results go some way in suggesting that Ewe tribal identities are politicized.However, the overall lack of bias in favor of the insider candidate across the districts was
surprising. That the insider did not receive consistent partial treatment might be because thecandidate’s ties to the constituency were otherwise so strong that respondents considered hima ‘son of the soil’ regardless of his tribal background. While it is possible that respondentsare not biased of local candidates in terms of their ethnic backgrounds, it is also certainly thecase that local identities are very politicized within each district. Analysis of the open-endedresponses about why respondents would or would not vote for the candidate show thatrespondents do care a great deal about the candidate’s living in the area/being from thearea. But perhaps name indicators of tribal identity are not enough to capture the complexityof local politicized identities. More testing is required to rule out political bias againstcandidates from outsider tribes. Perhaps an alternative experiment in the future would testfor ethno-linguistic candidate differences against tribal differences.
2 Finally, the list experiments used to test for the effect of clientelistic inducements onrespondent vote decisions are the only questions which provide evidence for Hypothesis 3:Clientelism-Based Voting. That such evidence was produced only after hiding the clientelismquestion in a list experiment suggests the great extent to which Ghanaian voters either do notconsider clientelistic inducements as having a big impact on their vote decisions or that they donot want to admit it. Either way, hidden experimental question types were the only questionsproviding the most prominent evidence for this hypothesis. Of course, it is also extremelytelling that, once broken down to the district-level, evidence of clientelistic impacts on votingwere only found in the competitive districts (i.e. the districts which have voted in MPs of boththe NDC and NPP in the Fourth Republic), Mfantsiman and Asikuma Odoben Brakwa. Thisfinding suggests that close elections do fuel clientelistic payouts to individual voters. However,by extension, this suggests that the increased political competition between centrally-appointedDCEs and locally-elected MPs of different political parties is not fueling patronage battles. Thisinterpretation is backed by the research I have done which points to escalating developmentinitiatives as the avenue through which the DCE and MP increase their parties’ local levels ofsupport.
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contributed to a lessening of neopatrimonial and ethnic voting incentives. Different methods
provided critical insights into the validity of causal logic. While the historical and current
institutional data provided the framework for the causal argument, and the national-level and
constituency-level statistical analyses tied numerical trends to the proposed causal mechanism,
the qualitative analysis and survey data took the analysis to the individual level.
Overall the qualitative evidence suggests the decreasing relevance of national-level
ethno-linguistic identities is plausible while showing that now ethnic mobilization takes the
form of local-level identities (tribe, town, traditional area). The system of local government
both empowers local-level decision makers and makes local-level politics extremely relevant
for individual livelihoods. However, though the survey evidence does overwhelmingly support
voters’ consideration of economic or policy-related issues, it provides mixed-evidence of the
relevance of local-level identities.3 That this evidence does not perfectly align with the
qualitative evidence requires a reconsideration of the survey tools used, particularly since the
tests for the politicization of local-level identities were non-exhaustive. Simply put, there is a
great deal of room for more research on identity politicization at the individual level.
9.2 Contributions to the Literature
Outside of Research Methods, this dissertation also makes several contributions to the
broad literatures on (1) Democratic Theory and (2) Ethnic Politics.
3 In the candidate experiment in Chapter 8, the overall lack of bias in favor of the insidercandidate across the districts was surprising. That the insider did not receive consistent partialtreatment might be because the candidate’s ties to the constituency were otherwise so strongthat respondents considered him a ‘son of the soil’ regardless of his tribal background. Whileit is possible that respondents are not biased of local candidates in terms of their ethnicbackgrounds, it is also certainly the case that local identities are very politicized within eachdistrict. Analysis of the open-ended responses about why respondents would or would not votefor the candidate show that respondents do care a great deal about the candidate’s living inthe area/being from the area. But perhaps name indicators of tribal identity are not enoughto capture the complexity of local politicized identities. More testing is required to rule outpolitical bias against candidates from outsider tribes. Perhaps an alternative experiment in thefuture would test for ethno-linguistic candidate differences against tribal differences.
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9.2.1 Contributions to Democratization Theory
First, this research makes a contribution to Democratization Theory in arguing that both
sub-national institutional design and the regulation of mobilizable politicized cleavages are
important considerations when setting up institutions in new democracies. I have made the
argument that sub-national institutional design is as important, if not more important, for
ensuring the overall quality of a democracy, particularly at the sub-national level. This work
looks at the important effects of local political competition, pointing out that national-level
democratic transitions, even in the context of stable political competition, does not mean that
citizens are also getting the opportunity to make retrospective and prospective vote choices in
local elections.
By far the largest contingent of scholars studying local government institutions tout the
democratic benefits of decentralized institutions for local communities. Assuming power is
politically, administratively and economically devolved (e.g., Burki et al 1997; Falleti 2005;
Willis, Garman, and Haggard 1999; Filippetti and Sacchi 2013), decentralization is assumed
to offer a wide range of democratic benefits. Yet many scholars are less specific about
these benefits as compared to their attention to the problems associated with incomplete
decentralization. It can generally be discerned that decentralization is supposed to increase
local autonomy, which can act as a buffer against the state. Similarly, decentralization is
supposed to provide a system of democratic governance at the local level which comes with
the presumed benefits of increased community involvement and voter turnout (never mind that
American voters need to be continuously reminded that local elections have a greater impact
on their lives than do national elections).
The local government reform that was instead implemented in Ghana, as Rondinelli (1990)
warns against, is that the central government deconcentrated its bureaucracies, installing
local-level versions of national-level departments in the districts without also promoting
political or economic decentralization. This system thereby allows deeper penetration of power
and control by the central state in localities. Yet, what my argument also emphasizes, and
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which is of particular concern within developing nations, is that the generalized public may
not feel the effects of decentralized institutions in new democracies, particularly in terms
of local development within their communities. In low development contexts, local revenue
cannot solely be raised from local tax bases and instead have to rely on transfers from the
central government which, particularly in sub-Saharan Africa, is itself monetarily constrained.
Further, when political competition does not extend down to the sub-national level, as is
common in SSA countries where historical legacies, political traditions, and ethnic politics
create binding political strongholds, citizens do not hold their politicians or political parties
accountable, opposition parties do not compete where a loss is guaranteed, political parties do
not develop strong party platforms, and politicians are not incentivized to be responsive to their
constituents.
Even where citizens want to punish their politicians for poor behavior, in the context of
the ethnically-politicized landscapes of African countries, members of the voting public are
dis-incentivized to vote against the dominant political tradition and/or their co-ethnic politician
because of the assumption that an oppositional or non-co-ethnic politician will exclusively
distribute resources to their own co-ethnic constituents. The devil you know is better than the
angel you don’t know.
In this on-going cycle, local politicians are not held accountable and citizens lose out on
the benefits real local competition brings. If, as Ghana has, a system can be institutionalized
where opposition leaders are positioned in dominant party strongholds to compete against
locally-elected politicians for party support, then voters have the opportunity to see both
parties in action in their localities. Voters can compare the quality and effectiveness of the two
political parties and make informed decisions in the next election. If local political competition
is not institutionalized, then voters in party strongholds become stuck in the political tradition,
not having a reason to vote for an opposition party which has never won a local election and
which probably does not even bother to campaign in the area. The institutionalization of
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real local competition generates greater democratic opportunities at the local level at a much
quicker rate than would have otherwise naturally progressed.
Second the argument presented in this work also emphasizes that the incorporation of
politicized cleavages does not go far enough to ensure democratic stability. The democratization
community needs to be additionally concerned about the regulation or de-politicization of
national-level ethnic cleavages. The origins of the cleavage incorporation argument have deep
roots from democratization scholars working in much older democracies (Lipset and Rokkan
1967; Luebbert 1991; Collier and Collier 2002). Yet the cleavage incorporation theory is still
a prominent feature of today’s democratization theories, including its permeation into recent
arguments about the development of strong opposition parties and democratic transitions in
sub-Saharan Africa.
For instance, a recent African Politics scholarship emphasizes the importance of the
development of a credible opposition for the prospects of a stable democratic transition (LeBas
2011; Arriola 2012; Elischer 2013; Riedl 2014). This literature presumes that the development
of an opposition strong enough to challenge authoritarian rule and force a democratic regime
change will need to be composed of ethnic-alliances. Their major question investigates
under what conditions strong ethnic opposition movements develop. Yet, by incorporating
ethnic cleavages into a new democracy’s institutions, the danger is that these divides will be
frozen into the political landscape for a significant time, and thus increase the possibility that
politicized ethnic divides stabilize and can be mobilized for violent or non-violent political
means.
My argument challenges this narrow focus on ethnic incorporation in further asking,
given a democratic transition, which political institutions contribute to the de-escalation and
de-politicization of national-level ethnic divides. Unfortunately, nation-building is an exhaustive
process and African nations face several structural impediments (i.e. insecure borders, weak
budgets, particularistic political traditions, and pre-bureaucratic moral economies) which
diminishes the likelihood of a national identity overcoming communal ethnic identities (e.g.,
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Ekeh 1975; Weber 1978; Herbst 2000, etc). By implementing centralized control over localities,
combined with national-level alternations in power, Ghana’s political parties have each been
able to infiltrate opposition strongholds, creating meaningful political competition at the local
levels which also combats national-level ethnic divides.
9.2.2 Contributions to Ethnic Politics
As a scholar whose first love was the study of race, ethnicity, and identity politics, an
important focus of this work is an informed and sophisticated treatment of ethnicity. As
statistical procedures increasingly dominate the research methods used by political scientists,
ethno-linguistic categories have become the staple level at which ethnicity is captured as a
variable and tested in statistical models. This is justified because linguistic differences, it is
argued, are representative of cultural differences and it is these cultural differences which are
used to mobilize communal groups for political action. But how can we be sure that linguistic
differences automatically proxy the politically relevant cultural differences for any given society?
Sometimes, for instance, institutional or social structures foment politically salient divisions
within language groups (Fearon 1999, 5). Well known and tragic examples of conflicts between
members of the same ethno-linguistic group include violence between the Hutus and Tutsi
in Rwanda and Burundi as well as the deadly intra-Dagbon chieftaincy conflicts in Northern
Ghana (Weiss 2005).
A growing literature attempts to test for politically relevant identity group boundaries or
configurations (Laitin and Posner 2001; Fearon 2003; Posner 2004; Desmet, Ortuno-Ortin and
Weber 2009; Wimmer, Cederman, and Min 2009; Baldwin and Huber 2010). But these studies
pair linguistic data with new information, as opposed to a reconsideration of the relevance of
ethno-linguistic boundaries for social conflict within their cases. That the political relevance of
other ethnic boundaries, such as cultural or religious differences, is not explored underutilizes
valuable contextual information.
Rather than assume that linguistic differences are the causal mechanism behind politicized
ethnic behavior, it might be that linguistic group boundaries do not define the set of politically
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relevant groups in a given area. Politically relevant identities refer to those identities which
are made salient at the group level and can be mobilized to achieve some political aim.
Different identities can be made salient within the same communities at different times, and for
different issues. In some cases, ethno-linguistic groups are the most politically relevant identity
groups. In other cases, however, other identity categories, such as caste in India, are the most
politically relevant groups (Banerjee, Iyer and Somanathan 2005). Political institutions can
greatly impact the politicization of different groups, particularly when political goods are at
stake during elections (Posner 2005).
Because of these epistemological concerns, this work takes substantial strides to treat
ethnicity in a sophisticated way. But I also address the shortcomings of my methods, which
naturally accompany any social science research on identity politics and which particularly need
to be acknowledged when the capture of identity for statistical procedures is used.
The research methods used in this work included Ecological Inference models to estimate
the relationships between citizens’ identities and vote outcomes, an experimental survey
question which primes respondents to test for biases in perceptions about political candidates,
and captures survey respondents’ own ethnic identities by asking for their tribe, the first
language they learned as a child, and their mother’s and father’s tribes.
First, Chapter 4 presents Ecological Inference models which utilize ethno-linguistic and
tribal group categories to test for the politicized cleavage groups as well as to analyze the
vote behaviors of these groups across Fourth Republic elections. As such, this work assesses
the often untested assumption that ethno-linguistic group differences are an African nation’s
politicized groups. While some ethno-linguistic group estimates show strong associations with
vote outcomes, the tribal analysis shows that not all of an ethno-linguistic groups’ tribes vote
according to the ethno-linguistic group’s political tradition. To my knowledge, this is the first
statistical analysis of Ghana’s tribal groups, and the results show that the political behavior
of tribal group members is more dynamic than an analysis of ethno-linguistic groups would
demonstrate.
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Two methodological concerns arise out of Chapter 4. First, an obvious concern is that my
analysis relies on the census capture of identity information. Many facets of identity cannot be
captured by censuses and surveys. The ethno-linguistic and tribal group information captured
by the Ghanaian census serve as proxies for concepts of much greater complexity, and thus the
statistical analysis of these variables is prone to conceptual shortcomings. Still, I argue that
the analysis of tribal captures of ethnicity alongside ethno-linguistic variables is an important
improvement from past work.
Relatedly, there is also the concern that the differences between tribes are not significant
or are not politically relevant and that an analysis based on tribes thus creates higher degrees
of fractionalization than otherwise exists (Fearon 2003). I defend my use of tribe on two
accounts. First, unlike works which use fractionalization measures to predict political outcomes,
such as conflict, and thus have an incentive to increase or decrease a nation’s fractionalization
measure to suit the theory, my research tests for the political relevance of tribal categories in
terms of political party vote estimates. In my case, proving that Ghanaian tribes perfectly align
with the political traditions of their encompassing ethno-linguistic group would also have been
an interesting finding. This, however, was not what the analysis showed. Second, this work
argues that tribal differences have been historically important in Ghana, but that both colonial
and past regimes’ centralized institutions provoked unified ethno-linguistic responses. Though
there was a breakdown of ethno-linguistic voting in the 1979 elections, which were supervised
by a military junta which specifically attacked the political elite and opened up space for
tribal political contention, the centralized institutions of the Fourth Republic de-escalate
national-level ethnic mobilization by introducing political competition at the local levels.
Beyond the Ecological Inference chapter, I also employ an experimental question which
tests for tribal bias in political perceptions and vote decisions. When testing for ethnic voting’
in Africa, researchers tend to either ask respondents what factors influenced their votes,
if ethnicity influenced their votes, or researchers infer ethnic voting took place if a voter’s
ethnicity matches the ethnicity known for supporting the politician or political party. In
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Western democracies, we accept that voters’ identities will impact their vote decisions as a
rational behavior while acknowledging that voters are also simultaneously capable of making
calculated and informed decisions when voting (Abrajano, Nagler, and Alvarez 2005). Further,
researchers in Western democracies also realize that it is socially unacceptable to admit that
you are voting for or against a candidate because of their race/gender or that many voters
may be unaware of the extent to which racial or gender biases impact their vote decisions.
In response, researchers instead hide’ the race/gender information in a question, in order to
subconsciously prime respondents to think about race or gender and then asking questions of
a political nature (e.g. rate the electability of this political candidate or the popularity of this
public policy) (Terkildsen 1993; Matland 1994; Sanbonmatsu 2002).
Research of this nature is seldom conducted in sub-Saharan Africa. Political research
experiments have only come into popularity for research in SSA in the last 15 years and
very few studies test for subconscious or hidden ethnic or gender biases. The analysis of the
experimental survey question within this work offers an innovative contribution to the field of
African Politics.
9.3 Moving Forward
While this dissertation has made use of innovative tools to analyze new ethnic data in
Ghana, there are some areas where further tests and more data would solidify some of the
arguments made in this work. First, the models presented in Chapter 5 provide evidence that
there is greater vote volatility in constituency elections with an Unfriendly DCE-MP pairing
in the prior term, as compared to constituencies with Friendly Pairs. This data is used to
argue that Unfriendly DCE-MP pairs generate particularly competitive political environments
as these officials compete to increase their party’s share of the votes in the next election.
However, as is the case in many African democracies, the way in which Ghanaian voters judge
the performance of their public officials is the extent to which they successfully implement
development projects. I argue the presence of an Unfriendly Pair in a constituency generates
a development race between the DCE and MP, as compared to Friendly Pairs where the DCE
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and MP work together to implement development projects which happen at a slower rate in the
absence of a heightened competitive environment.
In order to shore up the claims made in Chapter 5, I require data on constituency-level
development projects in order to show that development increased in constituencies with
Unfriendly Pairs as opposed to Friendly Pairs. Development project data is difficult to come by
in sub-Saharan Africa. Even if one gains access to a comprehensive project dataset, such as the
years and location of school projects, an analysis based on this data would probably fall short
because not every Unfriendly Pair competes on school projects. Perhaps some Unfriendly Pairs,
for instance, compete in the construction of water boreholes and markets rather than schools.
The analysis would fall short in this area. Still, I have a couple of leads on some development
datasets and I hope to incorporate them as an extension of this work in the future.
Second, this work applies a number of innovative methods to Ghana which would be
useful in studies of other sub-Saharan African nations. For one, I use Ecological Inference
models to analyze ethno-linguistic and tribal voting behavior in Ghana. While this is not the
first time EI models have been used to analyze elections in African nations, this is the first use
(to my knowledge) of the Multinomial-Dirichlet EI model using a hierarchical Bayesian model
fit to an election in an African nation. As EI models become more advanced, and as ethnic and
election data becomes more readily available in African nations, we will increasingly know more
about ethnic voting habits in sub-Saharan African nations.
Similarly, I also use two types of experiments in my survey. List experiments were used
to test for religious discriminatory beliefs and for the effect of clientelistic gifts on voting.
List experiments are increasingly being used to test for embarrassing or sensitive behavior in
African nations. I expect this trend will continue. The experiment I used to test for tribal
discriminatory beliefs, however, is not often applied in African nations. First, reading the
description of a fictional candidate and manipulating the candidate’s gender or race is a
common tool used to identify gender or racial discriminatory beliefs in the US. However,
other than this dissertation, I am unaware of any similar experiments tested in an African
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country. Relatedly, I also used tribal instead of ethno-linguistic identity as the manipulated
information in the experiment. Rather than assume that ethno-linguistic group differences
are the politically salient differences in a society, more experimental testing needs to be
done to measure the extent of politicized identity bias in African states. My own test found
contradictory information in that one district’s respondents gave higher candidate ratings to
the outsider candidate while two other districts’ respondents preferred voting for the insider
candidate. More testing needs to be done to determine if politicians’ tribal identities do have
an impact on voter perceptions, with the very distinct possibility that tribal identities matter in
some districts more than others.
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Table A-1. Presidential Vote Margins by Tribe (1996-2012)NDC NPP
Election >10% <10% >10% <10%
2012 Pres sefwi(53.4%), dan-gme(52.3%), ewe(58.4%)
fante(40.7%) ahanta(63.4%),akuapem(71.6%)
boron(44.8%)
bimoba(74.9%),builsa(67.1%), da-garte(50.4%)
akyem (72.9%), as-ante(76.2%)
denkyira(54.8%)
dagomba(53.3%),kusasi(66.3%),nankansi(53.5%)
kwahu(66.6%)
2008 Runoff sefwi(47.3%), ewe(58.4%) dangme(46.5%) ahanta(70.5%),akuapem(61.9%)
boron(34.5%)
bimoba(67.4%),builsa(72.0%)
akyem(67.5%, as-ante(79.3%)
chokosi(55.7%)
dagarte(45.6%),dagomba(56.6%)
asen(68.4%),denkyira(58.3%)
kwahu(53.1%)
kusasi(49.6%), mam-prusi(51.8%)
2008 Pres dangme(47.3%),ewe(44.5%)
sefwi(44.2%) ahanta(59.3%),akuapem(67.3%)
wasa(41.6%)
bimoba(58.6%),builsa(47.7%)
nankansi(40.2%) akyem(58.2%), as-ante(66.4%)
dagomba(48.9%),kusasi(60.1%)
denkyira(62.0%),sisala(55.6%)
kasena(57.0%)2004 Pres sefwi(59.5%), ga(64.0%) dangme(49.8%) ahanta(71.4%),
akuapem(90.3%)boron(47.7%)
ewe(63.5%), bi-moba(56.8%)
akyem(70.3%), as-ante(83.7%)
dagarte(42.3%),dagomba(62.0%)
asen(73.8%),denkyira(79.3%)
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Table A-1. ContinuedNDC NPP
Election >10% <10% >10% <10%
2004 Pres cont’d kusasi(64.7%),kasena(68.1%)
fante(51.4%),kwahu(43.7%)
sisala(52.1%) wasa(66.5%)2000 Runoff sefwi(41.4%), ewe(44.0%) kokomba(29.2%) agona(83.2%),
akyem(59.0%)ahanta(43.0%)
bimoba(53.5%),sisala(57.1%)
dagarte(26.5%) asante(61.3%),boron(34.0%)
asen(71.9%)
denkyira(70.3%),wasa(53.3%)
kwahu(51.3%)
kasena(54.9%) nankansi(34.9%)2000 Pres sefwi(47.0%), ewe(36.9%),
bimoba(57.1%)kokomba(26.2%) agona(81.4%),
ahanta(66.2%)boron(31.9%)
builsa(33.7%) akuapem(61.5%),akyem(52.3%)
wasa(55.4%)
dagarte(21.6%) asante(59.0%),asen(53.5%)
sisala(37.1%) denkyira(67.3%)1996 Pres aowin(49.2%), asen(59.1%) agona(58.2%) ahanta(59.6%),
akyem(64.2%)nzema(33.8%)
chokosi(70.6%), se-fwi(70.9%), dan-gme(49.9%)
boron(36.7%) asante(63.8%),kwahu(61.0%)
wasa(49.4%)
ewe(73.1%), bi-moba(96.8%),kokomba(38.2%)
denkyira(55.5%)
builsa(67.9%),dagarte(51.1%),kusasi(63.8%)
ga(51.7%)
, mamprusi(48.6%),nankansi(52.2%),sisala(47.0%)
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Table A-2. Parliamentary Voting Margins by Tribe (1996-2012)
NDC NPP Third PartyElection >10% <10% >10% <10% <10%
2012 Parl chokosi(59.4%),ewe(40.1%)
nzema(36.8%),sefwi(46.8%)
akyem(72.3%),asante(71.3%)
ahanta(55.7%)
bimoba(63.4%),kusasi(55.3%)
dangme(49.5%),dagarte(40.7%)
builsa(51.2%) akuapem(51.1%)
dagomba(47.4%),nankansi(45.0%)
boron(44.1%)
kasena(50.7%) denkyira(49.0%)kokomba(34.9%)
2008 Parl ga(68.5%),ewe(42.1%)
chokosi(53.2%),sefwi(46.4%)
akuapem(71.3%),akyem(63.4%)
ahanta(55.4%)
bimoba(47.8%) guan3(48.3%),dagomba(47.2%)
asante(55.6%),asen(63.1%)
kokomba(37.7%)
builsa(49.5%)2004 Parl sefwi(59.7%),
ga(64.6%)dangme(47.6%),nankansi(39.5%)
ahanta(83.1%),akuapem(81.9%)
fante(46.1%)
ewe(65.5%),bimoba(62.4%)
kasena(59.0%) akyem(73.4%),asante(84.5%)
kwahu(36.3%)
dagarte(48.6%),dagomba(62.3%)
asen(87.8%),boron(48.2%)
nzema(43.6%)
kusasi(67.5%) chokosi(54.5%),denkyira(83.4%)
builsa(40.6%)
wasa(70.3%),guan3(62.0%)sisala(60.3%)
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Table A-2. Continued
NDC NPP Third PartyElection >10% <10% >10% <10% <10%
2000 Parl sefwi(46.0%),ga(47.5%)
dagarte(26.2%),nankansi(24.5%)
ahanta(64.4%),akuapem(58.5%)
boron(31.7%) nzema
ewe(32.0%),builsa(50.2%)
sisala(51.3%) akyem(56.9%),asante(57.7%)
kasena(48.9%) (39.7%)
asen(63.2),kwahu(61.0%)wasa(45.4%),guan5(52.8%)
1996 Parl agona(63.5%),ahafo(98.0%)
dangme(34.5%),dagarte(33.4%)
asante(67.2%) akuapem(51.9%) kokomba
aowin(69.5%),asen(88.1%)
dagomba(31.9%),mamprusi(40.5%)
akyem(54.6%) (35.0%)
chokosi(70.9%),denkyira(71.6%)
fante(38.1%)
nzema(44.0%),sefwi(71.0%)wasa(48.4%),ga(80.8%)ewe(47.9%),guan5(60.8%)bimoba(99.8%),builsa(76.3%)kasena(81.4%),sisala(73.9%)
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Table A-3. Presidential Vote Margins by Ethnic Group (1996-2012)
NDC Vote Margin NPP Vote MarginElection >10% <10% >10% <10%
2012 Pres ewe(65.2%) gadangme(45.9%) akan(55.4%)mole dagbani(49.3%)grusi(59.8%)
2008 Runoff ewe(63.9%) gadangme(41.9%) akan(51.7%)mole dagbani(50.2%)
2008 Pres ewe(55.6%) gadangme(42.0%) akan(46.7%)mole dagbani(45.7%) mande(83.3%)
2004 Pres ewe(69.6%) gadangme(53.9%) akan(65.3%)mole dagbani(49.8%)others(49.3%)
2000 Runoff ewe(59.8%) akan(48.1%)gruma(39.0%)mande(61.5%)
2000 Pres ewe(48.4%) mole dagbani(26.5%) akan(45.7%)gruma(42.7%)mande(70.3%)others(57.1%)
1996 Pres ewe(74.2%) guan(47.3%) akan(48.0%)gadangme(57.5%) others(47.5%)gruma(64.2%)mole dagbani(42.2%)grusi(48.0%)mande(80.1%)
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Table A-4. Parliamentary Vote Margins by Ethnic Group (1996-2012)
NDC Vote Margin NPP Vote MarginElection >10% <10% >10% <10%
2012 Parl ewe(51.7%) akan(49.9%)mole dagbani(44.5%) others(74.2%)
2008 Parl ewe(45.4%) mole dagbani(39.1%) akan(42.9%)gadangme(48.9%)mande(61.3%)
2004 Parl ewe(53.1%) akan(61.2%)gadangme(53.2%)mole dagbani(45.3%)
2000 Parl ewe(38.3%) gadangme(29.8%) akan(43.5%)mande(82.7%) gruma(27.6%)
mole dagbani(28.1%)
1996 Parl ewe(59.9%) akan(45.8%)gadangme(57.8%)gruma(53.1%)mole dagbani(33.3%)grusi(83.0%)mande(99.9%)others(81.1%)
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APPENDIX BMETHODS OF BOUNDS
Table B-1. District-Level Bounds of Votes by Tribe - 1996 Presidential
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .536)Ellembelle nzema, ndc (.187, .360) nzema, npp (.327, .650)Ahanta West ahanta, ndc (0, .538) ahanta, npp (.102, 1)Sekondi Takoradi Metro. fante, ndc (0, .568) fante, npp (.064, 1)Shama fante, ndc (.300, .524) fante, npp (.286, .592)Tarkwa Nsuaem Mun. wasa, ndc (0, .782)Wassa Amenfi East wasa, ndc (0, .908)Sefwi Wiawso sefwi, ndc (.275, 1) sefwi, npp (0, .484)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.354, .765) sefwi, npp (0, .480)Juabeso sefwi, ndc (.202, 1) sefwi, npp (0, .483)KEEA fante, ndc (.424, .534) fante, npp (.283, .431)Cape Coast Metro. fante, ndc (.107, .569) fante, npp (.262, .860)Abura-Asebu-Kwamankese fante, ndc (.420, .498) fante, npp (.329, .433)Mfantsiman Mun. fante, ndc (.357, .458) fante, npp (.332, .471)Ajumako-Enyan-Essiam fante, ndc (.334, .371) fante, npp (.470, .519)Gomoa West fante, ndc (.352, .397) fante, npp (.378, .444)Gomoa East guan3, ndc (0, .741) guan3, npp (0, .955)Effutu Mun. fante, ndc (.122, .628) fante, npp (0, .804)Agona East fante, ndc (0, .957)Agona West Mun. fante, ndc (0, .901)Asikuma-Odoben-Brakwa fante, ndc (.387, .550) fante, npp (.276, .477)Assin South asen, ndc (0, .905)Upper Denkyira East Mun. denkyira, ndc (0, .966)Dangbe West dangme, ndc (.485, .959) dangme, npp (0, .181)Dangbe East dangme, ndc (.665, .880) dangme, npp (0, .053)South Tongu ewe, ndc (.844, .884) ewe, npp (0, .023)Keta Mun. ewe, ndc (.876, .889) ewe, npp (0, .008)Ketu South ewe, ndc (.735, .767) ewe, npp (0, .027)Ketu North ewe, ndc (.766, .784) ewe, npp (.012, .035)Akatsi ewe, ndc (.817, .831) ewe, npp (0, .012)North Tongu ewe, ndc (.766, .807) ewe, npp (0, .031)Adaklu Anyigbe ewe, ndc (.836, .965) ewe, npp (0, .035)Ho Mun. ewe, ndc (.795, .893) ewe, npp (0, .053)South Dayi ewe, ndc (.564, .628) ewe, npp (0, .058)North Dayi ewe, ndc (.776, .850) ewe, npp (0, .032)Hohoe Mun. ewe, ndc (.707, 1) ewe, npp (0, .061)Biakoye ewe, ndc (.363, 1) ewe, npp (0, .308)Jasikan ewe, ndc (.448, 1) ewe, npp (0, .128)
guan1, ndc (.274, 1)guan1, npp (0, .270)Kadjebi ewe, ndc (.284, 1) ewe, npp (0, .279)Nkwanta South kokomba, ndc (.445, 1) kokomba, npp (0, .307)
375
Table B-1. Continuedtribe (lower bound, upper bound)
District NDC NPPBirim South akyem, ndc (0, .563) akyem, npp (.219, 1)Birim Mun. akyem, ndc (0, .695)Yilo Krobo dangme, ndc (.539, .762) dangme, npp (0, .244)Asuogyaman dangme, ndc (.376, .746) dangme, npp (0, .485)Lower Manya ewe, ndc (.169, 1) ewe, npp (0, .608)Upper Manya dangme, ndc (.585, .760) dangme, npp (0, .140)East Akim Mun. akyem, ndc (0, .775)Atiwa akyem, ndc (0, .622)Kwaebibirem akyem, ndc (0, .860)Birim North akyem, ndc (0, .875)Kwahu West Mun. kwahu, ndc (0, .442) kwahu, npp (.320, 1)Kwahu South kwahu, ndc (0, .482) kwahu, npp (.257, 1)Kwahu East kwahu, ndc (0, .437) kwahu, npp (.285, 1)Kwahu North ewe, ndc (.492, 1)Atwima Mponua asante, ndc (0, .689)Amansie West asante, ndc (.083, .283) asante, npp (.610, .885)Amansie Central asante, ndc (.126, .268) asante, npp (.660, .840)Obuasi Mun. asante, ndc (0, .576) asante, npp (.094, 1)Adansi North asante, ndc (0, .515) asante, npp (.215, 1)Bekwai Mun. asante, ndc (0, .182) asante, npp (.751, 1)Bosome Freho asante, ndc (.043, .422) asante, npp (.329, .932)Asante Akim South asante, ndc (0, .808)Asante Akim North Mun. asante, ndc (0, .398) asante, npp (.437, .981)Ejisu Juaben Mun. asante, ndc (0, .259) asante, npp (.643, 1)Bosumtwi asante, ndc (0, .268) asante, npp (.566, .992)Atwima Kwanwoma asante, ndc (0, .192) asante, npp (.718, 1)Kumasi Metro. asante, ndc (0, .327) asante, npp (.447, 1)Atwima Nwabiagya asante, ndc (0, .299) asante, npp (.607, 1)Ahafo Ano South asante, ndc (0, .821)Offinso Mun. asante, ndc (0, .502) asante, npp (.250, 1)Afigya Kwabre asante, ndc (0, .353) asante, npp (.505, 1)Afigya Sekyere asante, ndc (.005, .396) asante, npp (.447, .976)Kwabre East asante, ndc (0, .249) asante, npp (.644, 1)Mampong Mun. asante, ndc (0, .323) asante, npp (.549, 1)Sekyere East asante, ndc (.052, .291) asante, npp (.603, .929)Sekyere Afram Plains asante, ndc (0, .473) asante, npp (.331, 1)Sekyere Central asante, ndc (0, .527) asante, npp (.046, 1)Offinso North asante, ndc (0, .950)Dormaa Mun. boron, ndc (.294, .607) boron, npp (.087, .558)Dormaa East boron, ndc (.236, .418) boron, npp (.302, .607)Sunyani Mun. boron, ndc (0, .695)Sunyani West boron, ndc (.031, .589) boron, npp (.119, .952)
376
Table B-1. Continuedtribe (lower bound, upper bound)
District NDC NPPBerekum Mun. boron, ndc (.275, .487) boron, npp (.200, .537)Jaman South boron, ndc (.241, .387) boron, npp (.119, .452)Tain boron, ndc (.227, .540) boron, npp (0, .480)Wenchi Mun. boron, ndc (0, .786)Techiman Mun. boron, ndc (0, .900)Nkoranza South boron, ndc (.149, .897) boron, npp (0, .646)Sawla-Tuna-Kalba dagarte, ndc (.265, 1) dagarte, npp (0, .245)West Gonja guan5, ndc (0, .777)Gonja Central guan5, ndc (.184, .780) guan5, npp (0, .663)East Gonja guan5, ndc (0, .814)Kpandai kokomba, ndc (.449, 1) kokomba, npp (0, .287)Nanumba South kokomba, ndc (.048, .629) kokomba, npp (0, .902)Nanumba North kokomba, ndc (0, .530)Zabzugu Tatali kokomba, ndc (.061, 1) kokomba, npp (0, .585)Yendi Mun. kokomba, ndc (0, .831) dagomba, npp (.104, 1)
dagomba, ndc (0, .481)Tamale Metro. dagomba, ndc (.199, .454) dagomba, npp (.339, .710)Tolon Kumbugu dagomba, ndc (.452, .490) dagomba, npp (.353, .404)Savelugu Nanton dagomba, ndc (.469, .562) dagomba, npp (.215, .334)Karaga dagomba, ndc (.076, .564) dagomba, npp (.049, .805)Saboba kokomba, ndc (.619, .722) kokomba, npp (.062, .195)Chereponi chokosi, ndc (.225, .715) chokosi, npp (0, .482)Bunkpurugu Yonyo bimoba, ndc (.408, 1) bimoba, npp (0, .216)
kokomba, npp (0, .862)Mamprusi East mamprusi, ndc (.107, 1) mamprusi, npp (0, .324)Mamprusi West mamprusi, ndc (.391, .669) mamprusi, npp (0, .259)Builsa builsa, ndc (.508, .635) builsa, npp (0, .071)Kasena Nankana West kasena, ndc (.200, .808) kasena, npp (0, .480)Kasena Nankana East nankansi, ndc (0, .986)Bolgatanga Mun. nankansi, ndc (.287, .596) nankansi, npp (0, .266)Talensi Nabdam nankansi, ndc (.326, .872) nankansi, npp (0, .270)
namnam, npp (0, .871)Bongo nankansi, ndc (.609, .636) nankansi, npp (.064, .101)Bawku West kusasi, ndc (.355, .655) kusasi, npp (0, .155)Garu Tempane kusasi, ndc (.224, 1) kusasi, npp (0, .350)Bawku Mun. kusasi, ndc (.062, .963) kusasi, npp (0, .771)Wa East dagarte, npp (0, .864)Sissala East sisala, ndc (.311, .564) sisala, npp (0, .130)Nadowli dagarte, ndc (.450, .735) dagarte, npp (0, .167)Jirapa dagarte, ndc (.581, .632) dagarte, npp (0, .075)Lambussie Karni dagarte, ndc (.267, 1) dagarte, npp (0, .278)Lawra dagarte, ndc (.480, .545) dagarte, npp (0, .080)
377
Table B-2. District-Level Bounds of Votes by Tribe - 1996 Parliamentary
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .527)Ellembelle nzema, ndc (.181, .354)Nzema East evalue, ndc (0, .987)Ahanta West ahanta, ndc (0, .457)Sekondi Takoradi Metro. fante, ndc (0, .532)Shama fante, ndc (.263, .487) fante, npp (.005, .463)Tarkwa Nsuaem Mun. wasa, ndc (0, .799)Wassa Amenfi East wasa, ndc (0, .810)Sefwi Wiawso sefwi, ndc (.241, 1) sefwi, npp (0, .596)Sefwi-Bibiani-Ahwiaso sefwi, ndc (.328, .738) sefwi, npp (0, .539)Juabeso sefwi, ndc (.178, 1) sefwi, npp (0, .558)KEEA fante, ndc (.443, .553)Cape Coast Metro. fante, ndc (.112, .574) fante, npp (.271, .857)Abura-Asebu-Kwamankese fante, ndc (.398, .476) fante, npp (.325, .436)Mfantsiman Mun. fante, ndc (.305, .406) fante, npp (0, .080)Ajumako-Enyan-Essiam fante, ndc (.279, .315) fante, npp (.471, .528)Gomoa West fante, ndc (.327, .372) fante, npp (.324, .401)Gomoa East guan3, ndc (.004, .756) guan3, npp (0, .940)Effutu Mun. fante, ndc (.138, .645) fante, npp (.016, .789)Agona East fante, ndc (0, .948)Agona West Mun. fante, ndc (0, .881)Asikuma-Odoben-Brakwa fante, ndc (.390, .553) fante, npp (.280, .484)Assin South asen, ndc (0, .891)Upper Denkyira East Mun. denkyira, ndc (0, .939)Dangbe West dangme, ndc (.416, .891) dangme, npp (0, .214)Dangbe East dangme, ndc (.486, .701)South Tongu ewe, ndc (.709, .750)Keta Mun. ewe, ndc (.856, .869) ewe, npp (.008, .023)Ketu South ewe, ndc (.679, .711) ewe, npp (0, .041)Ketu North ewe, ndc (.738, .756) ewe, npp (.060, .082)Akatsi ewe, ndc (.683, .697) ewe, npp (0, .014)North Tongu ewe, ndc (.522, .563)Adaklu Anyigbe ewe, ndc (.792, .921) ewe, npp (0, .055)Ho Mun. ewe, ndc (.756, .854) ewe, npp (0, .037)South Dayi ewe, ndc (.430, .494) ewe, npp (.015, .141)North Dayi ewe, ndc (.732, .807) ewe, npp (0, .025)Hohoe Mun. ewe, ndc (.582, .918) ewe, npp (0, .079)Biakoye ewe, ndc (.185, 1) ewe, npp (0, .417)Nkwanta South kokomba, ndc (.114, 1) kokomba, npp (0, .550)Birim South akyem, ndc (0, .562) akyem, npp (.181, 1)
378
Table B-2. Continuedtribe (lower bound, upper bound)
District NDC NPPBirim Mun. akyem, ndc (0, .662)Akwapem South Mun. akuapem, ndc (0, .976)Yilo Krobo dangme, ndc (.381, .604) dangme, npp (0, .292)Asuogyaman dangme, ndc (.335, .705) dangme, npp (0, .441)Lower Manya ewe, ndc (.116, 1) ewe, npp (0, .721)Upper Manya dangme, ndc (.334, .509) dangme, npp (0, .208)East Akim Mun. akyem, ndc (0, .755)Atiwa akyem, ndc (0, .628)Kwaebibirem akyem, ndc (0, .954)Birim North akyem, ndc (0, .830)Kwahu West Mun. kwahu, ndc (0, .413) kwahu, npp (.143, 1)Kwahu South kwahu, ndc (0, .496) kwahu, npp (.188, 1)Kwahu East kwahu, ndc (0, .435) kwahu, npp (.046, 1)Kwahu North ewe, ndc (.109, .991) ewe, npp (0, .474)Atwima Mponua asante, ndc (0, .707)Amansie West asante, ndc (.084, .283) asante, npp (.574, .861)Amansie Central asante, ndc (.142, .284) asante, npp (.648, .824)Obuasi Mun. asante, ndc (0, .520) asante, npp (.038, 1)Adansi North asante, ndc (0, .527) asante, npp (.192, 1)Bekwai Mun. asante, ndc (.010, .193) asante, npp (.745, .987)Bosome Freho asante, ndc (.023, .402) asante, npp (.299, .960)Asante Akim South asante, ndc (0, .869)Asante Akim North Mun. asante, ndc (0, .312) asante, npp (.494, 1)Ejisu Juaben Mun. asante, ndc (0, .248) asante, npp (.661, 1)Bosumtwi asante, ndc (0, .280) asante, npp (.357, .973)Atwima Kwanwoma asante, ndc (0, .204) asante, npp (.696, 1)Kumasi Metro. asante, ndc (0, .299) asante, npp (.410, 1)Atwima Nwabiagya asante, ndc (0, .299) asante, npp (.596, 1)Ahafo Ano South asante, ndc (0, .821)Offinso Mun. asante, ndc (0, .469) asante, npp (.192, 1)Afigya Kwabre asante, ndc (0, .340) asante, npp (.541, 1)Afigya Sekyere asante, ndc (.000, .391) asante, npp (.393, .999)Kwabre East asante, ndc (0, .251) asante, npp (.635, 1)Mampong Mun. asante, ndc (0, .351) asante, npp (.521, 1)Sekyere East asante, ndc (.067, .306) asante, npp (.590, .910)Sekyere Afram Plains asante, ndc (0, .471) asante, npp (.330, 1)Sekyere Central asante, ndc (0, .551) asante, npp (.048, 1)Offinso North asante, ndc (0, .911)Dormaa Mun. boron, ndc (.247, .561) boron, npp (.116, .598)Dormaa East boron, ndc (.244, .426) boron, npp (.273, .572)Sunyani Mun. boron, ndc (0, .676)
379
Table B-2. Continuedtribe (lower bound, upper bound)
District NDC NPPSunyani West boron, ndc (.040, .587) boron, npp (.095, .907)Berekum Mun. boron, ndc (.289, .501) boron, npp (.211, .539)Jaman South boron, ndc (.251, .398) boron, npp (.124, .434)Tain boron, ndc (.234, .547) boron, npp (0, .506)Wenchi Mun. boron, ndc (0, .720)Techiman Mun. boron, ndc (0, .878)Nkoranza South boron, ndc (.121, .869) boron, npp (0, .668)Sawla-Tuna-Kalba dagarte, ndc (.213, 1)West Gonja guan5, ndc (0, .873)Gonja Central guan5, ndc (.154, .751) guan5, npp (0, .652)East Gonja guan5, ndc (0, .818)Kpandai kokomba, ndc (.182, .828) kokomba, npp (0, .499)Nanumba South kokomba, ndc (0, .295)Nanumba North kokomba, ndc (0, .280)Zabzugu Tatali kokomba, ndc (0, .861)Yendi Mun. kokomba, ndc (0, .617)
dagomba, ndc (0, .357)Tamale Metro. dagomba, ndc (.142, .397) dagomba, npp (.071, .667)Tolon Kumbugu dagomba, ndc (.446, .485) dagomba, npp (.227, .288)Savelugu Nanton dagomba, ndc (.456, .548) dagomba, npp (.179, .315)Karaga dagomba, ndc (.040, .528) dagomba, npp (.022, .863)Saboba kokomba, ndc (.623, .726) kokomba, npp (.098, .226)Chereponi chokosi, ndc (.100, .589) chokosi, npp (0, .495)Bunkpurugu Yonyo bimoba, ndc (.357, 1)Mamprusi East mamprusi, ndc (.023, 1) mamprusi, npp (0, .462)Mamprusi West mamprusi, ndc (.316, .593)Builsa builsa, ndc (.482, .610) builsa, npp (0, .065)Kasena Nankana West kasena, ndc (.168, .776)Kasena Nankana East nankansi, ndc (0, .991)Bolgatanga Mun. nankansi, ndc (.252, .560) nankansi, npp (0, .210)Talensi Nabdam nankansi, ndc (.327, .873) nankansi, npp (0, .282)
namnam, npp (0, .952)Bongo nankansi, ndc (.588, .614)Bawku West kusasi, ndc (.292, .592) kusasi, npp (0, .117)Garu Tempane kusasi, ndc (0, .994) kusasi, npp (0, .764)Bawku Mun. kusasi, ndc (0, .803)Wa East dagarte, npp (0, .847)Sissala East sisala, ndc (.299, .552) sisala, npp (0, .098)Nadowli dagarte, ndc (.397, .682) dagarte, npp (0, .233)Jirapa dagarte, ndc (.576, .626) dagarte, npp (.009, .086)Lambussie Karni dagarte, ndc (.224, 1) dagarte, npp (0, .444)Lawra dagarte, ndc (.395, .459) dagarte, npp (0, .094)
380
Table B-3. District-Level Bounds of Votes by Tribe - 2000 Presidential
tribe (lower bound, upper bound)District NDC NPPEllembelle nzema, ndc (.214, .695) nzema, npp (.305, .786)Shama nzema, ndc (.114, .604) fante, npp (.396, .886)Sefwi-Bibiani-Ahwiaso sefwi, ndc (.224, .961) sefwi, npp (.039, .776)KEEA fante, ndc (.506, .755) fante, npp (.245, .494)Cape Coast Metro. fante, ndc (0, .783) fante, npp (.217, 1)Abura-Asebu-Kwam. fante, ndc (.436, .589) fante, npp (.411, 564)Mfantsiman Mun. fante, ndc (.536, .766) fante, npp (.234, .464)Ajumako-Enyan-Essiam fante, ndc (.402, 472) fante, npp (.528, .598)Gomoa West fante, ndc (.463, .562) fante, npp (.438, .537)Effutu Mun. fante, ndc (0, .960) fante, npp (.040, 1)Asikuma Odoben Brakwa fante, ndc (.307, .586) fante, npp (.414, .693)Dangbe West dangme, ndc (.570, 1) dangme, npp (0, .430)Dangbe East dangme, ndc (.823, 1) dangme, npp (0, .177)South Tongu ewe, ndc (.963, 1) ewe, npp (0, .037)Keta Mun. ewe, ndc (.975, .996) ewe, npp (.004, .025)Ketu South ewe, ndc (.941, 1) ewe, npp (0, .059)Ketu North ewe, ndc (.922, .957) ewe, npp (.043, .078)Akatsi ewe, ndc (.965, .992) ewe, npp (.008, .035)North Tongu ewe, ndc (.943, 1) ewe, npp (0, .057)Adaklu Anyigbe ewe, ndc (.955, 1) ewe, npp (0, .045)Ho Mun. ewe, ndc (.915, 1) ewe, npp (0, .085)South Dayi ewe, ndc (.907, 1) ewe, npp (0, .093)North Dayi ewe, ndc (.920, 1) ewe, npp (0, .080)Hohoe Mun. ewe, ndc (.825, 1) ewe, npp (0, .175)Birim South akyem, ndc (0, .831) akyem, npp (.169, 1)Yilo Krobo dangme, ndc (.447, .974) dangme, npp (.026, .553)Asuogyaman dangme, ndc (.228, 1) dangme, npp (0, .772)Upper Manya dangme, ndc (.687, 1) dangme, npp (0, .313)Kwahu West Mun. kwahu, ndc (0, .678) kwahu, npp (.322, 1)Kwahu South kwahu, ndc (0, .857) kwahu, npp (.143, 1)Kwahu East kwahu, ndc (0, .885) kwahu, npp (.115, 1)Amansie West asante, ndc (0, .217) asante, npp (.783, 1)Amansie Central asante, ndc (0, .175) asante, npp (.825, 1)Adansi North asante, ndc (0, .555) asante, npp (.445, 1)Bekwai Mun. asante, ndc (0, .145) asante, npp (.855, 1)Bosome Freho asante, ndc (0, .488) asante, npp (.512, 1)Asante Akim North Mun. asante, ndc (0, .460) asante, npp (.540, 1)Ejisu Juaben Mun. asante, ndc (0, .250) asante, npp (.750, 1)Bosumtwi asante, ndc (0, .264) asante, npp (.736, 1)Atwima Kwanwoma asante, ndc (0, .165) asante, npp (.835, 1)Kumasi Metro. asante, ndc (0, .556) asante, npp (.444, 1)
381
Table B-3. Continuedtribe (lower bound, upper bound)
District NDC NPPAtwima Nwabiagya asante, ndc (0, .274) asante, npp (.726, 1)Offinso Mun. asante, ndc (0, .715) asante, npp (.285, 1)Afigya Kwabre asante, ndc (0, .371) asante, npp (.629, 1)Afigya Sekyere asante, ndc (0, .407) asante, npp (.593, 1)Kwabre East asante, ndc (0, .242) asante, npp (.758, 1)Mampong Mun. asante, ndc (0, .360) asante, npp (.640, 1)Sekyere East asante, ndc (0, .305) asante, npp (.695, 1)Sekyere Afram Plains asante, ndc (0, .619) asante, npp (.381, 1)Dormaa Mun. boron, ndc (.097, .747) boron, npp (.253, .903)Dormaa East boron, ndc (.060, .451) boron, npp (.549, .940)Sunyani West boron, ndc (0, .839) boron, npp (.161, 1)Berekum Mun. boron, ndc (.055, .491) boron, npp (.509, .945)Jaman South boron, ndc (.293, .751) boron, npp (.249, .707)Kpandai kokomba, ndc (.149, 1)Tamale Metro. dagomba, ndc (.111, .856) dagomba, npp (.144, .890)Tolon Kumbugu dagomba, ndc (.639, .713) dagomba, npp (.287, .361)Savelugu Nanton dagomba, ndc (.574, .741) dagomba, npp (.259, .426)Karaga dagomba, ndc (.048, 1) dagomba, npp (0, .952)Saboba kokomba, ndc (.657, .874) kokomba, npp (.126, .343)Mamprusi West mamprusi, ndc (.381, 1) mamprusi, npp (0, .619)Builsa builsa, ndc (.681, 1) builsa, npp (0, .319)Kasena Nankana West kasena, ndc (.008, 1) kasena, npp (0, .992)Bongo nankansi, ndc (.851, .920) nankansi, npp (.080, .149)Bawku West kusasi, ndc (.958, 1) kusasi, npp (0, .042)Sissala East sisala, ndc (.589, 1) sisala, npp (0, .411)Nadowli dagarte, ndc (.729, 1) dagarte, npp (0, .271)Jirapa dagarte, ndc (.936, 1) dagarte, npp (0, .064)Lawra dagarte, ndc (.858, 1) dagarte, npp (0, .142)
382
Table B-4. District-Level Bounds of Votes by Tribe - 2000 Parliamentary
tribe (lower bound, upper bound)District NDC NPPJomoro fante, ndc (0, .871)
nzema, ndc (0, .225)
Ellembelle nzema, ndc (.085, .258)Nzema East evalue, ndc (0, .778)
nzema, ndc (0, .901)Ahanta West ahanta, ndc (0, .294)Sekondi Takoradi Metro. fante, ndc (0, .300)Shama fante, ndc (.009, .233) fante, npp (.181, .969)Mpohor-Wassa East fante, ndc (0, .716)
wasa, ndc (.056, .798)Tarkwa Nsuaem Mun. fante, ndc (0, .621)
wasa, ndc (0, .358)Prestea/Huni Valley fante, ndc (0, .906)
wasa, ndc (0, .645)Wassa Amenfi East wasa, ndc (0, .519)Wassa Amenfi West wasa, ndc (0, .779)Aowin/Suaman aowin, ndc (0, .716)Sefwi Wiawso sefwi, ndc (0, .834)Sefwi-Bibiani-Ahwiaso sefwi, ndc (.112, .522) sefwi, npp (.055, .798)Juabeso sefwi, ndc (0, .754)KEEA fante, ndc (.196, .306) fante, npp (0, .243)Cape Coast Metro. fante, ndc (0, .423) fante, npp (.201, 1)Abura-Asebu-Kwam. fante, ndc (.215, .293) fante, npp (.395, 556)Mfantsiman Mun. fante, ndc (.209, .310) fante, npp (.236, .485)Ajumako-Enyan-Essiam fante, ndc (.212, .248) fante, npp (.515, .586)Gomoa West fante, ndc (.210, .255) fante, npp (.408, .512)Gomoa East guan3, ndc (0, .411)Effutu Mun. fante, ndc (0, .497)Agona East fante, ndc (0, .618)
agona, ndc (0, .932)Agona West Mun. fante, ndc (0, .555)
agona, ndc (0, .706)Asikuma-Odoben-Brakwa fante, ndc (.180, .343) fante, npp (.419, .695)Assin South fante, ndc (0, .782)
asen, ndc (0, .529)Assin North Mun. fante, ndc (0, .782)
asen, ndc (0, .796)Twifo-Heman-Lower-Denkyira fante, ndc (0, .790)Upper Denkyira East Mun. denkyira, ndc (0, .544)Ga East Mun. ewe, ndc (0, .861)Ledzokuku/Krowor Mun. ga, ndc (0, .586)
383
Table B-4. Continuedtribe (lower bound, upper bound)
District NDC NPPAshaiman Mun. dangme, ndc (0, .852)
ewe, ndc (0, .360)Tema Metro. fante, ndc (0, .947)
ewe, ndc (0, .788)Dangbe West dangme, ndc (.091, .565) dangme, npp (0, .600)Dangbe East dangme, ndc (.113, .328) dangme, npp (0, .173)South Tongu ewe, ndc (.599, .639) ewe, npp (0, .026)Keta Mun. ewe, ndc (.326, .339) ewe, npp (.002, .040)Ketu South ewe, ndc (.437, .469) ewe, npp (.020, .087)Ketu North ewe, ndc (.303, .321) ewe, npp (.052, .105)Akatsi ewe, ndc (.443, .457) ewe, npp (0, .015)North Tongu ewe, ndc (.475, .516) ewe, npp (0, .032)Adaklu Anyigbe ewe, ndc (.554, .684) ewe, npp (0, .048)Ho Mun. ewe, ndc (.452, .550) ewe, npp (0, .082)South Dayi ewe, ndc (.313, .377) ewe, npp (0, .097)North Dayi ewe, ndc (.371, .446) ewe, npp (0, .055)Hohoe Mun. ewe, ndc (.203, .539) ewe, npp (0, .490)Biakoye ewe, ndc (0, .978)Jasikan ewe, ndc (0, .636)
guan1, ndc (0, .836)Kadjebi ewe, ndc (0, .542)Nkwanta South kokomba, ndc (0, .656)Birim South akyem, ndc (0, .386)Birim Mun. akyem, ndc (0, .493)
fante, ndc (0, .924)Suhum-Kraboa-Coaltar akuapem, ndc (0, .925)Akuapem South Mun. akuapem, ndc (0, .623)Akwapem North akuapem, ndc (0, .706)
guan4, ndc (0, .784)New Juaben Mun. asante, ndc (0, .752)Yilo Krobo dangme, ndc (.119, .343) dangme, npp (.012, .656)Asuogyaman dangme, ndc (.089, .459) dangme, npp (.037, .813)Lower Manya ewe, ndc (0, .643)Upper Manya dangme, ndc (.196, .371) dangme, npp (0, .336)Fanteakwa dangme, ndc (0, .770)
akyem, ndc (0, .877)East Akim Mun. akyem, ndc (0, .473)Atiwa akyem, ndc (0, .461)Kwaebibirem akyem, ndc (0, .527)Birim North akyem, ndc (0, .678)Kwahu West Mun. kwahu, ndc (0, .272) kwahu, npp (.182, 1)Kwahu South kwahu, ndc (0, .396)
384
Table B-4. Continuedtribe (lower bound, upper bound)
District NDC NPPKwahu East kwahu, ndc (0, .304)Kwahu North ewe, ndc (0, .719)Atwima Mponua asante, ndc (0, .473)Amansie West asante, ndc (0, .121) asante, npp (.771, 1)Amansie Central asante, ndc (0, .123) asante, npp (.799, 1)Adansi South asante, ndc (0, .932)Obuasi Mun. asante, ndc (0, .310)Adansi North asante, ndc (0, .271) asante, npp (.342, 1)Bekwai Mun. asante, ndc (0, .094) asante, npp (.841, 1)Bosome Freho asante, ndc (0, .261) asante, npp (.429, 1)Asante Akim South asante, ndc (0, .605)Asante Akim North Mun. asante, ndc (0, .253) asante, npp (.521, 1)Ejisu Juaben Mun. asante, ndc (0, .145) asante, npp (.688, 1)Bosumtwi asante, ndc (0, .244) asante, npp (.476, 1)Atwima Kwanwoma asante, ndc (0, .096) asante, npp (.811, 1)Kumasi Metro. asante, ndc (0, .168) asante, npp (.402, 1)Atwima Nwabiagya asante, ndc (0, .165) asante, npp (.706, 1)Ahafo Ano South asante, ndc (0, .579)Ahafo Ano North asante, ndc (0, .720)Offinso Mun. asante, ndc (0, .323) asante, npp (.239, 1)Afigya Kwabre asante, ndc (0, .256) asante, npp (.558, 1)Afigya Sekyere asante, ndc (0, .247) asante, npp (.574, 1)Kwabre East asante, ndc (0, .132) asante, npp (.765, 1)Mampong Mun. asante, ndc (0, .218) asante, npp (.566, 1)Sekyere East asante, ndc (0, .199) asante, npp (.663, 1)Sekyere Afram Plains asante, ndc (0, .243) asante, npp (.078, 1)Sekyere Central asante, ndc (0, .318)Ejura-Sekyedumase asante, ndc (0, .898)Offinso North asante, ndc (0, .595)Asunafo South asante, ndc (0, .624)Asunafo North Mun. asante, ndc (0, .644)Asutifi asante, ndc (0, .816)Dormaa Mun. boron, ndc (.046, .359) boron, npp (.219, .901)Dormaa East boron, ndc (.052, .235) boron, npp (.492, .887)Tano South asante, ndc (0, .816)Sunyani Mun. boron, ndc (0, .362)Sunyani West boron, ndc (0, .388)Berekum Mun. boron, ndc (.033, .245) boron, npp (.503, .933)Jaman South boron, ndc (.079, .226) boron, npp (.286, .749)Tain boron, ndc (0, .305)Wenchi Mun. boron, ndc (0, .514)
dagarte, ndc (0, .770)
385
Table B-4. Continuedtribe (lower bound, upper bound)
District NDC NPPTechiman Mun. boron, ndc (0, .565)Nkoranza South boron, ndc (0, .518)Kintampo South boron, ndc (0, .783)Sawla-Tuna-Kalba dagarte, ndc (0, .573)
othergrusi1, ndc (0, .994)West Gonja guan5, ndc (0, .683)Gonja Central guan5, ndc (0, .511)East Gonja guan5, ndc (0, .410)Kpandi kokomba, ndc (0, .559)Nanumba South kokomba, ndc (0, .549)Nanumba North kokomba, ndc (.004, .611) kokomba, npp (0, .987)Zabzugu Tatali kokomba, ndc (0, .387)
dagomba, ndc (0, .797)Yendi Mun. kokomba, ndc (0, .626)
dagomba, ndc (0, .362)Tamale Metro. dagomba, ndc (.032, .287) dagomba, npp (.142, .904)Tolon Kumbugu dagomba, ndc (.327, .365) dagomba, npp (.289, .364)Savelugu Nanton dagomba, ndc (.338, .431) dagomba, npp (.251, .412)Karaga dagomba, ndc (0, .478)Saboba kokomba, ndc (.300, .402) kokomba, npp (.112, .338)Chereponi chokosi, ndc (0, .382)Bunkpurugu Yonyo bimoba, ndc (0, .280)
kokomba, ndc (0, .513)Mamprusi East mamprusi, ndc (0, .576)Mamprusi West mamprusi, ndc (.023, .300) mamprusi, npp (0, .612)Builsa builsa, ndc (.190, .317) builsa, npp (0, .284)Kasena Nankana West kasena, ndc (0, .597)Kasena Nankana East nankansi, ndc (0, .624)
kasena, ndc (0, .842)Bolgatanga Mun. nankansi, ndc (0, .245)Talensi Nabdam nankansi, ndc (0, .471)
namnam, ndc (0, .929)Bongo nankansi, ndc (.349, .376) nankansi, npp (.075, .141)Bawku West kusasi, ndc (.122, .422) kusasi, npp (0, .268)Garu Tempane kusasi, ndc (0, .486)
bimoba, ndc (0, .911)Bawku Mun. kusasi, ndc (0, .600)Wa West dagarte, ndc (0, .864)Wa East dagarte, ndc (0, .807)Sissala East sisala, ndc (.099, .352) sisala, npp (0, .157)Nadowli dagarte, ndc (.188, .473) dagarte, npp (0, .224)Jirapa dagarte, ndc (.456, .506) dagarte, npp (0, .057)Lambussie Karni dagarte, ndc (0, .688)Lawra dagarte, ndc (.366, .430) dagarte, npp (.005, .155)
386
Table B-5. District-Level Bounds of Votes by Tribe - 2000 Pres. Runoff
tribe (lower bound, upper bound)District NDC NPPEllembelle nzema, ndc (.028, .452) nzema, npp (.548, .972)Ahanta West ahanta, ndc (0, .728) ahanta, npp (.272, 1)Shama fante, ndc (.046, .495) fante, npp (.505, .954)Sefwi-Bibiani-Ahwiaso sefwi, ndc (.098, .831) sefwi, npp (.169, .902)KEEA fante, ndc (.360, .576) fante, npp (.424, .640)Cape Coast Metro. fante, ndc (0, .758) fante, npp (.242, 1)Abura-Asebu-Kwamankese fante, ndc (.355, .507) fante, npp (.493, .645)Mfantsiman Mun. fante, ndc (.409, .612) fante, npp (.388, .591)Ajumako-Enyan-Essiam fante, ndc (.305, .374) fante, npp (.626, .695)Gomoa West fante, ndc (.378, .478) fante, npp (.522, .622)Effutu Mun. fante, ndc (0, .973) fante, npp (.027, 1)Asikuma-Odoben-Brakwa fante, ndc (.195, .481) fante, npp (.519, .805)Dangbe West dangme, ndc (.384, 1) dangme, npp (0, .616)Dangbe East dangme, ndc (.553, 1) dangme, npp (0, .447)South Tongu ewe, ndc (.937, .990) ewe, npp (.010, .063)Keta Mun. ewe, ndc (.963, .979) ewe, npp (.021, .037)Ketu South ewe, ndc (.931, .980) ewe, npp (.020, .069)Ketu North ewe, ndc (.891, .920) ewe, npp (.080, .109)Akatsi ewe, ndc (.919, .941) ewe, npp (.059, .081)North Tongu ewe, ndc (.911, .963) ewe, npp (.037, .089)Adaklu Anyigbe ewe, ndc (.927, 1) ewe, npp (0, .073)Ho Mun. ewe, ndc (.899, 1) ewe, npp (0, .101)South Dayi ewe, ndc (.843, .978) ewe, npp (.022, .157)North Dayi ewe, ndc (.880, 1) ewe, npp (0, .120)Hohoe Mun. ewe, ndc (.782, 1) ewe, npp (0, .218)Birim South akyem, ndc (.654, 1) akyem, npp (.346, 1)Yilo Krobo dangme, ndc (.285, .851) dangme, npp (.149, .715)Asuogyaman dangme, ndc (.149, .962) dangme, npp (.038, .851)Upper Manya dangme, ndc (.519, 1) dangme, npp (0, .481)Kwahu West Mun. kwahu, ndc (0, .547) kwahu, npp (.453, 1)Kwahu South kwahu, ndc (0, .733) kwahu, npp (.267, 1)Kwahu East kwahu, ndc (0, .804) kwahu, npp (.196, 1)Kwahu North ewe, ndc (.060, 1) ewe, npp (0, .940)Amansie West asante, ndc (0, .159) asante, npp (.841, 1)Amansie Central asante, ndc (0, .145) asante, npp (.855, 1)Obuasi Mun. asante, ndc (0, .855) asante, npp (.145, 1)Adansi North asante, ndc (0, .440) asante, npp (.560, 1)Bekwai Mun. asante, ndc (0, .119) asante, npp (.881, 1)Bosome Freho asante, ndc (0, .356) asante, npp (.644, 1)Asante Akim North Mun. asante, ndc (0, .398) asante, npp (.602, 1)Ejisu Juaben Mun. asante, ndc (0, .213) asante, npp (.787, 1)
387
Table B-5. Continuedtribe (lower bound, upper bound)
District NDC NPPBosumtwi asante, ndc (0, .226) asante, npp (.774, 1)Atwima Kwanwoma asante, ndc (0, .120) asante, npp (.880, 1)Kumasi Metro. asante, ndc (0, .458) asante, npp (.542, 1)Atwima Nwabiagya asante, ndc (0, .228) asante, npp (.772, 1)Offinso Mun. asante, ndc (0, .591) asante, npp (.409, 1)Afigya Kwabre asante, ndc (0, .309) asante, npp (.691, 1)Afigya Sekyere asante, ndc (0, .350) asante, npp (.650, 1)Kwabre East asante, ndc (0, .207) asante, npp (.793, 1)Mampong Mun. asante, ndc (0, .312) asante, npp (.688, 1)Sekyere East asante, ndc (0, .254) asante, npp (.746, 1)Sekyere Afram Plains asante, ndc (0, .523) asante, npp (.477, 1)Sekyere Central asante, ndc (0, .810) asante, npp (.190, 1)Dormaa Mun. boron, ndc (0, .642) boron, npp (.358, 1)Dormaa East boron, ndc (0, .374) boron, npp (.626, 1)Sunyani West boron, ndc (0, .721) boron, npp (.279, 1)Berekum Mun. boron, ndc (0, .418) boron, npp (.582, 1)Jaman South boron, ndc (.161, .628) boron, npp (.372, .839)Tain boron, ndc (0, .926) boron, npp (.074, 1)Kpandai kokomba, ndc (.085, 1) kokomba, npp (0, .915)Nanumba North kokomba, ndc (.038, 1) kokomba, npp (0, .962)Tamale Metro. dagomba, ndc (.064, .580) dagomba, npp (.420, .936)Tolon Kumbugu dagomba, ndc (.512, .575) dagomba, npp (.425, .488)Savelugu Nanton dagomba, ndc (.525, .700) dagomba, npp (.330, .475)Saboba kokomba, ndc (.457, .633) kokomba, npp (.367, .543)Mamprusi West mamprusi, ndc (.086, .702) mamprusi, npp (.298, .914)Builsa builsa, ndc (.386, .641) builsa, npp (.359, .614)Bolgatanga Mun. nankansi, ndc (0, .649) nankansi, npp (.351, 1)Bongo nankansi, ndc (.647, .697) nankansi, npp (.303, .353)Bawku West kusasi, ndc (.377, 1) kusasi, npp (0, .623)Sissala East sisala, ndc (.068, .547) sisala, npp (.453, .932)Nadowli dagarte, ndc (.416, 1) dagarte, npp (0, .584)Jirapa dagarte, ndc (.808, .910) dagarte, npp (.090, .192)Lawra dagarte, ndc (.747, .893) dagarte, npp (.107, .253)
388
Table B-6. District-Level Bounds of Votes by Tribe - 2004 Presidential
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .422) nzema, npp (.002, .613)Ellembelle nzema, ndc (.127, .299) nzema, npp (.370, .543)Nzema East evalue, ndc (0, .786)
nzema, ndc (0, .910)Ahanta West ahanta, ndc (0, .275) ahanta, npp (.349, .980)Sekondi Takoradi Metro. fante, ndc (0, .433) fante, npp (.158, 1)Shama fante, ndc (.124, .349) fante, npp (.377, .601)Mpohor-Wassa East fante, ndc (0, .932)
wasa, ndc (0, .820)Tarkwa Nsuaem Mun. wasa, ndc (0, .675)Prestea/Huni Valley wasa, ndc (0, .917)Wassa Amenfi East wasa, ndc (0, .603) wasa, npp (.028, 1)Wassa Amenfi West wasa, npp (0, .990)Sefwi Wiawso sefwi, ndc (.251, .924) sefwi, npp (0, .555)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.185, .596) sefwi, npp (.226, .636)Juabeso sefwi, ndc (.035, 1) sefwi, npp (0, .563)KEEA fante, ndc (.266, .376) fante, npp (.371, .481)Cape Coast Metro. fante, ndc (.052, .513) fante, npp (.238, .699)Abura-Asebu-Kwamnkese fante, ndc (.330, .408) fante, npp (.403, .481)Mfantsiman Mun. fante, ndc (.324, .425) fante, npp (.343, .444)Ajumako-Enyan-Essiam fante, ndc (.254, .290) fante, npp (.494, .530)Gomoa West fante, ndc (.250, .295) fante, npp (.465, .509)Effutu Mun. guan3, ndc (0, .623) guan3, npp (.054, .806)Gomoa East fante, ndc (0, .488) fante, npp (.179, .685)Agona East agona, ndc (0, .996)
fante, ndc (0, .660)Agona West Mun. agona, ndc (0, .835)
fante, ndc (0, .656)Asikuma-Odoben-Brakwa fante, ndc (.174, .337) fante, npp (.461, .624)Assin South asen, ndc (0, .577) asen, npp (.068, 1)
fante, ndc (0, .853)Twifo-Heman-LowerDenkyira
fante, ndc (0, .942)
Upper Denkyira East Mun. denkyira, ndc (0, .721)Upper Denkyira West denkyira, ndc (0, .545) denkyira, npp (.112, .1)Ashaiman Mun. ewe, npp (0, .978)Dangbe West dangme, ndc (.465, .939) dangme, npp (0, .254)Dangbe East dangme, ndc (.560, .774) dangme, npp (0, .183)South Tongu ewe, ndc (.809, .849) ewe, npp (.030, .070)Keta Mun. ewe, ndc (.783, .796) ewe, npp (.023, .036)Ketu South ewe, ndc (.795, .827) ewe, npp (.027, .060)
389
Table B-6. Continuedtribe (lower bound, upper bound)
District NDC NPPKetu North ewe, ndc (.679, .697) ewe, npp (.166, .184)Akatsi ewe, ndc (.767, .781) ewe, npp (.068, .083)North Tongu ewe, ndc (.756, .797) ewe, npp (.029, .070)Adaklu Anyigbe ewe, ndc (.774, .903) ewe, npp (0, .075)Ho Mun. ewe, ndc (.756, .854) ewe, npp (0, .095)South Dayi ewe, ndc (.715, .779) ewe, npp (.057, .122)North Dayi ewe, ndc (.760, .834) ewe, npp (.018, .092)Hohoe Mun. ewe, ndc (.669, 1) ewe, npp (0, .141)
guan1, npp (0, .982)Biakoye ewe, ndc (.159, 1) ewe, npp (0, .507)Jasikan ewe, ndc (.279, 1) ewe, npp (0, .387)
guan1, ndc (.052, 1) guan1, npp (0, .508)Kadjebi ewe, ndc (.019, .1) ewe, npp (0, .609)Krachi East guan7, npp (0, .800)
kokomba, npp (0, .647)Krachi West kokomba, npp (0, .622)Nkwanta South kokomba, ndc (.277, .596) kokomba, npp (.133, .452)Nkwanta North akyem, ndc (0, .347) akyem, npp (.413, 1)Birim South akyem, ndc (0, .496) akyem, npp (.178, 1)
fante, ndc (0, .930)Suhum-Kraboa-Coaltar akuapem, ndc (0, .788)Akwapem South Mun. akuapem, ndc (0, .781)
guan4, ndc (0, .868)Akwapem North asante, ndc (0, .985)New Juaben Mun. dangme, ndc (.386, .609) dangme, npp (.152, .375)Yilo Krobo dangme, ndc (.339, .709) dangme, npp (.055, .424)Lower Manya ewe, ndc (0, .964) ewe, npp (0, .857)Asuogyaman dangme, ndc (.439, .615) dangme, npp (.154, .329)Upper Manya dangme, ndc (0, .891)Fanteakwa akyem, ndc (0, .561) akyem, npp (.107, 1)East Akim Mun. akyem, ndc (0, .721)Kwaebibirem akyem, ndc (0, .502) akyem, npp (.149, 1)Akyem Mansa akyem, ndc (0, .894)Birim North akyem, ndc (0, .319) akyem, npp (.413, 1)Atiwa kwahu, ndc (0, .266) kwahu, npp (.368, .958)Kwahu West Mun. kwahu, ndc (0, .182) kwahu, npp (0, .459)Kwahu South kwahu, ndc (0, .210) kwahu, npp (0, .553)
ewe, ndc (0, .764)Kwahu East ewe, ndc (.280, 1) ewe, npp (0, .343)Kwahu North asante, ndc (0, .521) asante, npp (.228, 1)Atwima Mponua asante, ndc (0, .127) asante, npp (.711, .910)
390
Table B-6. Continuedtribe (lower bound, upper bound)
District NDC NPPAmansie West asante, ndc (0, .108) asante, npp (.752, .894)Adansi South asante, ndc (0, .466) asante, npp (.251, 1)Obuasi Mun. asante, ndc (0, .293) asante, npp (.503, 1)Adansi North asante, ndc (0, .104) asante, npp (.797, .980)Bekwai Mun. asante, ndc (0, .209) asante, npp (.641, 1)Bosome Freho asante, ndc (0, .570) asante, npp (.013, 1)Asante Akim South asante, ndc (0, .274) asante, npp (.539, .955)Asante Akim North Mun. asante, ndc (0, .195) asante, npp (.635, .977)Ejisu Juaben Mun. asante, ndc (0, .151) asante, npp (.678, .959)Bosumtwi asante, ndc (0, .125) asante, npp (.705, .999)Atwima Kwanwoma asante, ndc (0, .354) asante, npp (.406, 1)Kumasi Metro. asante, ndc (0, .220) asante, npp (.599, 1)Atwima Nwabiagya asante, ndc (0, .585) asnate, npp (.152, 1)Ahafo Ano South asante, ndc (0, .816)Ahafo Ano North asante, ndc (0, .445) asante, npp (.319, 1)Offinso Mun. asante, ndc (0, .270) asante, npp (.589, .980)Afigya Kwabre asante, ndc (0, .200) asante, npp (.618, 1)Kwabre East asante, ndc (0, .236) asante, npp (.637, .945)Afigya Sekyere asante, ndc (0, .261) asante, npp (.564, 1)Mampong Mun. asante, ndc (0, .187) asante, npp (.656, .895)Sekyere East asante, ndc (0, .302) asante, npp (.443, .967)Sekyere Afram Plains asante, ndc (0, .413) asante, npp (.303, .939)Ejura Sekyere Dumasi asante, ndc (0, .957)Asunafo South asante, ndc (0, .850)Asutifi boron, ndc (.161, .475) boron, npp (.283, .597)Dormaa Mun. boron, ndc (.135, .317) boron, npp (.447, .630)Tano North boron, ndc (0, .630)Sunyani Mun. boron, ndc (0, .484) boron, npp (.268, .815)Sunyani West boron, ndc (.156, .368) boron, npp (.406, .618)Berekum Mun. boron, ndc (.171, .320) boron, npp (.401, .550)Jaman South boron, ndc (.306, .450) boron, npp (.223, .367)Jaman North boron, ndc (.149, .462) boron, npp (.199, .512)Tain boron, ndc (0, .698) boron, npp (0, .915)Wenchi Mun. boron, ndc (0, .869) boron, npp (0, .757)Techiman Mun. boron, ndc (0, .787) boron, npp (0, .741)Nkoranza South boron, ndc (0, .551) boron, npp (.008, .652)Atebubu Amantin guan8, npp (0, .866)Sene kokomba, npp (0, .894)Kintampo North Mun. guan5, npp (0, .914)
dagarte, npp (0, .739)Bole dagarte, ndc (0, .905) dagarte, npp (0, .287)
othergrusi1, npp (0, .499)
391
Table B-6. Continuedtribe (lower bound, upper bound)
District NDC NPPSawla-Tuna-Kalba guan5, ndc (0, .934) guan5, npp (0, .952)West Gonja guan5, ndc (0, .570) guan5, npp (0, .401)Gonja Central guan5, ndc (0, .893) guan5, npp (0, .874)East Gonja kokomba, ndc (.196, .842) kokomba, npp (0, .512)Kpandai kokomba, ndc (.087, .668) kokomba, npp (.075, .657)Nanumba South kokomba, ndc (.037, .645) kokomba, npp (.031, .639)Nanumba North kokomba, ndc (0, .878) kokomba, npp (0, .717)Zabzugu Tatali dagomba, ndc (.019, .696) dagomba, npp (.052, .729)Yendi Mun. dagomba, ndc (.546, .801) dagomba, npp (.031, .286)Tamale Metro. dagomba, ndc (.580, .618) dagomba, npp (.225, .263)Tolon Kumbugu dagomba, ndc (.545, .637) dagomba, npp (.247, .340)Savelugu Nanton dagomba, ndc (.422, .703) dagomba, npp (.100, .381)Karaga dagomba, ndc (.043, .719) dagomba, npp (.078, .754)Gushiegu kokomba, ndc (.306, .408) kokomba, npp (.403, .505)Saboba chokosi, ndc (.011, .501) chokosi, npp (.100, .589)Chereponi bimoba, ndc (0, .738) bimoba, npp (0, .447)
kokomba, npp (0, .818)Bunkpurugu Yonyo mamprusi, ndc (0, .648) mamprusi, npp (0, .473)Mamprusi East mamprusi, ndc (.139, .416) mamprusi, npp (.034, .311)Mamprusi West builsa, ndc (.288, .415) builsa, npp (.150, .277)Builsa kasena, ndc (.202, .810) nankansi, npp (0, .880)
kasena, npp (0, .362)Kasena Nankana West nankansi, ndc (0, .711) nankansi, npp (0, .866)
kasena, ndc (0, .960)Kasena Nankana East nankansi, ndc (.137, .446) nankansi, npp (0, .299)Bolgatanga Mun. nankansi, ndc (.083, .628) nankansi, npp (0, .338)
namnam, npp (0, .667)Talensi Nabdam nankansi, ndc (.481, .508) nankansi, npp (.253, .280)Bongo kusasi, ndc (.220, .520) kusasi, npp (0, .286)Bawku West kusasi, ndc (0, .954) kusasi, npp (0, .519)
bimoba, npp (0, .973)Garu Tempane kusasi, ndc (.031, .932) kusasi, npp (0, .454)Bawku Mun. dagarte, ndc (0, .875) dagarte, npp (0, .371)Wa West wali, npp (0, .906)Wa Mun. dagarte, ndc (0, .824) dagarte, npp (0, .863)Wa East sisala, ndc (.099, .252) sisala, npp (.223, .375)Sissala East dagarte, ndc (.353, .638) dagarte, npp (0, .273)Nadowli dagarte, ndc (.521, .572) dagarte, npp (.102, .153)Jirapa sisala, ndc (.041, .429) sisala, npp (0, .344)Sissala West dagarte, ndc (0, .806) dagarte, npp (0, .403)
sisala, npp (0, .699)Lambussie Karni dagarte, ndc (.467, .532) dagarte, npp (.185, .250)
392
Table B-7. District-Level Bounds of Votes by Tribe - 2004 Parliamentary
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .484) nzema, npp (0, .436)Ellembelle nzema, ndc (.161, .334)Nzema East evalue, ndc (0, .760)
nzema, ndc (0, .880)Ahanta West ahanta, ndc (0, .258) ahanta, npp (.165, .795)
fante, ndc (0, .939)Sekondi Takoradi Metro. fante, ndc (0, .418) fante, npp (.042, 1)Shama fante, ndc (0 .177) fante, npp (.269, .493)Mpohor-Wassa East fante, ndc (0, .667)
wasa, ndc (0, .587)Tarkwa Nsuaem Mun. wasa, ndc (0, .644)Prestea/Huni Valley wasa, ndc (0, .604)
fante, ndc (0, .992)Wassa Amenfi East wasa, ndc (0, .604) wasa, npp (.054, 1)Wassa Amenfi West wasa, npp (0, .990)Sefwi Wiawso sefwi, ndc (.236, .908) sefwi, npp (0, .587)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.189, .599) sefwi, npp (.241, .652)Juabeso sefwi, ndc (.043, 1) sefwi, npp (0, .562)KEEA fante, ndc (.202, .312) fante, npp (.371, .481)Cape Coast Metro. fante, ndc (.093, .554) fante, npp (.176, .637)Abura-Asebu-Kwamankese fante, ndc (.297, .375) fante, npp (.390, .468)Mfantsiman Mun. fante, ndc (.292, .393) fante, npp (.372, .473)Ajumako-Enyan-Essiam fante, ndc (.297, .333) fante, npp (.459, .495)Gomoa West fante, ndc (.228, .272) fante, npp (.485, .530)Effutu Mun. guan3, ndc (0, .686) guan3, npp (.000, .752)Gomoa East fante, ndc (0, .464) fante, npp (.124, .631)Ewutu Senya fante, ndc (0, .971)Agona East agona, ndc (0, .493)
fante, ndc (0, .327)Agona West Mun. fante, ndc (0, .789)Asikuma-Odoben-Brakwa fante, ndc (.234, .397) fante, npp (.414, .577)Assin South asen, ndc (0, .589) asen, npp (.042, 1)
fante, ndc (0, .871)Assin North Mun. asen, ndc (0, .970)
fante, ndc (0, .953)Upper Denkyira East Mun. denkyira, ndc (0, .545)Upper Denkyira West denkyira, ndc (0, .556) denkyira, npp (.122, 1)Ledzokuku/Krowor Mun. ga, ndc (0, .937) ga, npp (0, .969)Ashaiman Mun. ewe, npp (0, .931)Dangbe West dangme, ndc (.426, .900) dangme, npp (0, .355)
393
Table B-7. Continuedtribe (lower bound, upper bound)
District NDC NPPDangbe East dangme, ndc (.466, .680) dangme, npp (0, .185)South Tongu ewe, ndc (.773, .814) ewe, npp (.062, .102)Keta Mun. ewe, ndc (.612, .624) ewe, npp (.041, .054)Ketu South ewe, ndc (.582, 614) ewe, npp (.029, .061)Ketu North ewe, ndc (.649, .667) ewe, npp (.225, .243)Akatsi ewe, ndc (.712, .726) ewe, npp (.103, .117)North Tongu ewe, ndc (.597, .638) ewe, npp (.023, .064)Adaklu Anyigbe ewe, ndc (.323, .453) ewe, npp (0, .072)Ho Mun. ewe, ndc (.704, .802) ewe, npp (.008, .106)South Dayi ewe, ndc (.114, .178) ewe, npp (.064, .128)North Dayi ewe, ndc (.678, .753) ewe, npp (.027, .101)Hohoe Mun. ewe, ndc (.603, .939) ewe, npp (0, .203)Biakoye ewe, npp (0, .493)Jasikan ewe, ndc (.111, 1) ewe, npp (0, .413)
guan1, ndc (.052, 1) guan1, npp (0, .544)Kadjebi ewe, npp (0, .769)Krachi East guan7, npp (0, .800)
ewe, npp (0, .693)Krachi West kokomba, npp (0, .628)
guan7, npp (0, .777)Nkwanta South kokomba, npp (0, .631)Nkwanta North kokomba, ndc (0, .312) kokomba, npp (.036, .356)
akyem, npp (.413, 1)Birim South akyem, ndc (0, .430) akyem, npp (.345, .936)Birim Mun. akyem, ndc (0, .480) akyem, npp (.198, 1)
fante, ndc (0, .901)Akwapem South Mun. akuapem, ndc (0, .740) akuapem, npp (0, .991)
guan4, ndc (0, .868)Akwapem North akuapem, ndc (0, .796)
guan4, ndc (0, .884)New Juaben Mun. asante, ndc (0, .911)Yilo Krobo dangme, ndc (.354, .577)Lower Manya dangme, ndc (.237, .607) dangme, npp (.128, .498)Asuogyaman ewe, ndc (0, .849) ewe, npp (0, .952)Upper Manya dangme, ndc (.426, .601) dangme, npp (.202, .378)Fanteakwa dangme, ndc (0, .932)East Akim Mun. akyem, ndc (0, .559) akyem, npp (0.046, 1)Kwaebibirem akyem, ndc (0, .759)Akyem Mansa akyem, ndc (0, .482) akyem, npp (.033, 1)
fante, ndc (0, .993)Birim North akyem, ndc (0, .778) akyem, npp (.413, 1)Atiwa akyem, ndc (0, .346) akyem, npp (.353, 1)
394
Table B-7. Continuedtribe (lower bound, upper bound)
District NDC NPPKwahu West Mun. akyem, ndc (0, .956) kwahu, npp (.136, .726)
asante, ndc (0, .563)kwahu, ndc (0, .050)ewe, ndc (0, .512)
Kwahu South kwahu, ndc (0, .211) kwahu, npp (0, .463)ewe, ndc (0, .764)
Kwahu East kwahu, ndc (0, .195) kwahu, npp (0, .474)ewe, ndc (0, .708)
Kwahu North ewe, ndc (.239, 1) ewe, npp (0, .478)Atwima Mponua asante, ndc (0, .525) asante, npp (.242, 1)Amansie West asante, ndc (0, .120) asante, npp (.672, .872)Amansie Central asante, ndc (0, .131) asante, npp (.695, .837)Obuasi Mun. asante, ndc (0, .163) asante, npp (.109, .982)
fante, ndc (0, .638)Adansi North asante, ndc (0, .209) asante, npp (.083, .855)
fante, ndc (0, .848)Bekwai Mun. asante, ndc (0, .091) asante, npp (.662, .845)Bosome Freho asante, ndc (0, .215) asante, npp (.641, 1)Asante Akim South asante, ndc (0, .593)Asante Akim North Mun. asante, ndc (0, .269) asante, npp (.535, .950)Ejisu Juaben Mun. asante, ndc (0, .203) asante, npp (.584, .926)Bosumtwi asante, ndc (0, .162) asante, npp (.648, .929)Atwima Kwanwoma asante, ndc (0, .134) asante, npp (.644, .939)Kumasi Metro. asante, ndc (0, .294) asante, npp (.368, 1)Atwima Nwabiagya asante, ndc (0, .213) asnate, npp (.583, 1)Ahafo Ano South asante, ndc (0, .638) asante, npp (.140, 1)Ahafo Ano North asante, ndc (0, .905)Offinso Mun. asante, ndc (0, .478) asante, npp (.062, .809)Afigya Kwabre asante, ndc (0, .254) asante, npp (.594, .985)Kwabre East asante, ndc (0, .204) asante, npp (.614, 1)Afigya Sekyere asante, ndc (0, .243) asante, npp (.617, .926)Mampong Mun. asante, ndc (0, .257) asante, npp (.550, 1)Sekyere East asante, ndc (0, .133) asante, npp (.389, .628)Sekyere Afram Plains asante, ndc (0, .268) asante, npp (.383, .907)Sekyere Central asante, ndc (0, .442) asante, npp (.258, .894)Asunafo South asante, npp (0, .963)Asunafo North Mun. asante, ndc (0, .927)Dormaa Mun. boron, ndc (.214, .527) boron, npp (.241, .554)Dormaa East boron, ndc (.188, .371) boron, npp (.385, .567)Sunyani Mun. boron, ndc (0, .618)Sunyani West boron, ndc (0, .445) boron, npp (.158, .705)
395
Table B-7. Continuedtribe (lower bound, upper bound)
District NDC NPPBerekum Mun. boron, ndc (.190, .402) boron, npp (.390, .601)Jaman South boron, ndc (.192, .341) boron, npp (.355, .503)Jaman North boron, ndc (.298, .442) boron, npp (.239, .383)Tain boron, ndc (.168, .481) boron, npp (.197, .510)Wenchi Mun. boron, npp (0, .929)
Techiman Mun. boron, ndc (0, .820) boron, npp (0, .722)Nkoranza South boron, ndc (0, .727) boron, npp (.003, .827)Nkoranza North boron, npp (0, .367)Sene guan8, npp (0, .982)Kintampo South boron, npp (0, .941)Kintampo North Mun. guan5, npp (0, .914)Bole dagarte, npp (0, .824)Sawla-Tuna-Kalba dagarte, ndc (0, .822) dagarte, npp (0, .271)
other grusi1, npp (0, .470)West Gonja guan5, ndc (0, .931) guan5, npp (0, .954)Gonja Central guan5, ndc (.036, .632) guan5, npp (0, .555)East Gonja guan5, ndc (0, .649) guan5, npp (0 .728)Kpandai kokomba, ndc (0, .582) kokomba, npp (0, .364)Nanumba South kokomba, ndc (.003, .584) kokomba, npp (.039, .621)Nanumba North kokomba, ndc (.104, .711) kokomba, npp (0, .574)Zabzugu Tatali kokomba, ndc (0, .868) kokomba, npp (0, .816)Yendi Mun. kokomba, ndc (0, .942) dagomba, npp (0, .654)
dagomba, ndc (0, .546)Tamale Metro. dagomba, ndc (.505, .760) dagomba, npp (.063, .318)Tolon Kumbugu dagomba, ndc (.588, .626) dagomba, npp (.239, 277)Savelugu Nanton dagomba, ndc (.547, .640) dagomba, npp (.253, .346)Karaga dagomba, ndc (.441, .722) dagomba, npp (.117, .398)Gushiegu dagomba, ndc (.031, .707) kokomba, npp (.114, .790)Saboba kokomba, ndc (.290, .393) kokomba, npp (.417, .520)
chokosi, ndc (.011, .501)Chereponi chokosi, ndc (0, .431) chokosi, npp (0, .455)
bimoba, ndc (0, .738)Bunkpurugu Yonyo bimoba, ndc (0, .326) bimoba, npp (0, .348)
kokomba, ndc (0, .596) kokomba, npp (0, .637)Mamprusi East mamprusi, ndc (0, .579) mamprusi, npp (0, .582)Mamprusi West mamprusi, ndc (.124, .401) mamprusi, npp (.068, .345)Builsa builsa, ndc (.219, .346) builsa, npp (.175, .302)
kasena, npp (0, .362)Kasena Nankana West kasena, ndc (0, .589) nankansi, npp (0, .755)
kasena, npp (0 .311)
396
Table B-7. Continuedtribe (lower bound, upper bound)
District NDC NPPKasena Nankana East nankansi, ndc (0, .384) nankansi, npp (0, .771)
kasena, ndc (0, .519)Bolgatanga Mun. nankansi, ndc (.044, .353) nankansi, npp (0, .244)Talensi Nabdam nankansi, ndc (.006, .552) nankansi, npp (0, .320)
namnam, npp (0, .632)
Bongo nankansi, ndc (.475, .502) nankansi, npp (.270, .297)Bawku West kusasi, ndc (.081, .381) kusasi, npp (.011, .311)Garu Tempane kusasi, ndc (0, .868) kusasi, npp (0, .606)Bawku Mun. kusasi, ndc (0, .777) kusasi, npp (0, .442)Wa West dagarte, ndc (0, .890) dagarte, npp (0, .408)Wa Mun. dagarte, ndc (0, .798) dagarte, npp (0, .600)
wali, npp (0, .459)mosi, npp (0, .830)
Wa East sisala, ndc (.099, .252) dagarte, npp (0, .942)Sissala East sisala, ndc (.096, .248) dagarte, npp (0, .264)Nadowli dagarte, ndc (.253, .538) dagarte, npp (.104, .155)Jirapa dagarte, ndc (.513, .564) sisala, npp (0, .344)Sissala West sisala, ndc (0, .342) sisala, npp (0, .318)Lambussie Karni dagarte, ndc (0, .740) dagarte, npp (0, .514)
sisala, npp (0, .891)Lawra dagarte, npp (.444, .509)
397
Table B-8. District-Level Bounds of Votes by Tribe - 2008 Presidential
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .380) nzema, npp (0, .304)Ellembelle nzema, ndc (.138, .311) nzema, npp (.137, .310)Nzema East evalue, ndc (0, .769)
nzema, ndc (0, .890)Ahanta West ahanta, ndc (0, .319) ahanta, npp (0, .609)Sekondi Takoradi Metro. fante, ndc (0, .470) fante, npp (0, .813)Shama fante, ndc (.185, .409) fante, npp (.184, .408)Mpohor-Wassa East wasa, ndc (0, .864) wasa, npp (0, .893)
fante, ndc (0, .983)Tarkwa Nsuaem Mun. wasa, ndc (0, .693)Wassa Amenfi East wasa, ndc (0, .640) wasa, npp (0, .781)Wassa Amenfi West wasa, ndc (0, .974) wasa, npp (0, .702)Aowin/Suaman aowin, npp (0, .723)Sefwi Akontombra sefwi, npp (0, .875)Sefwi Wiawso sefwi, ndc (.042, .714) sefwi, npp (0, .520)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.124, .534) sefwi, npp (.144, .555)Juabeso sefwi, ndc (0, .918) sefwi, npp (0, .394)Bia sefwi, npp (0, .747)KEEA fante, ndc (.302, .412) fante, npp (.171, .281)Cape Coast Metro. fante, ndc (.074, .535) fante, npp (0, .451)Abura-Asebu-Kwamankese fante, ndc (.350, .428) fante, npp (.190, .268)Mfantsiman Mun. fante, ndc (.352, .453) fante, npp (.182, .283)Ajumako-Enyan-Essiam fante, ndc (.330, .366) fante, npp (.300, .336)Gomoa West fante, ndc (.312, .357) fante, npp (.208, .253)Effutu Mun. guan3, ndc (0, .656) guan3, npp (0, .588)Gomoa East fante, ndc (.033, .539) fante, npp (0, .378)Ewutu Senya guan3, ndc (0, .966) guan3, npp (0, .923)Agona East fante, ndc (0, .773) fante, npp (0, .704)Agona West Mun. fante, ndc (0, .677) fante, npp (0, .794)
agona, ndc (0, .862)Asikuma-Odoben-Brakwa fante, ndc (.218, .380) fante, npp (.232, .394)Assin South asen, ndc (0, .619) asen, npp (0, .820)
fante, ndc (0, .916)Assin North Mun. asen, ndc (0, .976) fante, ndc (0, .959)Twifo-Heman-LowerDenkyira
fante, ndc (0, .901) fante, npp (0, .838)
Upper Denkyira East Mun. denkyira, ndc (0, .687)Upper Denkyira West denkyira, ndc (0, .556) denkyira, npp (0, .943)Adenta Mun. ewe, npp (0, .892)Ledzokuku/Krowor ga, ndc (0, .967) ga, npp (0, .779)
398
Table B-8. Continuedtribe (lower bound, upper bound)
District NDC NPPAshaiman ewe, npp (0, .664)Dangbe West dangme, ndc (.317, .792) dangme, npp (0, .176)
ewe, npp (0, .760)Dangbe East dangme, ndc (.450, .665) dangme, npp (0, .146)South Tongu ewe, ndc (.653, .694) ewe, npp (.010, .050)Keta Mun. ewe, ndc (.670, .683) ewe, npp (.008, .021)Ketu South ewe, ndc (.561, .593) ewe, npp (0, .030)Ketu North ewe, ndc (.509, .527) ewe, npp (.128, .146)Akatsi ewe, ndc (.550, .564) ewe, npp (.032, .046)North Tongu ewe, ndc (.597, .638) ewe, npp (.028, .070)Adaklu Anyigbe ewe, ndc (.549, .679) ewe, npp (0, .044)
kotokoli, npp (0, .764)Ho Mun. ewe, ndc (.561, .659) ewe, npp (0, .054)South Dayi ewe, ndc (.525, .590) ewe, npp (0, .058)North Dayi ewe, ndc (.533, .608) ewe, npp (0, .069)Hohoe Mun. ewe, ndc (.394, .731) ewe, npp (0, .093)
guan1, npp (0, .649)Biakoye ewe, npp (0, .391)guan6, npp (0, .932)Jasikan ewe, npp (0, .321)guan1, npp (0, .422)Kadjebi ewe, ndc (0, .946) ewe, npp (0, .439)
kotokoli, npp (0, .928)Krachi East ewe, npp (0, .688)Krachi West guan7, npp (0, .719)kokomba, npp (0, .582)Nkwanta South kokomba, npp (0, .680)Nkwanta North kokomba, ndc (.147, .466) kokomba, npp (.123, .443)Birim South akyem, ndc (0, .362) akyem, npp (.179, .770)Birim Mun. akyem, ndc (0, .490) akyem, npp (0, .974)
fante, ndc (0, .919)Akwapem South Mun. akuapem, ndc (0, .724) akuapem, npp (0, .952)Akwapem North akuapem, ndc (0, .707)
guan4, ndc (0, .785)New Juaben Mun. asante, ndc (0, .921)Yilo Krobo dangme, ndc (.287, .510) dangme, npp (.038, .261)Lower Manya dangme, ndc (.232, .601) dangme, npp (0, .309)Asuogyaman ewe, ndc (0, .779) ewe, npp (0, .673)Upper Manya dangme, ndc (.329, .504) dangme, npp (.031, .206)Fanteakwa akyem, ndc (0, .823)
dangme, ndc (0, .723)East Akim Mun. akyem, ndc (0, .465)
399
Table B-8. Continuedtribe (lower bound, upper bound)
District NDC NPPAkyem Mansa akyem, ndc (0, .488) akyem, npp (0, .894)Birim South akyem, ndc (0, .883)Atiwa akyem, ndc (0, .293) akyem, npp (.196, 1)Kwahu West Mun. kwahu, ndc (0, .294) kwahu, npp (.177, .767)Kwahu South kwahu, ndc (0, .318) kwahu, npp (.146, .670)Kwahu East kwahu, ndc (0, .282) kwahu, npp (.121, .679)Kwahu North ewe, ndc (0, .856) ewe, npp (0, .256)Atwima Mponua asante, ndc (0, .511) asante, npp (.015, .944)Amansie West asante, ndc (0, .129) asante, npp (.545, .744)Amansie Central asante, ndc (0, .097) asante, npp (.594, .736)Obuasi Mun. asante, ndc (0, .438) asante, npp (0, .870)Adansi North asante, ndc (0, .284) asante, npp (.210, .982)Bekwai Mun. asante, ndc (0, .106) asante, npp (.606, .789)Bosome Freho asante, ndc (0, .205) asante, npp (.452, .831)Asante Akim South asante, ndc (0, .516)Asante Akim North Mun. asante, ndc (0, .251) asante, npp (.354, .769)Ejisu Juaben Mun. asante, ndc (0, .182) asante, npp (.495, .837)Bosumtwi asante, ndc (0, .179) asante, npp (.507, .787)Atwima Kwanwoma asante, ndc (0, .150) asante, npp (.535, .830)Kumasi Metro. asante, ndc (0, .304) asante, npp (.179, .844)Atwima Nwabiagya asante, ndc (0, .215) asante, npp (.394, .813)Ahafo Ano South asante, ndc (0, .556) asante, npp (0, .908)Ahafo Ano North asante, ndc (0, .769) asante, npp (0, .914)Offinso Mun. asante, ndc (0, .378) asante, npp (.132, .879)Afigya Kwabre asante, ndc (0, .259) asante, npp (.400, .791)Kwabre East asante, ndc (0, .185) asante, npp (.436, .827)Afigya Sekyere asante, ndc (0, .212) asante, npp (.468, .776)Mampong Mun. asante, ndc (0, .241) asante, npp (.364, .889)Sekyere East asante, ndc (0, .175) asante, npp (.511, .750)Sekyere Afram Plains asante, ndc (0, .256) asante, npp (.292, .816)Sekyere Central asante, ndc (0, .329) asante, npp (.193, .829)Offinso North asante, ndc (0, .677) asante, npp (0, .901)Asunafo South asante, ndc (0, .891) asante, npp (0, .914)Asunafo North Mun. asante, ndc (0, .782) asante, npp (0, .975)Asutifi asante, ndc (0, .951)Dormaa Mun. boron, ndc (.107, .420) boron, npp (.145, .458)Dormaa East boron, ndc (.098, .281) boron, npp (.305, .487)Tano South asante, ndc (0, .961)Sunyani Mun. boron, ndc (0, .568) boron, npp (0, .930)Sunyani West boron, ndc (0, .442) boron, npp (.092, .639)Berekum Mun. boron, ndc (.137, .349) boron, npp (.226, .438)Jaman South boron, ndc (.143, .291) boron, npp (.266, .415)
400
Table B-8. Continuedtribe (lower bound, upper bound)
District NDC NPPJaman North boron, ndc (.254, .398) boron, npp (.130, .274)Tain boron, ndc (.082, .395) boron, npp (.051, .364)Wenchi Mun. boron, ndc (0, .586) boron, npp (0, .732)
dagarte, ndc (0, .878)Techiman Mun. boron, ndc (0, .683) boron, npp (0, .648)Nkoranza South boron, ndc (0, .665) boron, npp (0, .624)Nkoranza North boron, ndc (0, .472) boron, npp (0, .538)Sene ewe, npp (0, .961)
guan8, npp (0, .732)Pru kokomba, npp (0, .859)Kintampo South boron, npp (0, .880)Bole guan5, npp (0, .656)
dagarte, npp (0, .530)Sawla-Tuna-Kalba dagarte, ndc (0, .721) dagarte, npp (0, .358)
othergrusi1, npp (0, .622)West Gonja guan5, ndc (0, .843) guan5, npp (0, .683)Gonja Central guan5, ndc (0, .543) guan5, npp (0, .460)East Gonja guan5, ndc (0, .857) guan5, npp (0, .697)Kpandai kokomba, ndc (0, .627) kokomba, npp (0, .454)Nanumba South kokomba, ndc (0, .536) kokomba, npp (0, .571)Nanumba North kokomba, ndc (0, .428) kokomba, npp (.165, .773)
nanumba, ndc (0, .836)Zabzugu Tatali kokomba, ndc (0, .598) kokomba, npp (0, .798)Yendi Mun. dagomba, ndc (0, .582) dagomba, npp (0, .583)Tamale Metro. dagomba, ndc (.409, .664) dagomba, npp (0, .229)Tolon Kumbugu dagomba, ndc (.422, .460) dagomba, npp (.227, .265)Savelugu Nanton dagomba, ndc (.397, .490) dagomba, npp (.224, .317)Karaga dagomba, ndc (.260, .541) dagomba, npp (.071, .352)Gushiegu dagomba, ndc (0, .669) dagomba, npp (0, .593)Saboba kokomba, ndc (.330, .432) kokomba, npp (.270, .372)Chereponi chokosi, ndc (0, .485) chokosi, npp (.067, .556)Bunkpurugu Yonyo bimoba, ndc (.050, .831) bimoba, npp (0, .295)
kokomba, npp (0, .540)Mamprusi East mamprusi, ndc (0, .791) mamprusi, npp (0, .455)Mamprusi West mamprusi, ndc (.162, .439) mamprusi, npp (.090, .367)Builsa builsa, ndc (.301, .428) builsa, npp (.116, .243)Kasena Nankana West kasena, ndc (.024, .632) kasena, npp (0, .351)
nankansi, npp (0, .853)Kasena Nankana East nankansi, ndc (0, .780) nankansi, npp (0, .761)Bolgatanga Mun. nankansi, ndc (.244, .552) nankansi, npp (0, .242)
401
Table B-8. Continuedtribe (lower bound, upper bound)
District NDC NPPTalensi Nabdam nankansi, ndc (.004, .549) nankansi, npp (0, .370)
namnam, npp (0, .731)Bongo nankansi, ndc (.393, .420) nankansi, npp (.208, .235)Bawku West kusasi, ndc (.249, .549) kusasi, npp (0, .274)Garu Tempane kusasi, ndc (0, .764) kusasi, npp (0, .493)
bimoba, npp (0, .924)Bawku Mun. kusasi, ndc (0, .673) kusasi, npp (0, .517)Wa West dagarte, ndc (0, .791) dagarte, npp (0, .310)
othergrusi1, npp (0, .906)Wa Mun. wali, npp (0, .882)Wa East dagarte, ndc (0, .728) dagarte, npp (0, .767)Sissala East sisala, ndc (.144, .296) sisala, npp (.198, .351)Nadowli dagarte, ndc (.233, .518) dagarte, npp (0, .230)Jirapa dagarte, ndc (.345, .396) dagarte, npp (.151, .202)Sissala West sisala, ndc (.044, .433) sisala, npp (0, .351)Lambussie Karni dagarte, ndc (0, .535) dagarte, npp (0, .552)
sisala, ndc (0, .927) sisala, npp (0, .956)Lawra dagarte, ndc (.286, .351) dagarte, npp (.222, .287)
402
Table B-9. District-Level Bounds of Votes by Tribe - 2008 Parliamentary
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .324) nzema, npp (0, .154)
fante, npp (0, .597)Ellembelle nzema, ndc (.168, .341)Nzema East evalue, ndc (0, .629)
nzema, ndc (0, .728)Ahanta West ahanta, ndc (0, .274) ahanta, npp (0, .609)
fante, ndc (0, .996)Sekondi Takoradi Metro. fante, ndc (0, .415) fante, npp (0, .746)Shama fante, ndc (.191, .416) fante, npp (.168, .392)Mpohor-Wassa East fante, ndc (0, .828) fante, npp (0, .914)
wasa, ndc (0, .728) wasa, npp (0, .804)Tarkwa Nsuaem Mun. wasa, ndc (0, .708)Prestea/Huni Valley wasa, npp (0, .784)Wassa Amenfi East wasa, ndc (0, .949) wasa, npp (0, .772)Wassa Amenfi West wasa, ndc (0, .869) wasa, npp (0, .663)Aowin/Suaman aowin, ndc (0, .954) aowin, npp (0, .772)Sefwi Akontombra sefwi, npp (0, .932)Sefwi Wiawso sefwi, ndc (0, .647) sefwi, npp (0, .635)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.096, .507) sefwi, npp (.148, .558)Juabeso sefwi, ndc (0, .914) sefwi, npp (0, .390)Bia sefwi, npp (0, .795)KEEA fante, ndc (.268, .378) fante, npp (.210, .320)Cape Coast Metro. fante, ndc (.084, .545) fante, npp (0, .443)Abura-Asebu-Kwamankese fante, ndc (.327, .405) fante, npp (.193, .271)Mfantsiman Mun. fante, ndc (.290, .392) fante, npp (.238, .339)Ajumako-Enyan-Essiam fante, ndc (.336, .372) fante, npp (.277, .314)Gomoa West fante, ndc (.264, .308) fante, npp (.200, .241)Effutu Mun. guan3, ndc (0, .692) guan3, npp (0, .551)Gomoa East fante, ndc (.007, .513) fante, npp (0, .361)Ewutu Senya guan3, ndc (0, .964) guan3, npp (0, .876)
fante, npp (0, .990)Agona East fante, ndc (0, .759) fante, npp (0, .761)Agona West Mun. fante, ndc (0, .677) fante, npp (0, .650)
agona, ndc (0, .551)Asikuma-Odoben-Brakwa fante, ndc (.227, .389) fante, npp (.235, .398)Assin South asen, ndc (0, .663) asen, npp (0, .784)
fante, ndc (0, .980)Assin North Mun. asen, ndc (0, .909)
fante, ndc (0, .893)Twifo-Heman-LowerDenkyira
fante, ndc (0, .901) fante, npp (0, .782)
403
Table B-9. Continuedtribe (lower bound, upper bound)
District NDC NPPUpper Denkyira East Mun. asante, ndc (0, .873)
denkyira, ndc (0, .415)fante, ndc (0, .947)
Upper Denkyira West denkyira, ndc (0, .618) denkyira, npp (0, .825)Adenta Mun. ewe, npp (0, .878)Ledzokuku/Krowor ga, ndc (0, .976) ga, npp (0, .723)Ashaiman ewe, npp (0, .701)Dangbe West dangme, ndc (.235, .709) dangme, npp (0, .240)Dangbe East dangme, ndc (.400, .614) dangme, npp (0, .214)South Tongu ewe, ndc (.612, .653) ewe, npp (.022, .062)Keta Mun. ewe, ndc (.630, .643) ewe, npp (.019, .032)Ketu South ewe, ndc (.543, .575) ewe, npp (.004, .036)Ketu North ewe, ndc (.444, .462) ewe, npp (.191, .209)Akatsi ewe, ndc (.422, .436) ewe, npp (.022, .036)North Tongu ewe, ndc (.513, .555) ewe, npp (.074, .115)Adaklu Anyigbe ewe, ndc (.291, .421) ewe, npp (0, .024)
kotokoli, npp (0, .410)Ho Mun. ewe, ndc (.526, .624) ewe, npp (0, .082)South Dayi ewe, ndc (.512, .577) ewe, npp (0, .058)North Dayi ewe, ndc (.457, .532) ewe, npp (.050, .124)Hohoe Mun. ewe, ndc (.321, .658) ewe, npp (0, .137)
guan1, npp (0, .955)Biakoye ewe, npp (0, .450)Jasikan ewe, ndc (0, .936) ewe, npp (0, .391)
guan1, npp (0, .515)Kadjebi ewe, ndc (0, .814) ewe, npp (0, .474)Krachi East ewe, ndc (0, .999) ewe, npp (0, .669)Krachi West guan7, ndc (0, .975) guan7, npp (0, .715)
kokomba, ndc (0, .789) kokomba, npp (0, .578)
Nkwanta South kokomba, npp (0, .702)Nkwanta North kokomba, ndc (0, .146) kokomba, npp (.106, .425)Birim South akyem, ndc (0, .417) akyem, npp (.152, .743)Birim Mun. akyem, ndc (0, .539) akyem, npp (0, .932)Suhum-Kraboa-Coaltar akuapem, ndc (0, .993)Akwapem South Mun. akuapem, ndc (0, .623)Akwapem North akuapem, ndc (0, .658)
guan4, ndc (0, .731)New Juaben Mun. asante, ndc (0, .824)Yilo Krobo dangme, ndc (.200, .422) dangme, npp (.091, .314)Lower Manya dangme, ndc (.154, .524) dangme, npp (.031, .401)Asuogyaman ewe, ndc (0, .745) ewe, npp (0, .694)
404
Table B-9. Continuedtribe (lower bound, upper bound)
District NDC NPPUpper Manya dangme, ndc (.308, .483) dangme, npp (.047, .223)Fanteakwa dangme, ndc (0, .737) dangme, npp (0, .999)
akyem, ndc (0, .839)East Akim Mun. akyem, ndc (0, .470)Akyem Mansa akyem, ndc (0, .459) akyem, npp (0, .788)
fante, ndc (0, .945)Birim North akyem, ndc (0, .859)Atiwa akyem, ndc (0, .309) akyem, npp (.187, 1)Kwahu West Mun. kwahu, ndc (0, .059) kwahu, npp (0, .434)
asante, ndc (0, .667)ewe, ndc (0, .606)
Kwahu South kwahu, ndc (0, .302) kwahu, npp (.172, .696)Kwahu East kwahu, ndc (0, .279) kwahu, npp (.121, .679)Kwahu North ewe, ndc (0, .801) ewe, npp (0, .336)Atwima Mponua asante, ndc (0, .470) asante, npp (0, .827)Amansie West asante, ndc (0, .125) asante, npp (.450, .649)Amansie Central asante, ndc (0, .097) asante, npp (.566, .708)Obuasi Mun. asante, ndc (0, .463) asante, npp (0, .836)Adansi North asante, ndc (0, .269) asante, npp (.153, .925)Bekwai Mun. asante, ndc (0, .036) asante, npp (0, .176)Bosome Freho asante, ndc (0, .121) asante, npp (.065, .444)Asante Akim South asante, ndc (0, .558) asante, npp (0, .961)Asante Akim NorthMunicipal
asante, ndc (0, .185) asante, npp (.280, .695)
Ejisu Juaben Mun. asante, ndc (0, .157) asante, npp (.505, .847)Bosumtwi asante, ndc (0, .273) asante, npp (.410, .690)Atwima Kwanwoma asante, ndc (0, .147) asante, npp (.511, .806)Kumasi Metro. asante, ndc (0, .266) asante, npp (.146, .811)Atwima Nwabiagya asante, ndc (0, .178) asante, npp (.248, .667)Ahafo Ano South asante, ndc (0, .598) asante, npp (0, .861)Ahafo Ano North asante, ndc (0, .804) asante, npp (0, .881)Offinso Mun. asante, ndc (0, .430) asante, npp (.083, .830)Afigya Kwabre asante, ndc (0, .247) asante, npp (.400, .789)Kwabre East asante, ndc (0, .126) asante, npp (.412, .802)Afigya Sekyere asante, ndc (0, .216) asante, npp (.450, .759)Mampong Mun. asante, ndc (0, .224) asante, npp (.375, .900)Sekyere East asante, ndc (0, .179) asante, npp (.518, .757)Sekyere Afram Plains asante, ndc (0, .172) asante, npp (.089, .613)Sekyere Central asante, ndc (0, .119) asante, npp (0, .599)
kokomba, ndc (0, .756)Offinso North asante, ndc (0, .657) asante, npp (0, .846)
405
Table B-9. Continuedtribe (lower bound, upper bound)
District NDC NPPAsunafo South asante, ndc (0, .898) asante, npp (0, .935)Asunafo North Mun. asante, ndc (0, .829) asante, npp (0, .951)Dormaa Mun. boron, ndc (.123, .436) boron, npp (.141, .454)Dormaa East boron, ndc (.083, .266) boron, npp (.283, .466)Tano South asante, ndc (0, .990)Sunyani Mun. boron, ndc (0, .533) boron, npp (0, .956)Sunyani West boron, ndc (0, .399) boron, npp (.127, .674)Berekum Mun. boron, ndc (.154, .365) boron, npp (.200, .412)Jaman South boron, ndc (.010, .248) boron, npp (.255, .404)Jaman North boron, ndc (.247, .391) boron, npp (.160, .304)Tain boron, ndc (.052, .365) boron, npp (0, .294)Wenchi Mun. boron, ndc (0, .560) boron, npp (0, .768)
dagarte, ndc (0, .838)Techiman Mun. boron, ndc (0, .665) boron, npp (0, .671)Nkoranza South boron, ndc (0, .626) boron, npp (0, .688)Nkoranza North boron, ndc (0, .475) boron, npp (0, .540)Atebubu Amantin boron, npp (0, .955)Sene ewe, npp (0, .961)guan8, npp (0, .966)Pru kokomba, ndc (0, .998) kokomba, npp (0, .686)Kintampo South boron, npp (0, .887)Bole guan5, npp (0, .742)
dagarte, npp (0, .600)Sawla-Tuna-Kalba dagarte, ndc (0, .646) dagarte, npp (0, .424)
othergrusi1, npp (0, .737)West Gonja guan5, ndc (0, .813) guan5, npp (0, .653)Gonja Central guan5, ndc (0, .503) guan5, npp (0, .497)East Gonja guan5, ndc (0, .857) guan5, npp (0, .732)Kpandai kokomba, ndc (0, .431) kokomba, npp (0, .454)Nanumba South kokomba, ndc (0, .362) kokomba, npp (0, .371)
nanumba, ndc (0, .833) nanumba, npp (0, .854)Nanumba North kokomba, ndc (0, .457) kokomba, npp (.169, .777)
nanumba, ndc (0, .894)Zabzugu Tatali kokomba, ndc (0, .500) kokomba, npp (0, .836)Yendi Mun. dagomba, ndc (0, .494) dagomba, npp (0, .473)
kokomba, ndc (0, .854) kokomba, npp (0, .818)Tamale Metro. dagomba, ndc (.358, .613)Tolon Kumbugu dagomba, ndc (.403, .441) dagomba, npp (.245, .284)Savelugu Nanton dagomba, ndc (.350, .443) dagomba, npp (.241, .333)Karaga dagomba, ndc (.253, .534) dagomba, npp (.092, .373)Gushiegu dagomba, ndc (0, .650) dagomba, npp (0, .620)
406
Table B-9. Continuedtribe (lower bound, upper bound)
District NDC NPPSaboba kokomba, ndc (.329, .431) kokomba, npp (.271, .373)Chereponi chokosi, ndc (0, .490) chokosi, npp (.099, .588)Bunkpurugu Yonyo bimoba, ndc (0, .373) bimoba, npp (0, .275)
kokomba, ndc (0, .682) kokomba, npp (0, .504)Mamprusi East mamprusi, ndc (0, .644) mamprusi, npp (0, .477)Mamprusi West mamprusi, ndc (.141, .418) mamprusi, npp (.093, .370)Builsa builsa, ndc (.202, .329) builsa, npp (.140, .267)Kasena Nankana West kasena, ndc (0, .313) kasena, npp (0, .353)
nankansi, ndc (0, .761) nankansi, npp (0, .858)Kasena Nankana East nankansi, ndc (0, .726) nankansi, npp (0, .788)
kasena, ndc (0, .980)Bolgatanga Mun. nankansi, ndc (.203, .512) nankansi, npp (0, .180)Talensi Nabdam nankansi, ndc (0, .484) nankansi, npp (0, .409)
namnam, npp (0, .807)Bongo nankansi, ndc (.379, .406) nankansi, npp (.206, .233)Bawku West kusasi, ndc (.084, .384) kusasi, npp (.007, .308)Garu Tempane kusasi, ndc (0, .640) kusasi, npp (0, .614)
bimoba, npp (0, .924)Bawku Mun. kusasi, ndc (0, .585) kusasi, npp (0, .581)Wa West dagarte, ndc (0, .595) dagarte, npp (0, .253)
wali, npp (0, .823)othergrusi1, npp (0, .739)
Wa Mun. wali, npp (0, .880)Wa East dagarte, ndc (0, .664) dagarte, npp (0, .739)Sissala East sisala, ndc (.147, .300) sisala, npp (.066, .218)Nadowli dagarte, ndc (.185, .470) dagarte, npp (0, .221)Jirapa dagarte, ndc (.342, .392) dagarte, npp (.162, .213)Sissala West sisala, ndc (0, .331) sisala, npp (0, .273)
dagarte, npp (0, .884)Lambussie Karni dagarte, ndc (0, .468) dagarte, npp (0, .646)
sisala, ndc (0, .811)Lawra dagarte, ndc (.241, .306) dagarte, npp (.262, .327)
407
Table B-10. District-Level Bounds of Votes by Tribe - 2008 Presidential Runoff
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .481) nzema, npp (0, .405)Ellembelle nzema, ndc (.184, .357) nzema, npp (.160, .333)Nzema East evalue, ndc (0, .919)Ahanta West ahanta, ndc (0, .372) ahanta, npp (.024, .654)Sekondi Takoradi Metro. fante, ndc (0, .552) fante, npp (0, .865)Shama fante, ndc (.221, .445) fante, npp (.188, .412)Mpohor-Wassa East wasa, ndc (0, .986) wasa, npp (0, .927)Tarkwa Nsuaem Mun. wasa, ndc (0, .775)Wassa Amenfi East wasa, ndc (0, .678) wasa, npp (0, .815)Wassa Amenfi West wasa, npp (0, .668)Aowin/Suaman aowin, npp (0, .661)Sefwi Akontombra sefwi, npp (0, .782)Sefwi Wiawso sefwi, ndc (.100, .772) sefwi, npp (0, .450)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.153, .564) sefwi, npp (.152, .563)Juabeso sefwi, npp (0, .358)Bia sefwi, npp (0, .697)KEEA fante, ndc (.366, .476) fante, npp (.191, .301)Cape Coast Metro. fante, ndc (.101, .562) fante, npp (0, .444)Abura-Asebu-Kwamankese fante, ndc (.379, .457) fante, npp (.215, .293)Mfantsiman fante, ndc (.373, .474) fante, npp (.191, .292)Ajumako-Enyan-Essiam fante, ndc (.348, .384) fante, npp (.301, .338)Gomoa West fante, ndc (.347, .391) fante, npp (.219, .264)Effutu Mun. guan3, ndc (0, .669) guan3, npp (0, .553)Gomoa East fante, ndc (.069, .576) fante, npp (0, .392)Agona East fante, ndc (0, .798) fante, npp (0, .740)Agona West Mun. fante, ndc (0, .758) fante, npp (0, .794)
agona, ndc (0, .965)Asikuma-Odoben-Brakwa fante, ndc (.237, .399) fante, npp (.247, .409)Assin South asen, ndc (0, .657) asen, npp (0, .866)
fante, ndc (0, .971)Twifo-Heman-LowerDenkyira
fante, ndc (0, .996) fante, npp (0, .823)
Upper Denkyira East Mun. denkyira, ndc (0, .809)Upper Denkyira West denkyira, ndc (0, .630) denkyira, npp (0, .962)Adenta Mun. ewe, npp (0, .932)Ledzokuku/Krowor Mun. ga, npp (0, .785)Ashaiman Mun. ewe, npp (0, .683)Dangbe West dangme, ndc (.376, .850) dangme, npp (0, .168)
ewe, npp (0, .725)Dangbe East dangme, ndc (.482, .696) dangme, npp (0, .149)South Tongu ewe, ndc (.703, .743) ewe, npp (.026, .066)
408
Table B-10. Continuedtribe (lower bound, upper bound)
District NDC NPPKeta Mun. ewe, ndc (.783, .796) ewe, npp (.014, .027)Ketu South ewe, ndc (.688, .720) ewe, npp (.004, .036)Ketu North ewe, ndc (.578, .596) ewe, npp (.104, .122)Akatsi ewe, ndc (.679, .693) ewe, npp (.035, .049)North Tongu ewe, ndc (.708, .749) ewe, npp (.042, .084)Adaklu Anyigbe ewe, ndc (.723, .853) ewe, npp (0, .059)Ho Mun. ewe, ndc (.656, .754) ewe, npp (0, .058)South Dayi ewe, ndc (.604, .669) ewe, npp (0, .060)North Dayi ewe, ndc (.591, .665) ewe, npp (0, .072)Hohoe Mun. ewe, ndc (.506, .843) ewe, npp (0, .099)
guan1, npp (0, .690)Biakoye ewe, npp (0, .398)guan6, npp (0, .948)Jasikan ewe, npp (0, .294)guan1, npp (0, .387)Kadjebi ewe, ndc (0, .996) ewe, npp (0, .401)
kotokoli, npp (0, .848)Krachi East ewe, npp (0, .679)Krachi West guan7, npp (0, .799)kokomba, npp (0, .646)Nkwanta South kokomba, npp (0, .653)Nkwanta North kokomba, ndc (.176, .495) kokomba, npp (.109, .428)Birim South akyem, ndc (0, .395) akyem, npp (.228, .819)Birim Mun. akyem, ndc (0, .527) fante, ndc (0, .989)Akwapem South Mun. akuapem, ndc (0, .764) akuapem, npp (0, .956)Akwapem North akuapem, ndc (0, .748)
guan4, ndc (0, .831)New Juaben Mun. asante, ndc (0, .981)Yilo Krobo dangme, ndc (.349, .572) dangme, npp (.015, .238)Lower Manya dangme, ndc (.253, .623) dangme, npp (0, .277)Asuogyaman ewe, ndc (0, .836) ewe, npp (0, .686)Upper Manya dangme, ndc (.367, .542) dangme, npp (.005, .181)Fanteakwa akyem, ndc (0, .852)
dangme, ndc (0, .748)East Akim Mun. akyem, ndc (0, .473) akyem, npp (.046, 1)Kwaebibirem akyem, ndc (0, .648)Akyem Mansa akyem, ndc (0, .549) akyem, npp (0, .952)Birim North akyem, ndc (0, .933)Atiwa akyem, ndc (0, .308) akyem, npp (.317, 1)Kwahu West Mun. kwahu, ndc (0, .316) kwahu, npp (.225, .815)Kwahu South kwahu, ndc (0, .343) kwahu, npp (.194, .718)Kwahu East kwahu, ndc (0, .326) kwahu, npp (.166, .724)
409
Table B-10. Continuedtribe (lower bound, upper bound)
District NDC NPPKwahu North ewe, ndc (.098, .981) ewe, npp (0, .280)Atwima Mponua asante, ndc (0, .558) asante, npp (.081, 1)Amansie West asante, ndc (0, .143) asante, npp (.661, .860)Amansie Central asante, ndc (0, .112) asante, npp (.689, .831)Obuasi Mun. asante, ndc (0, .474) asante, npp (.051, .924)Adansi North asante, ndc (0, .314) asante, npp (.294, 1)Bekwai Mun. asante, ndc (0, .121) asante, npp (.715, .897)Bosome Freho asante, ndc (0, .223) asante, npp (.602, .982)Asante Akim South asante, ndc (0, .561)Asante Akim North Mun. asante, ndc (0, .280) asante, npp (.427, .842)Ejisu Juaben Mun. asante, ndc (0, .200) asante, npp (.622, .963)Bosumtwi asante, ndc (0, .191) asante, npp (.545, .826)Atwima Kwanwoma asante, ndc (0, .163) asante, npp (.680, .975)Kumasi Metro. asante, ndc (0, .332) asante, npp (.433, 1)Atwima Nwabiagya asante, ndc (0, .236) asante, npp (.487, .906)Ahafo Ano South asante, ndc (0, .614)Ahafo Ano North asante, ndc (0, .813) asante, npp (0, . 957)Offinso Mun. asante, ndc (0, .409) asante, npp (.238, .985)Afigya Kwabre asante, ndc (0, .286) asante, npp (.510, .902)Kwabre East asante, ndc (0, .207) asante, npp (.560, .951)Afigya Sekyere asante, ndc (0, .221) asante, npp (.627, .935)Mampong Mun. asante, ndc (0, .266) asante, npp (.457, .982)Sekyere East asante, ndc (0, .205) asante, npp (.579, .818)Sekyere Afram Plains asante, ndc (0, .303) asante, npp (.418, .942)Sekyere Central asante, ndc (0, .360) asante, npp (.384, 1)Offinso North asante, ndc (0, .741)Asunafo South asante, ndc (0, .916) asante, npp (0, .924)Asunafo North Mun. asante, ndc (0, .833) asante, npp (0, .993)Dormaa Mun. boron, ndc (.128, .441) boron, npp (.165, .479)Dormaa East boron, ndc (.128, .311) boron, npp (.321, .503)Sunyani Mun. boron, ndc (0, .630) boron, npp (0, .958)Sunyani West boron, ndc (0, .476) boron, npp (.080, .627)Berekum Mun. boron, ndc (.159, .371) boron, npp (.231, .443)Jaman South boron, ndc (.165, .313) boron, npp (.285, .434)Jaman North boron, ndc (.269, .413) boron, npp (.108, .252)Tain boron, ndc (.164, .477) boron, npp (0, .050)
dagarte, npp (0, .232)Wenchi Mun. boron, ndc (0, .679) boron, npp (0, .766)Techiman Mun. boron, ndc (0, .740) boron, npp (0, .642)Nkoranza South boron, ndc (0, .718) boron, npp (0, .640)Nkoranza North boron, ndc (0, .515) boron, npp (0, .554)Atebubu Amantin boron, npp (0, .969)
410
Table B-10. Continuedtribe (lower bound, upper bound)
District NDC NPPSene ewe, npp (0, .961)
guan8, npp (0, .732)Pru kokomba, npp (0, .835)Kintampo South boron, npp (0, .882)Bole guan5, npp (0, .639)
dagarte, npp (0, .517)Sawla-Tuna-Kalba dagarte, ndc (0, .780) dagarte, npp (0, .324)
othergrusi1, npp (0, .563)West Gonja guan5, ndc (0, .981) guan5, npp (0, .695)Gonja Central guan5, ndc (0, .595) guan5, npp (0, .447)East Gonja guan5, ndc (0, .902) guan5, npp (0, .675)Kpandai kokomba, ndc (.058, .704) kokomba, npp (0, .452)Nanumba South kokomba, ndc (0, .513) kokomba, npp (.023, .605)Nanumba North kokomba, ndc (0, .466) kokomba, npp (.081, .688)
nanumba, ndc (0, .912)Zabzugu Tatali kokomba, ndc (0, .625) kokomba, npp (0, .793)Yendi Mun. dagomba, ndc (0, .631) dagomba, npp (0, .624)Tamale Metro. dagomba, ndc (.493, .748) dagomba, npp (0, .243)Tolon Kumbugu dagomba, ndc (.494, .532) dagomba, npp (.249, .287)Savelugu Nanton dagomba, ndc (.447, .540) dagomba, npp (.245, .338)Karaga dagomba, ndc (.294, .575) dagomba, npp (.077, .358)Gushiegu dagomba, ndc (.013, .689) dagomba, npp (0, .612)Saboba kokomba, ndc (.374, .477) kokomba, npp (.271, .373)Chereponi chokosi, ndc (0, .466) chokosi, npp (.128, .618)Bunkpurugu Yonyo bimoba, ndc (.209, .990) bimoba, npp (0, .313)
kokomba, npp (0, .572)Mamprusi East mamprusi, ndc (0, .994) mamprusi, npp (0, .479)Mamprusi West mamprusi, ndc (.246, .523) mamprusi, npp (.132, .409)Builsa builsa, ndc (.417, .544) builsa, npp (.101, .228)Kasena Nankana West kasena, ndc (.186, .794) kasena, npp (0, .355)
nankansi, npp (0, .861)Kasena Nankana East nankansi, ndc (0, .926) nankansi, npp (0, .774)Bolgatanga Mun. nankansi, ndc (.330, .638) nankansi, npp (0, .277)Talensi Nabdam nankansi, ndc (.137, .682) nankansi, npp (0, .350)
namnam, npp (0, .690)Bongo nankansi, ndc (.431, .458) nankansi, npp (.212, .239)Bawku West kusasi, ndc (.306, .607) kusasi, npp (0, .293)Garu Tempane kusasi, ndc (0, .846) kusasi, npp (0, .466)
bimoba, npp (0, .874)Bawku Mun. kusasi, ndc (0, .846) kusasi, npp (0, .481)Wa West dagarte, ndc (0, .824) dagarte, npp (0, .309)Wa Mun. wali, npp (0, .897)
411
Table B-10. Continuedtribe (lower bound, upper bound)
District NDC NPPWa East dagarte, ndc (0, .839) dagarte, npp (0, .777)Sissala East sisala, ndc (.195, .347) sisala, npp (.288, .440)Nadowli dagarte, ndc (.325, .610) dagarte, npp (0, .220)Jirapa dagarte, ndc (.418, .468) dagarte, npp (.116, .167)Sissala West sisala, ndc (.115, .503) sisala, npp (.061, .449)Lambussie Karni dagarte, ndc (0, .685) dagarte, npp (0, .438)
sisala, npp (0, .759)Lawra dagarte, ndc (.351, .416) dagarte, npp (.199, .264)
412
Table B-11. District-Level Bounds of Votes by Tribe - 2012 Presidential
tribe (lower bound, upper bound)District NDC NPPEllembelle nzema, ndc (.490, .731) nzema, npp (.269, .510)Shama fante, ndc (.386, .716) fante, npp (.284, .614)Sefwi Wiawso sefwi, ndc (.227, 1) sefwi, npp (0, .773)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.224, .751) sefwi, npp (.249, .776)KEEA fante, ndc (.550, .726) fante, npp (.274, .450)Cape Coast Metro. fante, ndc (.241, .909) fante, npp (.091, .759)Abura-Asebu-Kwamankese fante, ndc (.576, .686) fante, npp (.314, .424)Mfantsiman Mun. fante, ndc (.549, .687) fante, npp (.313, .451)Ajumako-Enyan-Essiam fante, ndc (.511, .560) fante, npp (.440, .489)Gomoa West fante, ndc (.580, .645) fante, npp (.355, .420)Gomoa East fante, ndc (.199, 1) fante, npp (0, .801)Asikuma-Odoben-Brakwa fante, ndc (.394, .621) fante, npp (.379, .606)Dangbe West dangme, ndc (.551, 1) dangme, npp (0, .449)Dangbe East dangme, ndc (.769, 1) dangme, npp (0, .231)South Tongu ewe, ndc (.936, .990) ewe, npp (.010, .064)Keta Mun. ewe, ndc (.962, .979) ewe, npp (.021, .038)Ketu South ewe, ndc (.938, .986) ewe, npp (.014, .062)Ketu North ewe, ndc (.875, .900) ewe, npp (.100, .125)Akatsi ewe, ndc (.924, .944) ewe, npp (.056, .076)North Tongu ewe, ndc (.916, .972) ewe, npp (.028, .084)Adaklu Anyigbe ewe, ndc (.917, .1) ewe, npp (0, .083)Ho Mun. ewe, ndc (.914, 1) ewe, npp (0, .086)South Dayi ewe, ndc (.913, 1) ewe, npp (0, .087)North Dayi ewe, ndc (.900, 1) ewe, npp (0, .100)Hohoe Mun. ewe, ndc (.848, 1) ewe, npp (0, .152)Biakoye ewe, npp (0, .354)Jasikan ewe, ndc (.056, 1) ewe, npp (0, .944)Kadjebi ewe, ndc (.014, 1) ewe, npp (0, .986)Nkwanta North kokomba, ndc (.500, .973) kokomba, npp (.027, .500)Birim South akyem, ndc (0, .621) akyem, npp (.379, 1)Akwapem North guan4, ndc (0, .944)Yilo Krobo dangme, ndc (.589, .903) dangme, npp (.097, .411)Lower Manya dangme, ndc (.495, 1) dangme, npp (0, .505)Upper Manya dangme, ndc (.589, .903) dangme, npp (.136, .398)Fanteakwa dangme, ndc (0, .813)East Akim Mun. akyem, ndc (0, .935) akyem, npp (.065, 1)Atiwa akyem, ndc (0, .588) akyem, npp (.412, 1)Kwahu West Mun. kwahu, ndc (0, .542) kwahu, npp (.458, 1)Kwahu South kwahu, ndc (0, .548) kwahu, npp (.452, 1)Kwahu East kwahu, ndc (0, .626) kwahu, npp (.374, 1)Kwahu North ewe, ndc (.314, 1) ewe, npp (0, .686)Amansie West asante, ndc (0, .242) asante, npp (.758, 1)
413
Table B-11. Continuedtribe (lower bound, upper bound)
District NDC NPPAmansie Central asante, ndc (.008, .184) asante, npp (.816, .992)Obuasi Mun. asante, ndc (0, .859) asante, npp (.141, 1)Adansi North asante, ndc (0, .574) asante, npp (.426, 1)Bekwai Mun. asante, ndc (0, .171) asante, npp (.829, 1)Bosome Freho asante, ndc (0, .384) asante, npp (.616, 1)Asante Akim North Mun. asante, ndc (0, .448) asante, npp (.552, 1)Ejisu Juaben Mun. asante, ndc (0, .293) asante, npp (.707, 1)Bosumtwi asante, ndc (0, .291) asante, npp (.709, 1)Atwima Kwanwoma asante, ndc (0, .244) asante, npp (.756, 1)Kumasi Metro. asante, ndc (0, .513) asante, npp (.487, 1)Atwima Nwabiagya asante, ndc (0, .349) asante, npp (.651, 1)Offinso Mun. asante, ndc (0, .731) asante, npp (.269, 1)Afigya Kwabre asante, ndc (0, .320) asante, npp (.680, 1)Kwabre East asante, ndc (0, .305) asante, npp (.695, 1)Afigya Sekyere asante, ndc (0, .327) asante, npp (.673, 1)Mampong Mun. asante, ndc (0, .430) asante, npp (.570, 1)Sekyere East asante, ndc (0, .279) asante, npp (.721, 1)Sekyere Afram Plains asante, ndc (0, .568) asante, npp (.432, 1)Sekyere Central asante, ndc (0, .646) asante, npp (.354, 1)Dormaa Mun. boron, ndc (.286, .719) boron, npp (.281, .714)Dormaa East boron, ndc (.252, .490) boron, npp (.510, .748)Sunyani West boron, ndc (.032, .798) boron, npp (.202, .968)Berekum Mun. boron, ndc (.258, .549) boron, npp (.451, .742)Jaman South boron, ndc (.311, .521) boron, npp (.479, .689)Jaman North boron, ndc (.494, .712) boron, npp (.288, .506)Tain boron, ndc (.337, .822) boron, npp (.178, .663)Gonja Central guan5, ndc (.173, 1) guan5, npp (0, .827)Kpandai kokomba, ndc (.200, 1) kokomba, npp (0, .780)Nanumba South kokomba, ndc (.151, 1) kokomba, npp (0, .849)Nanumba North kokomba, ndc (0, .856) kokomba, npp (.144, 1)Tamale Metro. dagomba, ndc (.643, 1) dagomba, npp (0, .357)Tolon Kumbugu dagomba, ndc (.605, .658) dagomba, npp (.342, .395)Savelugu Nanton dagomba, ndc (.547, .666) dagomba, npp (.334, .453)Karaga dagomba, ndc (.412, .816) dagomba, npp (.184, .588)Gushiegu dagomba, ndc (.014, 1) dagomba, ndc (0, .986)Saboba kokomba, ndc (.460, .583) kokomba, npp (.417, .540)Chereponi chokosi, ndc (.123, .813) chokosi, npp (.187, .877)Bunkpurugu Yonyo bimoba, ndc (.187, 1) bimoba, npp (0, .813)Mamprusi West mamprusi, ndc (.236, .648) mamprusi, npp (.352, .764)Builsa builsa, ndc (.698, .904) builsa, npp (.096, .302)
414
Table B-11. Continuedtribe (lower bound, upper bound)
District NDC NPPKasena Nankana West kasena, ndc (.553, 1) kasena, npp (0, .447)Bolgatanga Mun. nankansi, ndc (.654, 1) nankansi, npp (0, .346)Talensi Nabdam nankansi, ndc (.262, 1) nankansi, npp (0, .738)Bongo nankansi, ndc (.699, .741) nankansi, npp (.259, .301)Bawku West kusasi, ndc (.497, .959) kusasi, npp (.041, .503)Garu Tempane kusasi, ndc (0, .918)Sissala East sisala, ndc (.556, .791) sisala, npp (.209, .444)Nadowli dagarte, ndc (.600, 1) dagarte, npp (0, .400)Jirapa dagarte, ndc (.848, .926) dagarte, npp (.074, .152)Sissala West sisala, ndc (.413, 1) sisala, npp (0, .587)Lambussie Karni dagarte, ndc (.474, 1) dagarte, npp (0, .526)Lawra dagarte, ndc (.689, .773) dagarte, npp (.227, .311)
415
Table B-12. District-Level Bounds of Votes by Tribe - 2012 Parliamentary
tribe (lower bound, upper bound)District NDC NPPJomoro nzema, ndc (0, .951) nzema, npp (0, .423)Ellembelle nzema, ndc (.475, .707) nzema, npp (.253, .485)Ahanta West ahanta, ndc (0, .896)Shama fante, ndc (.318, .630) fante, npp (.275, .587)Sefwi Wiawso sefwi, ndc (.091, 1) sefwi, npp (0, .861)Sefwi Bibiani-Ahwiaso B. sefwi, ndc (.193, .698) sefwi, npp (.241, .746)Juabeso sefwi, npp (0, .740)KEEA fante, ndc (.120, .267) fante, npp (.276, .424)Cape Coast Metro. fante, ndc (.187, .824) fante, npp (.100, .737)Abura-Asebu-Kwamankese fante, ndc (.500, .603) fante, npp (.303, .406)Mfantsiman Mun. fante, ndc (.474, .604) fante, npp (.354, .485)Ajumako-Enyan-Essiam fante, ndc (.494, .540) fante, npp (.422, .468)Gomoa West fante, ndc (.529, .590) fante, npp (.351, .412)Gomoa East fante, ndc (.155, .963) fante, npp (0, .755)Asikuma-Odoben-Brakwa fante, ndc (.402, .618) fante, npp (.329, .545)Dangbe West dangme, ndc (.226, .956) dangme, npp (0, .587)Dangbe East dangme, ndc (.530, .813) dangme, npp (.020, .303)South Tongu ewe, ndc (.803, .856) ewe, npp (0, .051)Keta Mun. ewe, ndc (.856, .872) ewe, npp (.048, .064)Ketu South ewe, ndc (.867, .914) ewe, npp (.002, .048)Ketu North ewe, ndc (.746, .770) ewe, npp (.161, .186)Akatsi ewe, ndc (.680, .699) ewe, npp (.054, .072)North Tongu ewe, ndc (.858, .912) ewe, npp (.043, .096)Adaklu Anyigbe ewe, ndc (.778, .966) ewe, npp (0, .096)Ho Mun. ewe, ndc (.863, .995) ewe, npp (0, .105)South Dayi ewe, ndc (.582, .670) ewe, npp (0, .059)North Dayi ewe, ndc (.744, .846) ewe, npp (.034, .136)Hohoe Mun. ewe, ndc (.723, 1) ewe, npp (0, .200)Jasikan ewe, npp (0, .950)Kadjebi ewe, ndc (0, .912) ewe, npp (0, .684)Nkwanta North kokomba, ndc (.433, .870) kokomba, npp (.076, .512)Birim South akyem, ndc (0, .554) akyem, npp (.253, 1)Birim Mun. akyem, ndc (0, .840)Yilo Krobo dangme, ndc (.485, .786) dangme, npp (.128, .429)Lower Manya dangme, ndc (.252, .780) dangme, npp (0, .518)Upper Manya dangme, ndc (.482, .726) dangme, npp (.162, .406)East Akim Mun. akyem, ndc (0, .892) akyem, npp (.046, 1)Atiwa akyem, ndc (0, .589) akyem, npp (.371, 1)Kwahu West Mun. kwahu, ndc (0, .569) kwahu, npp (.394, 1)Kwahu South kwahu, ndc (0, .465) kwahu, npp (.421, 1)Kwahu East kwahu, ndc (0, .655) kwahu, npp (.320, 1)
416
Table B-12. Continuedtribe (lower bound, upper bound)
District NDC NPPKwahu North ewe, ndc (.034, 1) ewe, npp (0, .742)Atwima Mponua asante, ndc (0, .978)Amansie West asante, ndc (.007, .258) asante, npp (.689, .940)Amansie Central asante, ndc (.033, .203) asante, npp (.729, .899)Obuasi Mun. asante, ndc (0, .835) asante, npp (.089, 1)Adansi North asante, ndc (0, .644) asante, npp (.318, 1)Bekwai Mun. asante, ndc (0, .157) asante, npp (.810, 1)Bosome Freho asante, ndc (0, .323) asante, npp (.357, .845)Asante Akim North Mun. asante, ndc (0, .397) asante, npp (.325, .842)Ejisu Juaben Mun. asante, ndc (0, .281) asante, npp (.690, 1)Bosumtwi asante, ndc (.102, .438) asante, npp (.548, .883)Atwima Kwanwoma asante, ndc (0, .228) asante, npp (.688, 1)Kumasi Metro. asante, ndc (0, .468) asante, npp (.468, 1)Atwima Nwabiagya asante, ndc (0, .293) asante, npp (.502, 1)Ahafo Ano South asante, ndc (0, .989)Offinso Mun. asante, ndc (0, .637) asante, npp (.305, 1)Afigya Kwabre asante, ndc (0, .287) asante, npp (.647, 1)Kwabre East asante, ndc (0, .378) asante, npp (.541, 1)Afigya Sekyere asante, ndc (0, .332) asante, npp (.602, .970)Mampong Mun. asante, ndc (0, .415) asante, npp (.526, 1)Sekyere East asante, ndc (0, .275) asante, npp (.685, .967)Sekyere Afram Plains asante, ndc (0, .443) asante, npp (.260, .934)Sekyere Central asante, ndc (0, .659) asante, npp (.305, 1)Dormaa Mun. boron, ndc (.260, .671) boron, npp (.285, .696)Dormaa East boron, ndc (.269, .496) boron, npp (.460, .687)Sunyani West boron, ndc (.055, .788) boron, npp (.178, .919)Berekum Mun. boron, ndc (.236, .518) boron, npp (.439, .720)Jaman South boron, ndc (.286, .486) boron, npp (.488, .688)Jaman North boron, ndc (.381, .585) boron, npp (.389, .593)Tain boron, ndc (.328, .790) boron, npp (.156, .618)Nkoranza South boron, ndc (.010, 1) boron, npp (0, .943)Nkoranza North boron, ndc (0, .883) boron, npp (.006, .949)Gonja Central guan5, ndc (0, .909) guan5, npp (0, .873)Kpandai kokomba, ndc (0, .659) kokomba, npp (0, .775)Nanumba South kokomba, ndc (0, .705) kokomba, npp (0, .648)Nanumba North kokomba, ndc (0, .602) kokomba, npp (.178, 1)Zabzugu Tatali kokomba, ndc (0, .926) kokomba, npp (0, .989)Yendi Mun. dagomba, ndc (0, .620) dagomba, npp (0, .830)Tamale Metro. dagomba, ndc (.517, .862) dagomba, npp (0, .341)Tolon Kumbugu dagomba, ndc (.448, .496) dagomba, npp (.341, .389)Savelugu Nanton dagomba, ndc (.467, .578) dagomba, npp (.357, .469)
417
Table B-12. Continuedtribe (lower bound, upper bound)
District NDC NPPKaraga dagomba, ndc (.307, .667) dagomba, npp (.199, .559)Gushiegu dagomba, ndc (.032, .915) dagomba, ndc (.015, .899)Saboba kokomba, ndc (.440, .558) kokomba, npp (.412, .530)Chereponi chokosi, ndc (.112, .728) chokosi, npp (.189, .805)Bunkpurugu Yonyo bimoba, ndc (0, .998) bimoba, npp (0, .766)Mamprusi West mamprusi, ndc (.124, .493) mamprusi, npp (.237, .605)Builsa builsa, ndc (.339, .505) builsa, npp (.089, .256)Kasena Nankana West kasena, ndc (.227, 1) kasena, npp (0, .414)Bolgatanga Mun. nankansi, ndc (.407, .833) nankansi, npp (0, .382)Talensi Nabdam nankansi, ndc (0, .698) nankansi, npp (0, .824)Bongo nankansi, ndc (.500, .537) nankansi, npp (.283, .321)Bawku West kusasi, ndc (.321, .729) kusasi, npp (.160, .569)Garu Tempane kusasi, ndc (0, .918)Wa West dagarte, ndc (0, .926)Sissala East sisala, ndc (.228, .414) sisala, npp (.118, .304)Nadowli dagarte, ndc (.368, .746) dagarte, npp (.165, .543)Jirapa dagarte, ndc (.363, .430) dagarte, npp (.016, .083)Sissala West sisala, ndc (.235, .727) sisala, npp (.033, .524)Lambussie Karni dagarte, npp (0, .362)Lawra dagarte, ndc (.589, .668) dagarte, npp (.280, .359)
418
Table C-1. 2012 Presidential Vote Estimates by Tribe (urban covariate, flat priors
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.406 0.268 0.461 0.534 0.479 0.601 0.013 0.001 0.039 0.025 0.001 0.134ahafo 0.540 0.453 0.667 0.425 0.288 0.506 0.004 0.001 0.011 0.018 0.003 0.052ahanta 0.177 0.102 0.347 0.634 0.461 0.721 0.023 0.006 0.047 0.154 0.106 0.247
akuapem 0.194 0.132 0.261 0.716 0.665 0.767 0.005 0.002 0.009 0.073 0.025 0.125akwamu 0.515 0.498 0.540 0.473 0.448 0.489 0.003 0.001 0.007 0.002 0.001 0.006akyem(d) 0.140 0.084 0.211 0.729 0.654 0.788 0.005 0.002 0.009 0.114 0.060 0.184aowin 0.389 0.293 0.469 0.316 0.241 0.386 0.016 0.007 0.029 0.258 0.170 0.331
asante(d) 0.105 0.081 0.130 0.762 0.742 0.784 0.002 0.001 0.003 0.126 0.110 0.144asen 0.420 0.315 0.517 0.469 0.379 0.566 0.017 0.004 0.039 0.081 0.018 0.170
boron(d) 0.347 0.317 0.372 0.448 0.427 0.466 0.006 0.004 0.008 0.182 0.159 0.207chokosi(d) 0.457 0.366 0.516 0.445 0.389 0.513 0.027 0.014 0.042 0.054 0.014 0.095denkyira 0.257 0.159 0.365 0.548 0.439 0.637 0.013 0.004 0.028 0.167 0.099 0.256evalue 0.499 0.299 0.728 0.233 0.042 0.436 0.025 0.005 0.060 0.212 0.034 0.432fante(d) 0.407 0.367 0.443 0.313 0.273 0.349 0.013 0.010 0.016 0.250 0.218 0.289kwahu(d) 0.174 0.061 0.306 0.666 0.534 0.793 0.006 0.002 0.011 0.145 0.080 0.282nzema(d) 0.336 0.259 0.421 0.353 0.227 0.446 0.024 0.016 0.036 0.268 0.214 0.354sefwi(d) 0.534 0.497 0.572 0.278 0.247 0.307 0.005 0.001 0.011 0.165 0.131 0.205wasa 0.347 0.269 0.447 0.317 0.263 0.381 0.010 0.003 0.018 0.314 0.228 0.388bawle 0.403 0.258 0.474 0.044 0.002 0.185 0.531 0.342 0.571 0.015 0.002 0.083
other akan 0.095 0.046 0.114 0.867 0.847 0.906 0.027 0.004 0.039 0.005 0.001 0.026dangme(d) 0.523 0.452 0.582 0.239 0.192 0.287 0.007 0.004 0.010 0.212 0.166 0.262
ga 0.493 0.343 0.665 0.280 0.192 0.375 0.006 0.001 0.011 0.217 0.059 0.427other ga 0.326 0.133 0.529 0.566 0.368 0.668 0.067 0.001 0.222 0.027 0.002 0.112ewe(d) 0.584 0.523 0.652 0.045 0.030 0.066 0.006 0.005 0.008 0.351 0.289 0.405guan1 0.940 0.927 0.947 0.013 0.007 0.019 0.004 0.0002 0.012 0.002 0.001 0.007guan2 0.320 0.286 0.368 0.565 0.480 0.622 0.067 0.025 0.098 0.004 0.001 0.011guan3 0.342 0.191 0.450 0.455 0.358 0.542 0.014 0.003 0.034 0.169 0.067 0.309
guan4(d) 0.132 0.118 0.146 0.852 0.828 0.869 0.004 0.001 0.011 0.009 0.003 0.026guan5(d) 0.490 0.314 0.642 0.258 0.143 0.457 0.012 0.004 0.025 0.225 0.148 0.343guan6 0.712 0.448 0.911 0.086 0.016 0.217 0.016 0.003 0.036 0.179 0.028 0.439guan7 0.745 0.668 0.844 0.112 0.079 0.156 0.023 0.006 0.046 0.102 0.021 0.170guan8 0.818 0.487 0.925 0.069 0.002 0.309 0.013 0.001 0.027 0.031 0.002 0.211
other guan 0.621 0.599 0.635 0.283 0.262 0.303 0.086 0.059 0.113 0.003 0.001 0.005
420
Table C-1. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.749 0.669 0.840 0.032 0.002 0.128 0.022 0.004 0.042 0.169 0.092 0.237kokomba(d) 0.323 0.262 0.407 0.383 0.323 0.432 0.017 0.009 0.027 0.229 0.179 0.273
basare 0.737 0.589 0.872 0.179 0.112 0.257 0.032 0.003 0.079 0.043 0.004 0.120pilapila 0.350 0.324 0.380 0.206 0.184 0.224 0.386 0.317 0.441 0.010 0.003 0.034salfalba 0.200 0.148 0.295 0.651 0.529 0.756 0.110 0.008 0.198 0.029 0.007 0.102kotokoli 0.294 0.123 0.521 0.239 0.050 0.465 0.042 0.015 0.076 0.378 0.128 0.624chamba 0.842 0.834 0.851 0.011 0.007 0.014 0.102 0.092 0.112 0.002 0.001 0.004
other gruma 0.942 0.898 0.969 0.042 0.016 0.074 0.006 0.001 0.022 0.005 0.001 0.016builsa(d) 0.671 0.624 0.711 0.124 0.092 0.163 0.059 0.044 0.081 0.116 0.101 0.135dagarte(d) 0.504 0.435 0.567 0.108 0.081 0.143 0.017 0.011 0.023 0.326 0.272 0.381
wali 0.588 0.542 0.609 0.368 0.337 0.392 0.028 0.006 0.053 0.007 0.002 0.032dagomba(d) 0.533 0.495 0.567 0.253 0.227 0.282 0.016 0.010 0.022 0.181 0.158 0.215kusasi(d) 0.663 0.589 0.723 0.085 0.049 0.127 0.012 0.005 0.020 0.204 0.142 0.270
mamprusi(d) 0.368 0.279 0.465 0.359 0.299 0.420 0.019 0.008 0.034 0.216 0.153 0.328namnam 0.301 0.265 0.339 0.559 0.530 0.594 0.081 0.046 0.145 0.005 0.001 0.016
nankansi(d) 0.535 0.396 0.637 0.140 0.070 0.242 0.024 0.015 0.035 0.273 0.217 0.375nanumba 0.473 0.262 0.759 0.251 0.037 0.524 0.095 0.041 0.167 0.146 0.017 0.401mosi 0.489 0.410 0.528 0.480 0.459 0.532 0.008 0.001 0.030 0.018 0.005 0.039
other mole 0.825 0.813 0.833 0.054 0.050 0.058 0.021 0.009 0.025 0.002 0.001 0.005kasena(d) 0.350 0.251 0.470 0.518 0.395 0.575 0.015 0.002 0.036 0.098 0.041 0.183
mo 0.790 0.773 0.837 0.194 0.142 0.210 0.005 0.0004 0.013 0.003 0.0004 0.012sisala(d) 0.535 0.322 0.687 0.269 0.151 0.362 0.056 0.042 0.077 0.111 0.066 0.269vagala 0.327 0.005 0.545 0.161 0.004 0.529 0.440 0.281 0.552 0.046 0.006 0.177
othergrusi1 0.324 0.184 0.557 0.240 0.127 0.342 0.031 0.009 0.057 0.353 0.203 0.492othergrusi2 0.750 0.722 0.760 0.237 0.190 0.253 0.008 0.0004 0.032 0.002 0.0004 0.007busanga 0.135 0.106 0.161 0.838 0.805 0.871 0.011 0.001 0.041 0.008 0.002 0.024wangara 0.436 0.424 0.443 0.560 0.554 0.571 0.001 0.0003 0.004 0.002 0.001 0.002
othermande 0.235 0.163 0.357 0.571 0.307 0.701 0.105 0.004 0.370 0.017 0.004 0.043other inside 0.338 0.262 0.440 0.559 0.440 0.666 0.037 0.003 0.101 0.058 0.011 0.156other outside 0.318 0.074 0.667 0.154 0.040 0.433 0.053 0.019 0.098 0.408 0.129 0.669Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
421
Table C-2. 2012 Parliamentary Results by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.654 0.532 0.752 0.307 0.200 0.418 0.006 0.001 0.023 0.014 0.001 0.066ahafo 0.596 0.387 0.739 0.386 0.242 0.610 0.004 0.001 0.013 0.009 0.003 0.023
ahanta(d) 0.221 0.134 0.362 0.557 0.389 0.658 0.069 0.029 0.124 0.142 0.098 0.191akuapem 0.484 0.457 0.497 0.511 0.499 0.535 0.002 0.0003 0.004 0.002 0.001 0.005akwamu 0.419 0.383 0.460 0.566 0.522 0.605 0.006 0.0002 0.028 0.006 0.002 0.018akyem(d) 0.128 0.083 0.177 0.723 0.636 0.784 0.043 0.014 0.088 0.100 0.058 0.160aowin 0.385 0.279 0.496 0.351 0.268 0.433 0.020 0.002 0.041 0.230 0.129 0.325
asante(d) 0.111 0.092 0.128 0.713 0.688 0.732 0.028 0.024 0.038 0.166 0.142 0.190asen 0.374 0.232 0.523 0.521 0.367 0.644 0.031 0.008 0.053 0.060 0.011 0.132
boron(d) 0.358 0.324 0.392 0.441 0.395 0.471 0.011 0.005 0.017 0.185 0.155 0.216chokosi(d) 0.594 0.568 0.623 0.380 0.345 0.405 0.006 0.001 0.018 0.006 0.002 0.025denkyira 0.285 0.178 0.381 0.490 0.393 0.588 0.052 0.023 0.079 0.161 0.071 0.271evalue 0.312 0.075 0.459 0.590 0.399 0.693 0.010 0.001 0.038 0.075 0.005 0.325fante(d) 0.352 0.318 0.401 0.288 0.242 0.342 0.043 0.032 0.055 0.309 0.266 0.360kwahu(d) 0.177 0.072 0.358 0.434 0.316 0.620 0.019 0.006 0.047 0.362 0.138 0.557nzema(d) 0.368 0.253 0.488 0.147 0.105 0.242 0.133 0.112 0.189 0.334 0.247 0.439sefwi(d) 0.468 0.421 0.513 0.309 0.282 0.336 0.069 0.057 0.080 0.145 0.110 0.185wasa 0.410 0.301 0.519 0.339 0.267 0.443 0.018 0.002 0.045 0.226 0.150 0.328bawle 0.113 0.094 0.128 0.427 0.412 0.442 0.009 0.003 0.020 0.002 0.002 0.004
other akan 0.876 0.847 0.898 0.093 0.077 0.109 0.017 0.004 0.038 0.004 0.001 0.013dangme(d) 0.495 0.429 0.568 0.259 0.182 0.334 0.048 0.030 0.073 0.187 0.133 0.249
ga 0.477 0.266 0.636 0.181 0.027 0.363 0.015 0.005 0.028 0.322 0.108 0.537other ga 0.008 0.002 0.013 0.764 0.741 0.783 0.003 0.0003 0.008 0.002 0.001 0.005ewe(d) 0.401 0.358 0.444 0.148 0.081 0.201 0.066 0.046 0.082 0.377 0.318 0.443guan1 0.850 0.796 0.877 0.118 0.092 0.159 0.018 0.002 0.037 0.005 0.001 0.013guan2 0.777 0.749 0.797 0.163 0.146 0.182 0.053 0.039 0.069 0.003 0.001 0.007guan3 0.488 0.477 0.498 0.473 0.462 0.483 0.019 0.013 0.027 0.003 0.002 0.005guan4 0.357 0.333 0.392 0.615 0.580 0.643 0.007 0.001 0.022 0.006 0.002 0.013
guan5(d) 0.399 0.240 0.590 0.238 0.189 0.316 0.087 0.020 0.218 0.265 0.145 0.451guan6 0.423 0.387 0.464 0.562 0.522 0.596 0.010 0.002 0.018 0.004 0.001 0.010guan7 0.907 0.749 0.956 0.050 0.005 0.192 0.008 0.001 0.024 0.011 0.001 0.048guan8 0.715 0.620 0.870 0.245 0.029 0.352 0.004 0.0002 0.015 0.026 0.002 0.164
other guan 0.509 0.394 0.593 0.115 0.043 0.199 0.195 0.152 0.243 0.019 0.008 0.048
422
Table C-2. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.634 0.502 0.720 0.182 0.029 0.300 0.061 0.004 0.126 0.108 0.022 0.239kokomba(d) 0.169 0.122 0.236 0.349 0.295 0.408 0.185 0.162 0.205 0.280 0.234 0.326
basare 0.634 0.577 0.697 0.333 0.252 0.400 0.009 0.002 0.023 0.020 0.009 0.049pilapila 0.933 0.819 0.968 0.023 0.005 0.098 0.036 0.006 0.087 0.009 0.001 0.047salfalba 0.369 0.353 0.399 0.448 0.430 0.465 0.100 0.058 0.112 0.003 0.001 0.007kotokoli 0.522 0.140 0.721 0.111 0.020 0.416 0.068 0.013 0.201 0.266 0.141 0.464chamba 0.153 0.013 0.274 0.043 0.004 0.109 0.603 0.517 0.688 0.035 0.008 0.149
other gruma 0.729 0.682 0.774 0.239 0.174 0.289 0.005 0.001 0.019 0.008 0.003 0.031builsa(d) 0.190 0.158 0.230 0.512 0.454 0.560 0.137 0.121 0.160 0.130 0.106 0.175dagarte(d) 0.407 0.308 0.523 0.161 0.080 0.276 0.059 0.047 0.077 0.356 0.282 0.426
wali 0.210 0.093 0.282 0.517 0.452 0.621 0.232 0.167 0.276 0.027 0.003 0.137dagomba(d) 0.474 0.386 0.522 0.274 0.230 0.320 0.060 0.045 0.076 0.179 0.148 0.224kusasi(d) 0.553 0.464 0.620 0.140 0.085 0.195 0.022 0.009 0.035 0.279 0.217 0.350
mamprusi(d) 0.344 0.223 0.460 0.355 0.270 0.490 0.071 0.063 0.084 0.215 0.149 0.353namnam 0.279 0.116 0.375 0.597 0.484 0.679 0.038 0.003 0.229 0.025 0.001 0.115
nankansi(d) 0.450 0.325 0.521 0.202 0.156 0.278 0.071 0.052 0.089 0.265 0.206 0.345nanumba 0.623 0.576 0.659 0.252 0.197 0.299 0.049 0.017 0.100 0.036 0.011 0.076
mosi 0.492 0.461 0.510 0.424 0.403 0.457 0.008 0.001 0.022 0.003 0.002 0.007other mole 0.430 0.387 0.508 0.476 0.430 0.552 0.077 0.040 0.107 0.005 0.002 0.007kasena(d) 0.507 0.412 0.569 0.335 0.253 0.388 0.045 0.005 0.067 0.097 0.020 0.190
mo 0.503 0.486 0.517 0.491 0.480 0.505 0.001 0.0001 0.003 0.003 0.001 0.005sisala(d) 0.378 0.198 0.457 0.354 0.297 0.456 0.134 0.105 0.183 0.120 0.072 0.274vagala 0.104 0.023 0.205 0.697 0.583 0.829 0.042 0.003 0.142 0.044 0.007 0.139
othergrusi1 0.383 0.201 0.602 0.440 0.263 0.595 0.028 0.004 0.063 0.111 0.008 0.269othergrusi2 0.618 0.485 0.829 0.277 0.137 0.347 0.009 0.001 0.030 0.031 0.003 0.100busanga 0.293 0.286 0.302 0.710 0.700 0.717 0.002 0.0004 0.005 0.003 0.001 0.005wangara 0.346 0.268 0.393 0.635 0.597 0.697 0.002 0.001 0.006 0.006 0.003 0.015
othermande 0.286 0.018 0.516 0.192 0.071 0.317 0.156 0.105 0.274 0.054 0.005 0.188other inside 0.370 0.234 0.470 0.529 0.451 0.649 0.008 0.001 0.031 0.037 0.004 0.122
other outside 0.714 0.671 0.735 0.173 0.157 0.200 0.002 0.0004 0.006 0.003 0.001 0.007Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
423
Table C-3. 2008 Presidential Runoff Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%agona(d) 0.328 0.181 0.437 0.587 0.501 0.662 0.014 0.002 0.029 0.072 0.010 0.210ahafo 0.491 0.382 0.585 0.411 0.259 0.558 0.007 0.001 0.018 0.090 0.015 0.251
ahanta(d) 0.087 0.047 0.136 0.705 0.631 0.757 0.007 0.002 0.016 0.201 0.145 0.283akuapem(d) 0.118 0.043 0.251 0.619 0.451 0.709 0.006 0.003 0.010 0.256 0.163 0.361
akwamu 0.404 0.227 0.589 0.447 0.196 0.607 0.022 0.005 0.063 0.127 0.014 0.371akyem(d) 0.142 0.048 0.289 0.675 0.545 0.784 0.005 0.002 0.009 0.178 0.090 0.318aowin(d) 0.297 0.160 0.490 0.214 0.068 0.347 0.017 0.003 0.046 0.472 0.338 0.629asante(d) 0.052 0.036 0.070 0.793 0.761 0.821 0.002 0.001 0.003 0.153 0.123 0.187asen(d) 0.280 0.239 0.321 0.684 0.618 0.725 0.005 0.001 0.011 0.031 0.005 0.108boron(d) 0.273 0.239 0.312 0.345 0.316 0.371 0.004 0.003 0.006 0.378 0.340 0.414chokosi 0.268 0.143 0.385 0.557 0.421 0.696 0.025 0.009 0.045 0.150 0.082 0.250
denkyira(d) 0.211 0.092 0.328 0.583 0.445 0.723 0.013 0.004 0.035 0.194 0.099 0.308evalue(d) 0.261 0.182 0.349 0.674 0.544 0.774 0.038 0.003 0.107 0.027 0.004 0.085fante(d) 0.351 0.297 0.394 0.266 0.214 0.317 0.006 0.005 0.007 0.378 0.314 0.427kwahu(d) 0.113 0.037 0.291 0.531 0.297 0.760 0.005 0.002 0.010 0.351 0.161 0.634nzema(d) 0.256 0.172 0.391 0.254 0.174 0.382 0.009 0.004 0.016 0.481 0.387 0.602sefwi(d) 0.473 0.427 0.517 0.259 0.233 0.284 0.004 0.002 0.008 0.264 0.218 0.309wasa(d) 0.315 0.211 0.426 0.391 0.324 0.457 0.006 0.002 0.013 0.288 0.182 0.413bawle 0.174 0.120 0.337 0.295 0.026 0.524 0.503 0.242 0.816 0.027 0.002 0.257
other akan 0.905 0.874 0.926 0.069 0.051 0.104 0.020 0.003 0.035 0.006 0.0004 0.036dangme(d) 0.465 0.341 0.573 0.189 0.123 0.267 0.006 0.003 0.009 0.340 0.259 0.434
ga(d) 0.534 0.327 0.723 0.269 0.098 0.410 0.002 0.0004 0.005 0.195 0.074 0.402other ga 0.330 0.102 0.501 0.612 0.445 0.856 0.028 0.005 0.078 0.030 0.004 0.117ewe(d) 0.584 0.497 0.655 0.043 0.027 0.072 0.004 0.003 0.005 0.369 0.299 0.455guan1(d) 0.316 0.079 0.674 0.353 0.146 0.460 0.010 0.003 0.023 0.320 0.092 0.516guan2 0.869 0.681 0.930 0.093 0.032 0.286 0.032 0.009 0.050 0.006 0.0003 0.035
guan3(d) 0.361 0.243 0.471 0.328 0.205 0.444 0.016 0.003 0.037 0.294 0.133 0.448guan4(d) 0.126 0.090 0.175 0.843 0.779 0.881 0.009 0.002 0.021 0.021 0.001 0.080guan5(d) 0.219 0.146 0.349 0.450 0.246 0.589 0.011 0.004 0.023 0.320 0.213 0.510guan6(d) 0.952 0.858 0.980 0.034 0.014 0.114 0.007 0.001 0.018 0.008 0.0005 0.042guan7(d) 0.743 0.502 0.972 0.090 0.004 0.232 0.010 0.003 0.020 0.157 0.004 0.369guan8(d) 0.513 0.300 0.821 0.071 0.004 0.169 0.047 0.005 0.095 0.369 0.115 0.564other guan 0.840 0.756 0.967 0.108 0.015 0.170 0.038 0.007 0.059 0.014 0.001 0.074
424
Table C-3. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.674 0.467 0.823 0.134 0.066 0.223 0.014 0.003 0.026 0.178 0.023 0.387kokomba(d) 0.317 0.255 0.373 0.245 0.204 0.298 0.013 0.008 0.017 0.426 0.375 0.470
basare 0.101 0.069 0.141 0.885 0.838 0.917 0.005 0.0004 0.016 0.009 0.003 0.020pilapila 0.152 0.004 0.355 0.221 0.083 0.346 0.575 0.456 0.691 0.052 0.015 0.156salfalba 0.692 0.444 0.772 0.033 0.002 0.146 0.249 0.114 0.426 0.026 0.005 0.094
kotokoli(d) 0.547 0.110 0.748 0.242 0.032 0.395 0.016 0.005 0.042 0.196 0.002 0.781chamba 0.727 0.691 0.778 0.040 0.013 0.076 0.212 0.151 0.254 0.022 0.006 0.064
other gurma 0.983 0.969 0.988 0.006 0.003 0.009 0.009 0.005 0.019 0.002 0.0002 0.013builsa(d) 0.720 0.680 0.757 0.106 0.079 0.136 0.012 0.004 0.022 0.162 0.140 0.189dagarte(d) 0.456 0.355 0.560 0.100 0.070 0.140 0.010 0.006 0.014 0.434 0.317 0.535wali(d) 0.317 0.110 0.464 0.445 0.367 0.534 0.023 0.007 0.045 0.215 0.073 0.424
dagomba(d) 0.566 0.526 0.603 0.239 0.207 0.267 0.008 0.006 0.011 0.187 0.165 0.220kusasi(d) 0.496 0.369 0.603 0.113 0.069 0.182 0.009 0.005 0.016 0.381 0.287 0.494
mamprusi(d) 0.518 0.427 0.581 0.248 0.187 0.315 0.012 0.007 0.020 0.222 0.161 0.318namnam 0.764 0.331 0.969 0.107 0.003 0.444 0.024 0.002 0.050 0.105 0.003 0.504
nankansi(d) 0.470 0.298 0.573 0.227 0.157 0.365 0.013 0.008 0.020 0.290 0.219 0.398nanumba(d) 0.229 0.189 0.252 0.758 0.724 0.789 0.007 0.002 0.021 0.005 0.001 0.018
mosi 0.768 0.658 0.872 0.193 0.080 0.265 0.006 0.0004 0.024 0.032 0.004 0.173other mole 0.927 0.865 0.967 0.056 0.008 0.115 0.008 0.0004 0.022 0.009 0.001 0.045kasena(d) 0.492 0.286 0.636 0.276 0.117 0.500 0.022 0.008 0.042 0.209 0.087 0.448
mo 0.906 0.850 0.938 0.078 0.048 0.117 0.008 0.0004 0.028 0.008 0.0004 0.026sisala(d) 0.425 0.252 0.559 0.302 0.215 0.463 0.013 0.006 0.027 0.260 0.151 0.440vagala 0.225 0.057 0.409 0.515 0.262 0.663 0.110 0.021 0.193 0.150 0.003 0.481
othergrusi1(d) 0.733 0.567 0.823 0.223 0.153 0.330 0.018 0.003 0.044 0.027 0.003 0.108othergrusi2 0.011 0.002 0.019 0.984 0.972 0.993 0.003 0.0005 0.009 0.002 0.0004 0.011busanga 0.753 0.714 0.782 0.234 0.208 0.270 0.006 0.001 0.014 0.008 0.002 0.018wangara 0.359 0.316 0.405 0.630 0.565 0.671 0.005 0.001 0.033 0.005 0.002 0.017
othermande 0.564 0.286 0.780 0.149 0.0004 0.479 0.240 0.089 0.402 0.047 0.003 0.201other inside 0.496 0.396 0.579 0.468 0.382 0.545 0.018 0.004 0.040 0.017 0.003 0.055other outside 0.473 0.366 0.639 0.439 0.213 0.525 0.060 0.042 0.086 0.027 0.003 0.139
Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;(d) = deterministic bounds info. contributed to this group’s vote estimates
425
Table C-4. 2008 Presidential Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%agona(d) 0.377 0.349 0.410 0.564 0.529 0.588 0.015 0.004 0.027 0.007 0.003 0.013ahafo 0.522 0.486 0.553 0.439 0.399 0.475 0.004 0.0003 0.015 0.016 0.005 0.039
ahanta(d) 0.113 0.033 0.242 0.593 0.460 0.688 0.051 0.022 0.095 0.221 0.174 0.293akuapem(d) 0.108 0.019 0.196 0.673 0.616 0.728 0.009 0.004 0.016 0.197 0.111 0.269akwamu 0.233 0.203 0.270 0.735 0.683 0.767 0.008 0.001 0.022 0.016 0.005 0.039akyem(d) 0.134 0.052 0.253 0.582 0.498 0.688 0.007 0.003 0.014 0.266 0.169 0.381aowin 0.226 0.125 0.343 0.233 0.146 0.329 0.027 0.009 0.055 0.393 0.273 0.511
asante(d) 0.053 0.036 0.067 0.664 0.640 0.685 0.003 0.002 0.005 0.275 0.257 0.295asen(d) 0.228 0.068 0.375 0.470 0.355 0.617 0.022 0.006 0.057 0.251 0.154 0.391boron(d) 0.292 0.264 0.323 0.348 0.319 0.373 0.005 0.003 0.008 0.345 0.314 0.378chokosi(d) 0.402 0.197 0.569 0.336 0.221 0.458 0.048 0.017 0.096 0.152 0.051 0.293denkyira(d) 0.109 0.043 0.212 0.620 0.521 0.719 0.047 0.018 0.086 0.198 0.113 0.295evalue(d) 0.231 0.204 0.257 0.675 0.642 0.703 0.076 0.050 0.112 0.003 0.001 0.009fante(d) 0.319 0.291 0.352 0.273 0.238 0.312 0.018 0.013 0.023 0.374 0.330 0.426kwahu(d) 0.171 0.037 0.377 0.393 0.295 0.515 0.013 0.006 0.028 0.413 0.209 0.619nzema(d) 0.182 0.125 0.263 0.193 0.126 0.303 0.151 0.102 0.219 0.441 0.371 0.527sefwi(d) 0.442 0.398 0.482 0.279 0.252 0.307 0.006 0.002 0.012 0.253 0.212 0.299wasa(d) 0.207 0.151 0.267 0.416 0.345 0.497 0.050 0.020 0.087 0.313 0.242 0.397bawle 0.396 0.288 0.435 0.463 0.395 0.585 0.057 0.024 0.091 0.012 0.003 0.042
other akan 0.850 0.700 0.969 0.029 0.004 0.059 0.082 0.001 0.234 0.014 0.003 0.058dangme(d) 0.473 0.405 0.544 0.203 0.120 0.261 0.013 0.009 0.019 0.296 0.239 0.388
ga(d) 0.678 0.548 0.780 0.251 0.150 0.315 0.007 0.0005 0.015 0.062 0.001 0.196other ga 0.807 0.713 0.883 0.071 0.053 0.095 0.100 0.007 0.178 0.006 0.001 0.015ewe(d) 0.445 0.410 0.489 0.045 0.027 0.073 0.008 0.006 0.011 0.492 0.434 0.532
guan1(d) 0.878 0.807 0.916 0.085 0.056 0.127 0.012 0.003 0.025 0.012 0.001 0.041guan2 0.059 0.018 0.108 0.573 0.523 0.625 0.189 0.126 0.218 0.015 0.003 0.124
guan3(d) 0.318 0.197 0.450 0.243 0.140 0.345 0.030 0.007 0.063 0.376 0.226 0.504guan4(d) 0.246 0.237 0.258 0.692 0.682 0.705 0.030 0.024 0.036 0.001 0.0004 0.003guan5(d) 0.352 0.287 0.423 0.343 0.256 0.413 0.019 0.007 0.039 0.272 0.207 0.366guan6(d) 0.741 0.585 0.862 0.170 0.088 0.268 0.010 0.001 0.029 0.067 0.008 0.177guan7(d) 0.420 0.284 0.710 0.127 0.019 0.287 0.026 0.008 0.051 0.389 0.177 0.556guan8(d) 0.649 0.204 0.821 0.146 0.028 0.215 0.029 0.007 0.053 0.147 0.004 0.610other guan 0.319 0.269 0.432 0.483 0.389 0.527 0.176 0.008 0.233 0.012 0.002 0.052
426
Table C-4. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.586 0.426 0.744 0.080 0.014 0.173 0.070 0.040 0.097 0.214 0.090 0.320kokomba(d) 0.337 0.285 0.383 0.299 0.239 0.354 0.027 0.017 0.039 0.303 0.256 0.360
basare 0.056 0.032 0.068 0.892 0.864 0.911 0.027 0.008 0.037 0.006 0.002 0.035pilapila 0.024 0.009 0.044 0.188 0.125 0.262 0.362 0.225 0.451 0.011 0.002 0.021salfalba 0.412 0.111 0.610 0.035 0.003 0.175 0.234 0.117 0.404 0.036 0.003 0.143
kotokoli(d) 0.806 0.743 0.868 0.172 0.109 0.232 0.003 0.0004 0.017 0.008 0.003 0.023chamba 0.134 0.125 0.145 0.028 0.001 0.052 0.014 0.007 0.021 0.004 0.001 0.018
other gurma 0.942 0.931 0.949 0.012 0.006 0.021 0.003 0.0004 0.010 0.003 0.001 0.005builsa(d) 0.477 0.384 0.541 0.165 0.126 0.250 0.114 0.066 0.175 0.200 0.156 0.258dagarte(d) 0.250 0.203 0.304 0.147 0.111 0.195 0.029 0.022 0.039 0.545 0.482 0.598wali(d) 0.845 0.708 0.939 0.035 0.008 0.066 0.012 0.002 0.031 0.094 0.005 0.223
dagomba(d) 0.489 0.457 0.521 0.240 0.207 0.278 0.020 0.013 0.029 0.236 0.207 0.268kusasi(d) 0.601 0.536 0.659 0.129 0.081 0.185 0.012 0.005 0.021 0.235 0.180 0.295
mamprusi(d) 0.303 0.232 0.378 0.312 0.220 0.393 0.095 0.067 0.131 0.259 0.193 0.351namnam 0.201 0.077 0.355 0.409 0.169 0.566 0.224 0.061 0.281 0.095 0.005 0.415
nankansi(d) 0.402 0.312 0.489 0.194 0.135 0.269 0.047 0.031 0.079 0.327 0.268 0.401nanumba(d) 0.282 0.153 0.454 0.569 0.359 0.771 0.047 0.008 0.099 0.081 0.005 0.238
mosi 0.241 0.140 0.313 0.659 0.587 0.746 0.031 0.003 0.109 0.051 0.011 0.141other mole 0.072 0.002 0.308 0.208 0.051 0.354 0.350 0.307 0.448 0.019 0.004 0.071kasena(d) 0.570 0.459 0.677 0.233 0.126 0.319 0.062 0.007 0.126 0.110 0.019 0.216
mo 0.876 0.768 0.964 0.068 0.001 0.183 0.005 0.001 0.016 0.031 0.005 0.097sisala 0.202 0.145 0.270 0.556 0.485 0.615 0.067 0.041 0.086 0.144 0.105 0.191vagala 0.073 0.015 0.133 0.652 0.606 0.739 0.160 0.061 0.235 0.017 0.003 0.055
othergrusi1(d) 0.676 0.648 0.697 0.217 0.184 0.243 0.018 0.001 0.045 0.008 0.002 0.029othergrusi2 0.193 0.170 0.246 0.747 0.701 0.795 0.042 0.003 0.103 0.006 0.002 0.018busanga 0.616 0.535 0.702 0.343 0.261 0.422 0.008 0.002 0.020 0.014 0.003 0.039wangara 0.226 0.213 0.244 0.762 0.741 0.776 0.004 0.001 0.012 0.004 0.002 0.007
othermande 0.273 0.055 0.578 0.543 0.224 0.693 0.049 0.001 0.133 0.042 0.006 0.267other inside 0.623 0.501 0.757 0.105 0.024 0.221 0.199 0.034 0.315 0.038 0.001 0.165other outside 0.494 0.366 0.661 0.223 0.078 0.375 0.033 0.009 0.079 0.216 0.049 0.391
Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;(d) = deterministic bounds info. contributed to this group’s vote estimates
427
Table C-5. 2008 Parliamentary Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%agona(d) 0.191 0.031 0.360 0.258 0.079 0.507 0.231 0.035 0.349 0.279 0.068 0.503ahafo 0.484 0.417 0.556 0.465 0.339 0.523 0.014 0.002 0.040 0.027 0.008 0.103
ahanta(d) 0.161 0.035 0.301 0.554 0.386 0.694 0.097 0.034 0.226 0.172 0.103 0.300akuapem(d) 0.091 0.026 0.193 0.713 0.672 0.748 0.025 0.007 0.043 0.164 0.086 0.236
akwamu 0.320 0.207 0.384 0.595 0.364 0.674 0.026 0.002 0.121 0.049 0.003 0.312akyem(d) 0.161 0.063 0.297 0.634 0.500 0.734 0.020 0.010 0.032 0.177 0.120 0.248aowin(d) 0.433 0.272 0.580 0.228 0.045 0.384 0.024 0.005 0.060 0.303 0.126 0.510asante(d) 0.098 0.059 0.133 0.556 0.517 0.600 0.072 0.057 0.085 0.270 0.234 0.303asen(d) 0.210 0.100 0.350 0.631 0.481 0.738 0.010 0.004 0.021 0.139 0.053 0.236boron(d) 0.292 0.241 0.332 0.356 0.317 0.401 0.019 0.011 0.029 0.327 0.284 0.374chokosi(d) 0.532 0.368 0.648 0.221 0.130 0.350 0.035 0.010 0.074 0.163 0.053 0.305denkyira(d) 0.165 0.066 0.296 0.469 0.272 0.616 0.219 0.130 0.333 0.136 0.051 0.256evalue(d) 0.103 0.014 0.274 0.360 0.153 0.535 0.204 0.083 0.319 0.297 0.087 0.566fante(d) 0.314 0.256 0.392 0.265 0.202 0.318 0.044 0.029 0.068 0.368 0.313 0.449kwahu(d) 0.107 0.031 0.278 0.362 0.184 0.621 0.110 0.090 0.151 0.406 0.216 0.629nzema(d) 0.276 0.133 0.386 0.094 0.013 0.251 0.288 0.248 0.365 0.295 0.226 0.371sefwi(d) 0.464 0.412 0.514 0.325 0.282 0.365 0.013 0.003 0.025 0.193 0.134 0.245wasa(d) 0.256 0.174 0.352 0.341 0.208 0.476 0.162 0.106 0.224 0.232 0.113 0.345bawle 0.237 0.153 0.311 0.558 0.448 0.640 0.024 0.003 0.078 0.017 0.004 0.047
other akan 0.836 0.784 0.872 0.108 0.081 0.129 0.013 0.001 0.048 0.005 0.001 0.014dangme(d) 0.383 0.275 0.483 0.253 0.181 0.345 0.023 0.013 0.039 0.331 0.242 0.447
ga(d) 0.685 0.542 0.823 0.067 0.020 0.137 0.027 0.002 0.065 0.215 0.072 0.363other ga 0.022 0.009 0.045 0.848 0.831 0.867 0.049 0.025 0.067 0.003 0.001 0.005ewe(d) 0.421 0.352 0.490 0.054 0.039 0.082 0.036 0.027 0.051 0.481 0.412 0.552
guan1(d) 0.803 0.767 0.850 0.166 0.115 0.200 0.016 0.005 0.032 0.005 0.001 0.017guan2 0.746 0.716 0.772 0.090 0.070 0.137 0.095 0.065 0.121 0.005 0.001 0.014
guan3(d) 0.483 0.351 0.621 0.173 0.086 0.264 0.020 0.004 0.043 0.307 0.136 0.456guan4(d) 0.138 0.018 0.247 0.736 0.581 0.835 0.028 0.002 0.093 0.084 0.003 0.183guan5(d) 0.264 0.145 0.508 0.371 0.206 0.580 0.028 0.008 0.076 0.317 0.193 0.518guan6 0.624 0.563 0.679 0.292 0.241 0.343 0.062 0.028 0.089 0.012 0.003 0.032
guan7(d) 0.240 0.052 0.457 0.226 0.063 0.497 0.126 0.022 0.332 0.380 0.166 0.620guan8(d) 0.393 0.136 0.598 0.392 0.119 0.653 0.021 0.002 0.062 0.157 0.006 0.506other guan 0.548 0.519 0.574 0.428 0.390 0.465 0.013 0.005 0.023 0.004 0.001 0.013
428
Table C-5. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.478 0.372 0.572 0.149 0.108 0.209 0.186 0.110 0.234 0.166 0.067 0.291kokomba(d) 0.129 0.067 0.205 0.377 0.299 0.440 0.165 0.112 0.212 0.310 0.232 0.395
basare 0.408 0.333 0.523 0.554 0.405 0.639 0.009 0.001 0.036 0.021 0.003 0.084pilapila 0.047 0.009 0.115 0.870 0.798 0.916 0.019 0.001 0.054 0.009 0.002 0.023salfalba 0.085 0.002 0.270 0.649 0.184 0.920 0.128 0.017 0.302 0.058 0.005 0.235
kotokoli(d) 0.131 0.082 0.193 0.683 0.616 0.743 0.033 0.009 0.066 0.134 0.070 0.207chamba 0.004 0.0002 0.014 0.841 0.649 0.902 0.057 0.011 0.084 0.021 0.001 0.084
other gruma 0.895 0.879 0.913 0.085 0.050 0.101 0.003 0.0002 0.012 0.006 0.001 0.027builsa(d) 0.176 0.138 0.232 0.495 0.376 0.556 0.125 0.099 0.160 0.169 0.125 0.268dagarte 0.227 0.152 0.341 0.211 0.164 0.276 0.052 0.039 0.069 0.492 0.378 0.583wali(d) 0.595 0.510 0.663 0.322 0.249 0.372 0.048 0.007 0.089 0.019 0.002 0.062
dagomba(d) 0.472 0.414 0.523 0.204 0.162 0.248 0.061 0.041 0.094 0.251 0.202 0.306kusasi(d) 0.234 0.143 0.364 0.313 0.205 0.439 0.057 0.043 0.076 0.376 0.271 0.479
mamprusi(d) 0.310 0.220 0.377 0.312 0.219 0.388 0.125 0.088 0.159 0.234 0.172 0.321namnam 0.180 0.013 0.300 0.635 0.555 0.696 0.092 0.015 0.269 0.054 0.013 0.098nankansi(d) 0.325 0.252 0.457 0.208 0.086 0.346 0.097 0.071 0.144 0.344 0.239 0.472nanumba(d) 0.522 0.354 0.628 0.257 0.167 0.363 0.057 0.010 0.124 0.120 0.035 0.224
mosi 0.537 0.159 0.818 0.093 0.023 0.220 0.044 0.010 0.101 0.290 0.047 0.693other mole 0.347 0.341 0.353 0.110 0.104 0.116 0.539 0.529 0.547 0.001 0.0004 0.002kasena(d) 0.290 0.178 0.410 0.350 0.177 0.519 0.195 0.151 0.239 0.145 0.061 0.251
mo 0.624 0.435 0.768 0.299 0.173 0.445 0.029 0.002 0.120 0.034 0.007 0.110sisala(d) 0.234 0.114 0.416 0.351 0.162 0.542 0.137 0.116 0.164 0.248 0.158 0.376vagala 0.733 0.688 0.759 0.005 0.0004 0.015 0.205 0.188 0.247 0.006 0.002 0.017
othergrusi1(d) 0.631 0.548 0.696 0.241 0.197 0.317 0.030 0.008 0.063 0.055 0.019 0.109othergrusi2 0.513 0.372 0.571 0.398 0.166 0.478 0.049 0.001 0.225 0.036 0.002 0.166busganga 0.505 0.341 0.611 0.430 0.356 0.520 0.017 0.001 0.044 0.035 0.006 0.193wangara 0.602 0.580 0.653 0.381 0.302 0.410 0.009 0.001 0.042 0.006 0.001 0.026
othermande 0.139 0.092 0.254 0.025 0.003 0.086 0.693 0.572 0.735 0.009 0.001 0.069other inside 0.411 0.129 0.786 0.334 0.007 0.616 0.197 0.147 0.286 0.032 0.004 0.141
other outside 0.344 0.287 0.364 0.635 0.606 0.660 0.005 0.001 0.013 0.006 0.001 0.029Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
429
Table C-6. 2004 Presidential Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.349 0.310 0.376 0.640 0.608 0.674 0.006 0.0004 0.019 0.004 0.001 0.011ahafo 0.555 0.417 0.627 0.356 0.262 0.465 0.011 0.002 0.028 0.062 0.012 0.137
ahanta(d) 0.094 0.012 0.196 0.714 0.568 0.845 0.018 0.004 0.037 0.147 0.056 0.298akuapem(d) 0.071 0.012 0.104 0.903 0.876 0.932 0.006 0.003 0.012 0.017 0.003 0.077akwamu 0.349 0.319 0.365 0.637 0.624 0.648 0.007 0.001 0.035 0.004 0.001 0.009akyem(d) 0.236 0.121 0.315 0.703 0.638 0.797 0.005 0.002 0.014 0.048 0.015 0.114aowin 0.364 0.272 0.441 0.481 0.390 0.567 0.011 0.001 0.030 0.128 0.024 0.235
asante(d) 0.056 0.041 0.068 0.837 0.817 0.855 0.003 0.002 0.007 0.094 0.079 0.110asen(d) 0.151 0.108 0.188 0.738 0.706 0.781 0.098 0.073 0.116 0.007 0.001 0.023boron(d) 0.321 0.288 0.356 0.477 0.449 0.505 0.009 0.005 0.014 0.182 0.155 0.213chokosi(d) 0.458 0.426 0.489 0.467 0.424 0.488 0.045 0.013 0.088 0.004 0.001 0.012denkyira(d) 0.121 0.102 0.146 0.793 0.760 0.844 0.064 0.001 0.094 0.005 0.001 0.019evalue(d) 0.200 0.120 0.267 0.739 0.674 0.781 0.043 0.002 0.110 0.010 0.002 0.041fante(d) 0.263 0.235 0.299 0.514 0.477 0.543 0.015 0.011 0.019 0.190 0.165 0.218kwahu(d) 0.044 0.012 0.109 0.437 0.267 0.585 0.016 0.006 0.034 0.487 0.346 0.654nzema(d) 0.232 0.150 0.332 0.378 0.324 0.464 0.049 0.032 0.071 0.311 0.231 0.395sefwi(d) 0.593 0.560 0.623 0.306 0.281 0.330 0.006 0.002 0.011 0.069 0.045 0.093wasa(d) 0.190 0.124 0.251 0.665 0.575 0.734 0.017 0.005 0.032 0.105 0.052 0.184bawle 0.726 0.697 0.756 0.236 0.172 0.267 0.019 0.005 0.041 0.012 0.001 0.063
other akan 0.867 0.805 0.893 0.108 0.098 0.125 0.008 0.0004 0.073 0.003 0.001 0.012dangme(d) 0.498 0.420 0.561 0.286 0.205 0.343 0.015 0.010 0.023 0.175 0.122 0.302
ga 0.640 0.555 0.714 0.343 0.272 0.426 0.010 0.007 0.014 0.005 0.001 0.017other ga 0.751 0.717 0.779 0.213 0.168 0.247 0.023 0.002 0.041 0.005 0.001 0.014ewe(d) 0.635 0.604 0.674 0.090 0.054 0.149 0.009 0.007 0.011 0.243 0.183 0.293
guan1(d) 0.888 0.797 0.943 0.071 0.018 0.131 0.022 0.005 0.040 0.013 0.001 0.057guan2 0.411 0.333 0.478 0.523 0.450 0.583 0.056 0.021 0.089 0.008 0.002 0.024
guan3(d) 0.420 0.323 0.535 0.422 0.290 0.523 0.017 0.004 0.035 0.119 0.057 0.210guan4 0.400 0.132 0.493 0.530 0.481 0.646 0.018 0.007 0.030 0.038 0.002 0.199
guan5(d) 0.311 0.235 0.400 0.421 0.333 0.484 0.022 0.008 0.042 0.223 0.164 0.297guan6 0.669 0.599 0.732 0.245 0.210 0.277 0.029 0.001 0.113 0.036 0.006 0.101
guan7(d) 0.582 0.467 0.694 0.121 0.057 0.204 0.038 0.010 0.074 0.176 0.081 0.273guan8(d) 0.931 0.888 0.960 0.027 0.003 0.064 0.026 0.009 0.049 0.006 0.001 0.017other guan 0.345 0.334 0.359 0.639 0.627 0.649 0.012 0.001 0.027 0.003 0.001 0.005
430
Table C-6. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.568 0.555 0.587 0.420 0.388 0.436 0.007 0.001 0.027 0.003 0.002 0.006kokomba(d) 0.341 0.295 0.399 0.368 0.323 0.400 0.066 0.044 0.089 0.145 0.120 0.169
basare 0.560 0.500 0.595 0.366 0.305 0.432 0.026 0.006 0.072 0.033 0.006 0.120pilapila 0.459 0.403 0.525 0.437 0.316 0.518 0.068 0.009 0.144 0.014 0.003 0.038salfalba 0.969 0.911 0.984 0.009 0.004 0.022 0.011 0.002 0.051 0.005 0.001 0.021kotokoli 0.584 0.551 0.615 0.371 0.339 0.404 0.021 0.002 0.052 0.014 0.006 0.029chamba 0.516 0.269 0.604 0.145 0.021 0.420 0.264 0.010 0.361 0.049 0.005 0.239
other gurma 0.789 0.754 0.838 0.101 0.083 0.117 0.087 0.032 0.132 0.008 0.001 0.024builsa(d) 0.422 0.319 0.512 0.252 0.165 0.348 0.144 0.108 0.197 0.142 0.093 0.217
dagarte(d) 0.423 0.367 0.483 0.164 0.116 0.208 0.034 0.025 0.046 0.309 0.256 0.357wali(d) 0.129 0.018 0.251 0.640 0.556 0.703 0.137 0.052 0.188 0.078 0.008 0.228
dagomba(d) 0.620 0.572 0.648 0.262 0.233 0.303 0.016 0.008 0.027 0.085 0.070 0.109kusasi(d) 0.647 0.612 0.678 0.101 0.088 0.128 0.050 0.039 0.061 0.183 0.154 0.218
mamprusi(d) 0.261 0.153 0.350 0.248 0.169 0.329 0.231 0.188 0.278 0.199 0.138 0.278namnam(d) 0.505 0.417 0.595 0.455 0.384 0.526 0.019 0.0002 0.048 0.008 0.002 0.019nankansi(d) 0.339 0.235 0.419 0.249 0.184 0.340 0.124 0.100 0.153 0.251 0.163 0.356nanumba 0.423 0.355 0.476 0.519 0.472 0.582 0.040 0.005 0.075 0.011 0.003 0.030mosi 0.604 0.586 0.619 0.373 0.353 0.387 0.018 0.001 0.032 0.003 0.001 0.004
other mole 0.147 0.031 0.222 0.105 0.032 0.215 0.672 0.424 0.779 0.013 0.003 0.051kasena(d) 0.681 0.550 0.783 0.144 0.057 0.242 0.059 0.011 0.138 0.095 0.028 0.184
mo 0.522 0.454 0.552 0.464 0.441 0.509 0.007 0.001 0.022 0.005 0.001 0.024sisala(d) 0.521 0.430 0.572 0.208 0.170 0.255 0.166 0.143 0.187 0.083 0.051 0.130vagala 0.192 0.064 0.415 0.541 0.403 0.680 0.238 0.072 0.371 0.018 0.003 0.051
othergrusi1(d) 0.941 0.813 0.969 0.037 0.019 0.108 0.015 0.002 0.071 0.004 0.001 0.015othergrusi2 0.741 0.713 0.757 0.137 0.121 0.149 0.112 0.096 0.136 0.004 0.001 0.011busganga 0.177 0.152 0.224 0.814 0.765 0.838 0.005 0.001 0.011 0.003 0.001 0.010wangara 0.552 0.538 0.585 0.436 0.401 0.450 0.003 0.001 0.009 0.003 0.001 0.008
othermande 0.553 0.505 0.632 0.206 0.161 0.259 0.182 0.023 0.282 0.036 0.006 0.089other inside 0.130 0.080 0.168 0.746 0.687 0.816 0.097 0.005 0.181 0.013 0.004 0.031other outside 0.660 0.648 0.671 0.327 0.316 0.337 0.002 0.0004 0.009 0.003 0.002 0.005Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
431
Table C-7. 2004 Presidential Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%agona(d) 0.156 0.108 0.218 0.832 0.760 0.859 0.006 0.0003 0.029 0.004 0.001 0.015ahafo 0.487 0.390 0.627 0.404 0.202 0.527 0.011 0.001 0.029 0.075 0.024 0.221
ahanta(d) 0.054 0.013 0.093 0.831 0.784 0.874 0.019 0.006 0.032 0.078 0.042 0.112akuapem(d) 0.069 0.014 0.145 0.819 0.696 0.879 0.018 0.006 0.034 0.084 0.008 0.244
akwamu 0.411 0.375 0.442 0.574 0.534 0.605 0.005 0.001 0.012 0.005 0.001 0.017akyem(d) 0.219 0.145 0.285 0.734 0.662 0.787 0.006 0.002 0.015 0.034 0.009 0.078aowin 0.525 0.434 0.613 0.336 0.255 0.416 0.016 0.003 0.034 0.110 0.029 0.196
asante(d) 0.050 0.038 0.063 0.845 0.827 0.858 0.004 0.002 0.006 0.093 0.076 0.112asen(d) 0.092 0.041 0.110 0.878 0.821 0.906 0.017 0.007 0.039 0.010 0.0005 0.072boron(d) 0.312 0.276 0.351 0.482 0.454 0.506 0.010 0.006 0.014 0.189 0.158 0.224chokosi(d) 0.362 0.316 0.392 0.545 0.497 0.599 0.059 0.015 0.092 0.008 0.003 0.020denkyira(d) 0.089 0.024 0.183 0.834 0.710 0.926 0.029 0.005 0.077 0.034 0.007 0.089evalue(d) 0.054 0.021 0.086 0.919 0.880 0.965 0.018 0.002 0.034 0.005 0.001 0.017fante(d) 0.294 0.263 0.335 0.461 0.431 0.490 0.015 0.011 0.020 0.209 0.179 0.246kwahu(d) 0.052 0.008 0.202 0.363 0.260 0.569 0.011 0.004 0.025 0.557 0.362 0.689nzema(d) 0.199 0.123 0.287 0.436 0.338 0.530 0.054 0.031 0.089 0.283 0.216 0.374sefwi(d) 0.597 0.563 0.631 0.311 0.280 0.343 0.005 0.001 0.010 0.062 0.037 0.089wasa(d) 0.171 0.111 0.252 0.703 0.642 0.765 0.021 0.004 0.044 0.087 0.047 0.140bawle 0.433 0.352 0.498 0.493 0.360 0.592 0.045 0.003 0.107 0.018 0.006 0.068
other akan 0.104 0.001 0.161 0.821 0.787 0.952 0.069 0.022 0.088 0.002 0.0004 0.008dangme(d) 0.476 0.384 0.573 0.295 0.217 0.378 0.016 0.010 0.026 0.180 0.132 0.234
ga(d) 0.646 0.633 0.664 0.351 0.330 0.364 0.0005 0.00003 0.002 0.001 0.0004 0.004other ga 0.040 0.027 0.063 0.233 0.016 0.491 0.659 0.441 0.872 0.016 0.004 0.050ewe(d) 0.656 0.612 0.704 0.101 0.061 0.148 0.009 0.007 0.012 0.214 0.184 0.249
guan1(d) 0.832 0.799 0.857 0.137 0.114 0.166 0.014 0.002 0.031 0.011 0.003 0.030guan2 0.674 0.646 0.701 0.291 0.251 0.329 0.028 0.001 0.065 0.004 0.001 0.011
guan3(d) 0.263 0.196 0.343 0.620 0.516 0.694 0.011 0.002 0.029 0.086 0.014 0.182guan4 0.230 0.220 0.239 0.760 0.751 0.770 0.001 0.0001 0.001 0.002 0.0005 0.003
guan5(d) 0.338 0.244 0.424 0.355 0.284 0.430 0.024 0.011 0.046 0.257 0.190 0.340guan6 0.527 0.321 0.653 0.424 0.312 0.549 0.013 0.001 0.035 0.031 0.002 0.161
guan7(d) 0.636 0.316 0.766 0.168 0.051 0.287 0.034 0.001 0.081 0.088 0.004 0.344guan8(d) 0.881 0.833 0.924 0.089 0.042 0.126 0.008 0.0001 0.033 0.010 0.001 0.040other guan 0.423 0.335 0.470 0.514 0.471 0.583 0.049 0.044 0.055 0.006 0.001 0.018
432
Table C-7. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.624 0.606 0.640 0.363 0.347 0.382 0.006 0.001 0.017 0.005 0.002 0.016kokomba(d) 0.353 0.317 0.408 0.317 0.286 0.350 0.076 0.062 0.090 0.166 0.131 0.192
basare 0.619 0.544 0.664 0.331 0.308 0.353 0.004 0.001 0.015 0.027 0.003 0.109pilapila 0.390 0.211 0.552 0.139 0.024 0.289 0.336 0.185 0.493 0.049 0.007 0.140salfalba 0.283 0.230 0.326 0.379 0.331 0.428 0.308 0.274 0.356 0.007 0.002 0.018kotokoli 0.768 0.729 0.794 0.211 0.184 0.245 0.007 0.002 0.017 0.007 0.004 0.017chamba 0.089 0.081 0.105 0.244 0.233 0.254 0.659 0.635 0.672 0.002 0.001 0.004
other gurma 0.405 0.386 0.444 0.577 0.518 0.594 0.007 0.001 0.023 0.003 0.001 0.010builsa(d) 0.249 0.196 0.317 0.406 0.352 0.457 0.138 0.107 0.230 0.159 0.106 0.244
dagarte(d) 0.486 0.423 0.554 0.098 0.070 0.136 0.031 0.022 0.043 0.307 0.260 0.357wali(d) 0.566 0.505 0.637 0.337 0.279 0.385 0.075 0.018 0.105 0.010 0.003 0.027
dagomba(d) 0.623 0.594 0.652 0.265 0.241 0.292 0.014 0.008 0.022 0.082 0.067 0.103kusasi(d) 0.675 0.597 0.723 0.082 0.046 0.132 0.051 0.034 0.065 0.174 0.125 0.225
mamprusi(d) 0.330 0.267 0.389 0.223 0.183 0.269 0.237 0.204 0.283 0.167 0.112 0.228namnam(d) 0.030 0.002 0.099 0.500 0.246 0.620 0.428 0.297 0.511 0.027 0.004 0.156nankansi(d) 0.395 0.278 0.484 0.182 0.129 0.277 0.112 0.090 0.140 0.272 0.208 0.367nanumba 0.409 0.373 0.440 0.540 0.474 0.592 0.031 0.002 0.084 0.012 0.003 0.036mosi(d) 0.476 0.445 0.497 0.490 0.470 0.509 0.026 0.002 0.049 0.004 0.002 0.008
other mole 0.322 0.098 0.469 0.605 0.463 0.857 0.034 0.008 0.132 0.026 0.002 0.187kasena(d) 0.590 0.475 0.670 0.349 0.303 0.420 0.041 0.003 0.090 0.014 0.001 0.041
mo 0.891 0.822 0.920 0.068 0.036 0.111 0.025 0.003 0.055 0.011 0.001 0.065sisala(d) 0.122 0.085 0.160 0.603 0.562 0.639 0.175 0.142 0.196 0.077 0.049 0.113vagala 0.426 0.380 0.471 0.200 0.180 0.235 0.356 0.324 0.388 0.005 0.002 0.016
othergrusi1(d) 0.522 0.479 0.558 0.431 0.387 0.463 0.035 0.018 0.061 0.007 0.002 0.030othergrusi2 0.610 0.471 0.704 0.291 0.213 0.359 0.029 0.004 0.121 0.063 0.021 0.152busanga 0.508 0.372 0.584 0.429 0.314 0.525 0.019 0.001 0.067 0.037 0.003 0.123wangara 0.191 0.169 0.209 0.779 0.755 0.802 0.025 0.009 0.044 0.003 0.001 0.005
othermande 0.112 0.014 0.194 0.547 0.468 0.640 0.304 0.243 0.347 0.016 0.003 0.034other inside 0.636 0.625 0.650 0.295 0.274 0.317 0.054 0.031 0.076 0.003 0.002 0.007other outside 0.528 0.492 0.543 0.452 0.436 0.464 0.010 0.0003 0.053 0.003 0.002 0.005Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
433
Table C-8. 2000 Presidential Runoff Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.153 0.114 0.195 0.832 0.774 0.866 0.007 0.0003 0.021 0.008 0.002 0.035ahafo 0.458 0.405 0.506 0.523 0.471 0.573 0.005 0.001 0.011 0.014 0.002 0.036
ahanta(d) 0.073 0.019 0.150 0.430 0.233 0.754 0.013 0.004 0.027 0.484 0.173 0.680akuapem 0.271 0.059 0.444 0.453 0.252 0.656 0.006 0.002 0.010 0.271 0.044 0.462akwamu 0.961 0.931 0.982 0.027 0.003 0.062 0.007 0.002 0.015 0.005 0.0004 0.021akyem(d) 0.118 0.048 0.266 0.590 0.457 0.703 0.003 0.002 0.006 0.289 0.195 0.440aowin 0.063 0.006 0.159 0.340 0.238 0.423 0.005 0.002 0.014 0.592 0.482 0.701
asante(d) 0.028 0.019 0.040 0.613 0.583 0.640 0.001 0.001 0.002 0.358 0.331 0.386asen 0.202 0.090 0.410 0.719 0.489 0.804 0.009 0.003 0.020 0.070 0.004 0.187
boron(d) 0.174 0.142 0.205 0.340 0.308 0.366 0.004 0.002 0.005 0.482 0.444 0.518chokosi 0.301 0.163 0.424 0.372 0.256 0.475 0.025 0.008 0.051 0.302 0.211 0.424denkyira 0.105 0.015 0.203 0.703 0.564 0.810 0.006 0.002 0.012 0.187 0.048 0.332evalue 0.180 0.038 0.290 0.707 0.484 0.827 0.012 0.002 0.034 0.101 0.002 0.332fante(d) 0.218 0.183 0.264 0.304 0.250 0.351 0.005 0.003 0.006 0.473 0.421 0.542kwahu(d) 0.102 0.044 0.225 0.513 0.294 0.703 0.005 0.002 0.010 0.380 0.223 0.599nzema(d) 0.145 0.073 0.244 0.219 0.163 0.293 0.008 0.004 0.014 0.627 0.527 0.709sefwi(d) 0.414 0.367 0.464 0.197 0.157 0.241 0.002 0.001 0.004 0.387 0.334 0.438wasa 0.106 0.054 0.153 0.533 0.446 0.604 0.004 0.001 0.008 0.357 0.276 0.443bawle 0.714 0.615 0.759 0.164 0.116 0.339 0.117 0.033 0.159 0.005 0.002 0.015
other akan 0.933 0.859 0.969 0.030 0.005 0.075 0.027 0.002 0.052 0.010 0.001 0.045dangme(d) 0.267 0.185 0.368 0.222 0.108 0.335 0.005 0.003 0.008 0.505 0.343 0.662
ga 0.266 0.129 0.413 0.156 0.026 0.431 0.003 0.0004 0.007 0.576 0.262 0.817other ga 0.580 0.311 0.735 0.208 0.067 0.446 0.140 0.066 0.269 0.072 0.007 0.368ewe(d) 0.440 0.409 0.470 0.127 0.056 0.193 0.007 0.006 0.008 0.426 0.348 0.514guan1 0.606 0.311 0.808 0.251 0.117 0.348 0.016 0.003 0.035 0.127 0.004 0.341guan2 0.729 0.673 0.769 0.246 0.195 0.291 0.016 0.001 0.065 0.009 0.001 0.025guan3 0.172 0.080 0.271 0.295 0.163 0.423 0.017 0.007 0.036 0.515 0.380 0.647guan4 0.077 0.009 0.224 0.801 0.370 0.977 0.006 0.001 0.018 0.116 0.006 0.421guan5 0.237 0.118 0.356 0.424 0.192 0.557 0.012 0.005 0.021 0.327 0.225 0.611guan6 0.813 0.732 0.846 0.170 0.138 0.225 0.010 0.001 0.021 0.006 0.001 0.030guan7 0.711 0.457 0.857 0.170 0.037 0.303 0.018 0.001 0.045 0.102 0.009 0.326guan8 0.938 0.685 0.990 0.019 0.001 0.117 0.013 0.002 0.036 0.029 0.001 0.246
other guan 0.177 0.064 0.348 0.744 0.524 0.882 0.037 0.009 0.116 0.042 0.007 0.119
434
Table C-8. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
bimoba 0.535 0.406 0.640 0.205 0.118 0.304 0.013 0.004 0.025 0.247 0.145 0.361kokomba(d) 0.292 0.212 0.390 0.124 0.081 0.188 0.014 0.007 0.021 0.570 0.485 0.660
basare 0.808 0.546 0.886 0.139 0.066 0.196 0.009 0.001 0.031 0.044 0.001 0.349pilapila 0.205 0.009 0.356 0.748 0.627 0.983 0.021 0.001 0.083 0.027 0.002 0.141salfalba 0.416 0.212 0.560 0.407 0.120 0.601 0.116 0.005 0.366 0.061 0.011 0.272kotokoli 0.971 0.890 0.993 0.014 0.003 0.062 0.005 0.001 0.022 0.009 0.001 0.071chamba 0.606 0.274 0.769 0.067 0.012 0.144 0.295 0.132 0.593 0.032 0.005 0.158
other gruma 0.866 0.840 0.882 0.122 0.106 0.144 0.006 0.001 0.018 0.006 0.002 0.015builsa(d) 0.451 0.202 0.571 0.208 0.155 0.272 0.023 0.004 0.052 0.319 0.210 0.530dagarte(d) 0.265 0.201 0.334 0.080 0.046 0.144 0.012 0.008 0.016 0.643 0.557 0.709
wali 0.497 0.410 0.613 0.375 0.184 0.488 0.017 0.002 0.045 0.111 0.038 0.219dagomba(d) 0.259 0.213 0.306 0.337 0.285 0.393 0.009 0.006 0.012 0.395 0.336 0.459kusasi(d) 0.368 0.280 0.450 0.165 0.058 0.285 0.009 0.003 0.016 0.458 0.330 0.613
mamprusi(d) 0.281 0.154 0.414 0.277 0.191 0.382 0.022 0.011 0.035 0.420 0.297 0.559namnam 0.439 0.277 0.635 0.451 0.212 0.611 0.030 0.006 0.043 0.081 0.006 0.285
nankansi(d) 0.193 0.150 0.241 0.349 0.244 0.418 0.013 0.007 0.019 0.446 0.377 0.559nanumba 0.232 0.140 0.326 0.603 0.478 0.691 0.038 0.010 0.057 0.127 0.040 0.243
mosi 0.391 0.182 0.490 0.585 0.499 0.802 0.007 0.001 0.027 0.017 0.004 0.051other mole 0.317 0.286 0.411 0.652 0.452 0.699 0.016 0.001 0.085 0.014 0.001 0.093kasena 0.216 0.136 0.296 0.549 0.440 0.630 0.020 0.006 0.037 0.216 0.128 0.348mo 0.014 0.0003 0.045 0.978 0.932 0.998 0.004 0.0004 0.012 0.004 0.0003 0.018
sisala(d) 0.571 0.529 0.627 0.236 0.178 0.285 0.012 0.002 0.024 0.181 0.129 0.241vagala 0.218 0.008 0.591 0.601 0.332 0.862 0.085 0.005 0.185 0.096 0.008 0.352
othergrusi1 0.354 0.133 0.689 0.135 0.036 0.267 0.035 0.016 0.062 0.476 0.179 0.744othergrusi2 0.195 0.176 0.216 0.797 0.772 0.817 0.005 0.0004 0.015 0.003 0.001 0.012busanga 0.220 0.069 0.497 0.328 0.097 0.587 0.020 0.005 0.037 0.433 0.066 0.758wangara 0.157 0.151 0.164 0.838 0.832 0.844 0.003 0.0004 0.008 0.002 0.001 0.003
othermande 0.648 0.507 0.827 0.193 0.026 0.290 0.119 0.015 0.227 0.040 0.005 0.156other inside 0.395 0.360 0.406 0.591 0.581 0.613 0.013 0.010 0.018 0.002 0.001 0.008other outside 0.511 0.491 0.526 0.477 0.429 0.492 0.005 0.0005 0.027 0.007 0.002 0.042
Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;(d) = deterministic bounds info. contributed to this group’s vote estimates
435
Table C-9. 2000 Presidential Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.118 0.108 0.137 0.814 0.788 0.826 0.067 0.060 0.076 0.001 0.0004 0.003ahafo 0.447 0.430 0.469 0.548 0.522 0.564 0.003 0.0004 0.008 0.002 0.001 0.005ahanta 0.146 0.120 0.168 0.662 0.625 0.695 0.028 0.010 0.046 0.157 0.120 0.203
akuapem 0.370 0.355 0.386 0.615 0.593 0.629 0.010 0.002 0.019 0.005 0.002 0.011akwamu 0.751 0.741 0.758 0.148 0.140 0.161 0.099 0.090 0.106 0.001 0.0003 0.002akyem(d) 0.189 0.100 0.308 0.523 0.426 0.644 0.014 0.004 0.037 0.269 0.185 0.401aowin 0.309 0.211 0.421 0.137 0.060 0.199 0.105 0.078 0.130 0.434 0.347 0.534
asante(d) 0.033 0.022 0.046 0.590 0.554 0.617 0.003 0.002 0.007 0.368 0.341 0.409asen 0.340 0.327 0.354 0.535 0.526 0.544 0.123 0.107 0.130 0.002 0.001 0.003
boron(d) 0.210 0.182 0.239 0.319 0.284 0.346 0.011 0.006 0.019 0.458 0.426 0.492chokosi 0.408 0.286 0.490 0.106 0.051 0.194 0.229 0.164 0.290 0.235 0.157 0.314denkyira 0.190 0.078 0.268 0.673 0.577 0.731 0.019 0.004 0.038 0.107 0.028 0.215evalue 0.370 0.321 0.416 0.477 0.434 0.524 0.138 0.104 0.171 0.010 0.002 0.032fante(d) 0.256 0.215 0.292 0.245 0.206 0.288 0.031 0.024 0.042 0.454 0.415 0.498kwahu(d) 0.183 0.052 0.433 0.526 0.284 0.692 0.023 0.006 0.076 0.260 0.200 0.427nzema(d) 0.118 0.081 0.162 0.284 0.156 0.355 0.069 0.038 0.118 0.511 0.449 0.627sefwi(d) 0.470 0.421 0.511 0.215 0.186 0.241 0.005 0.001 0.009 0.303 0.257 0.358wasa 0.270 0.210 0.328 0.454 0.395 0.503 0.018 0.005 0.034 0.251 0.178 0.327bawle 0.468 0.458 0.478 0.056 0.051 0.065 0.470 0.458 0.481 0.002 0.001 0.002
other akan 0.814 0.725 0.856 0.108 0.087 0.156 0.068 0.046 0.132 0.008 0.001 0.037dangme(d) 0.306 0.230 0.388 0.195 0.100 0.293 0.034 0.024 0.050 0.455 0.337 0.557
ga 0.366 0.269 0.478 0.232 0.135 0.353 0.012 0.007 0.020 0.389 0.260 0.538other ga 0.006 0.001 0.014 0.925 0.908 0.935 0.063 0.056 0.079 0.005 0.001 0.011ewe(d) 0.369 0.337 0.397 0.038 0.021 0.065 0.019 0.016 0.025 0.567 0.530 0.607guan1 0.660 0.641 0.706 0.137 0.084 0.159 0.200 0.186 0.212 0.003 0.001 0.007guan2 0.859 0.836 0.871 0.130 0.120 0.148 0.007 0.001 0.023 0.003 0.0002 0.015guan3 0.288 0.205 0.376 0.294 0.194 0.379 0.074 0.027 0.126 0.319 0.234 0.420guan4 0.255 0.157 0.329 0.454 0.347 0.547 0.043 0.013 0.082 0.227 0.146 0.327guan5 0.125 0.077 0.172 0.520 0.459 0.573 0.043 0.014 0.090 0.292 0.240 0.336guan6 0.775 0.728 0.837 0.182 0.149 0.209 0.039 0.001 0.072 0.004 0.001 0.013guan7 0.810 0.784 0.835 0.134 0.095 0.163 0.051 0.037 0.073 0.004 0.001 0.008guan8 0.518 0.287 0.769 0.160 0.049 0.257 0.046 0.015 0.089 0.274 0.041 0.495
other guan 0.379 0.288 0.425 0.292 0.256 0.359 0.321 0.284 0.348 0.007 0.002 0.016
436
Table C-9. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
bimoba 0.571 0.494 0.655 0.085 0.031 0.156 0.184 0.118 0.236 0.149 0.075 0.237kokomba(d) 0.262 0.216 0.311 0.098 0.062 0.141 0.055 0.033 0.075 0.534 0.481 0.584
basare 0.717 0.713 0.721 0.277 0.270 0.284 0.005 0.0003 0.013 0.001 0.001 0.002pilapila 0.643 0.603 0.691 0.319 0.294 0.341 0.030 0.002 0.074 0.006 0.002 0.018salfalba 0.100 0.004 0.182 0.325 0.169 0.596 0.556 0.367 0.697 0.014 0.003 0.050kotokoli 0.596 0.451 0.814 0.042 0.014 0.082 0.053 0.019 0.098 0.303 0.108 0.440chamba 0.682 0.651 0.709 0.071 0.050 0.101 0.242 0.220 0.265 0.003 0.002 0.006
other gruma 0.727 0.715 0.736 0.188 0.176 0.208 0.081 0.057 0.093 0.004 0.001 0.014builsa(d) 0.337 0.292 0.392 0.170 0.151 0.193 0.224 0.184 0.267 0.267 0.237 0.305dagarte(d) 0.216 0.181 0.254 0.060 0.030 0.125 0.047 0.035 0.061 0.658 0.601 0.706
wali 0.409 0.364 0.456 0.341 0.298 0.373 0.227 0.188 0.258 0.023 0.006 0.054dagomba(d) 0.270 0.241 0.304 0.232 0.188 0.282 0.110 0.092 0.139 0.364 0.312 0.417kusasi(d) 0.160 0.105 0.217 0.229 0.112 0.318 0.074 0.057 0.103 0.525 0.436 0.626
mamprusi(d) 0.174 0.079 0.324 0.043 0.011 0.166 0.300 0.246 0.381 0.450 0.324 0.554namnam 0.637 0.613 0.662 0.008 0.0001 0.022 0.351 0.324 0.376 0.003 0.001 0.007nankansi(d) 0.157 0.104 0.270 0.114 0.075 0.250 0.152 0.124 0.197 0.568 0.431 0.656nanumba 0.309 0.246 0.388 0.594 0.539 0.635 0.071 0.008 0.114 0.023 0.006 0.051
mosi 0.696 0.686 0.704 0.299 0.292 0.308 0.003 0.001 0.010 0.002 0.001 0.002other mole 0.283 0.263 0.316 0.508 0.440 0.545 0.199 0.179 0.226 0.009 0.001 0.036kasena(d) 0.448 0.380 0.484 0.362 0.318 0.395 0.052 0.014 0.096 0.137 0.091 0.220
mo 0.294 0.237 0.359 0.562 0.500 0.609 0.133 0.097 0.176 0.011 0.002 0.032sisala(d) 0.371 0.289 0.437 0.236 0.208 0.272 0.220 0.190 0.252 0.164 0.110 0.220vagala 0.547 0.507 0.565 0.314 0.289 0.343 0.133 0.111 0.151 0.004 0.001 0.010
othergrusi1 0.683 0.648 0.722 0.193 0.166 0.231 0.113 0.051 0.160 0.010 0.004 0.023othergrusi2 0.947 0.941 0.950 0.002 0.0002 0.005 0.050 0.047 0.055 0.001 0.0003 0.005busanga 0.750 0.727 0.766 0.236 0.226 0.251 0.006 0.001 0.018 0.007 0.002 0.020wangara 0.772 0.688 0.805 0.212 0.175 0.299 0.010 0.001 0.064 0.006 0.002 0.018
othermande 0.148 0.065 0.200 0.646 0.571 0.786 0.186 0.089 0.254 0.015 0.002 0.065other inside 0.470 0.426 0.498 0.137 0.120 0.161 0.387 0.353 0.439 0.005 0.002 0.013other outside 0.569 0.560 0.578 0.383 0.284 0.432 0.045 0.002 0.142 0.003 0.001 0.008Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
437
Table C-10. 2000 Parliamentary Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%agona(d) 0.464 0.375 0.570 0.514 0.404 0.610 0.007 0.001 0.027 0.012 0.003 0.032ahafo 0.405 0.365 0.438 0.566 0.520 0.620 0.022 0.002 0.037 0.004 0.002 0.010
ahanta(d) 0.107 0.021 0.239 0.644 0.515 0.736 0.029 0.005 0.071 0.210 0.152 0.272akuapem(d) 0.130 0.035 0.260 0.585 0.444 0.696 0.052 0.034 0.071 0.222 0.137 0.324akwamu 0.713 0.685 0.771 0.277 0.213 0.298 0.002 0.0004 0.006 0.004 0.001 0.010akyem(d) 0.221 0.123 0.338 0.569 0.448 0.651 0.015 0.005 0.026 0.192 0.128 0.269aowin(d) 0.288 0.145 0.435 0.181 0.037 0.293 0.076 0.005 0.136 0.439 0.266 0.611asante(d) 0.053 0.034 0.084 0.577 0.542 0.611 0.016 0.010 0.023 0.351 0.316 0.388asen(d) 0.223 0.083 0.317 0.632 0.525 0.760 0.014 0.003 0.028 0.112 0.019 0.251boron(d) 0.183 0.148 0.212 0.317 0.289 0.341 0.039 0.019 0.057 0.455 0.412 0.510chokosi(d) 0.410 0.238 0.549 0.046 0.017 0.082 0.194 0.106 0.288 0.309 0.186 0.474denkyira(d) 0.432 0.321 0.545 0.300 0.203 0.407 0.023 0.005 0.050 0.231 0.107 0.358evalue(d) 0.418 0.224 0.556 0.054 0.003 0.140 0.368 0.192 0.531 0.140 0.023 0.371fante(d) 0.212 0.166 0.257 0.289 0.251 0.341 0.073 0.058 0.090 0.415 0.366 0.471kwahu(d) 0.110 0.073 0.157 0.610 0.492 0.663 0.041 0.022 0.076 0.233 0.180 0.352nzema(d) 0.113 0.067 0.246 0.021 0.004 0.059 0.397 0.262 0.465 0.459 0.399 0.534sefwi(d) 0.460 0.398 0.519 0.227 0.173 0.283 0.011 0.001 0.036 0.292 0.234 0.347wasa(d) 0.164 0.102 0.226 0.454 0.366 0.559 0.095 0.024 0.146 0.282 0.192 0.374bawle 0.399 0.278 0.644 0.402 0.112 0.644 0.093 0.005 0.409 0.044 0.007 0.217
other akan 0.581 0.473 0.708 0.061 0.004 0.128 0.340 0.204 0.481 0.009 0.001 0.041dangme(d) 0.235 0.180 0.295 0.173 0.082 0.272 0.113 0.067 0.167 0.460 0.373 0.561
ga(d) 0.475 0.357 0.560 0.013 0.001 0.051 0.027 0.004 0.073 0.483 0.370 0.615other ga 0.399 0.384 0.418 0.393 0.366 0.416 0.200 0.177 0.214 0.002 0.001 0.005ewe(d) 0.320 0.288 0.368 0.049 0.030 0.073 0.099 0.085 0.112 0.525 0.459 0.565guan1(d) 0.224 0.032 0.485 0.324 0.197 0.467 0.206 0.050 0.359 0.208 0.036 0.412guan2 0.779 0.763 0.790 0.152 0.144 0.165 0.065 0.054 0.074 0.002 0.0003 0.006
guan3(d) 0.334 0.202 0.439 0.236 0.114 0.329 0.047 0.010 0.121 0.354 0.269 0.456guan4(d) 0.497 0.431 0.530 0.476 0.446 0.545 0.006 0.001 0.013 0.004 0.001 0.012guan5(d) 0.102 0.058 0.157 0.528 0.474 0.577 0.109 0.073 0.156 0.234 0.175 0.294guan6 0.626 0.594 0.655 0.060 0.037 0.085 0.303 0.275 0.333 0.005 0.0004 0.019guan7 0.981 0.919 0.994 0.009 0.002 0.052 0.003 0.0002 0.021 0.004 0.0002 0.025guan8 0.469 0.138 0.663 0.289 0.071 0.411 0.047 0.005 0.120 0.181 0.005 0.506
other guan 0.577 0.573 0.582 0.371 0.362 0.379 0.019 0.014 0.024 0.001 0.001 0.002
438
Table C-10. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
bimoba(d) 0.184 0.076 0.322 0.102 0.046 0.195 0.200 0.101 0.331 0.479 0.274 0.631kokomba(d) 0.096 0.056 0.141 0.184 0.140 0.228 0.225 0.176 0.284 0.459 0.391 0.529
basare 0.835 0.674 0.928 0.052 0.011 0.119 0.021 0.004 0.056 0.085 0.022 0.222pilapila 0.145 0.124 0.166 0.664 0.517 0.779 0.108 0.003 0.272 0.016 0.003 0.047salfalba 0.487 0.362 0.575 0.451 0.384 0.522 0.019 0.007 0.051 0.012 0.002 0.049kotokoli 0.147 0.050 0.331 0.165 0.030 0.456 0.324 0.041 0.583 0.342 0.152 0.659chamba 0.642 0.403 0.767 0.207 0.079 0.322 0.051 0.001 0.230 0.075 0.002 0.349
other gruma 0.874 0.798 0.913 0.005 0.001 0.014 0.113 0.082 0.166 0.004 0.001 0.018builsa(d) 0.502 0.406 0.606 0.113 0.041 0.169 0.147 0.130 0.178 0.207 0.167 0.253dagarte(d) 0.262 0.196 0.338 0.052 0.027 0.092 0.103 0.070 0.135 0.552 0.462 0.626
wali 0.532 0.474 0.573 0.398 0.340 0.448 0.028 0.004 0.069 0.016 0.003 0.041dagomba(d) 0.242 0.211 0.279 0.200 0.158 0.256 0.151 0.106 0.199 0.381 0.318 0.456kusasi(d) 0.134 0.065 0.246 0.267 0.138 0.365 0.138 0.107 0.163 0.436 0.349 0.580
mamprusi(d) 0.204 0.101 0.329 0.085 0.023 0.207 0.288 0.232 0.378 0.385 0.292 0.498namnam(d) 0.031 0.008 0.066 0.612 0.573 0.635 0.349 0.315 0.369 0.006 0.001 0.019nankansi(d) 0.245 0.178 0.341 0.054 0.025 0.109 0.141 0.124 0.171 0.529 0.442 0.601nanumba 0.928 0.892 0.974 0.008 0.0004 0.029 0.048 0.005 0.092 0.011 0.001 0.057
mosi 0.368 0.104 0.498 0.482 0.364 0.546 0.029 0.006 0.161 0.111 0.003 0.388other mole 0.797 0.782 0.818 0.012 0.004 0.028 0.012 0.001 0.037 0.004 0.0004 0.021kasena(d) 0.257 0.137 0.363 0.489 0.393 0.561 0.052 0.018 0.083 0.173 0.100 0.267
mo 0.158 0.020 0.400 0.245 0.058 0.458 0.244 0.045 0.492 0.297 0.089 0.572sisala(d) 0.513 0.378 0.599 0.040 0.008 0.093 0.225 0.160 0.287 0.189 0.121 0.298vagala 0.655 0.601 0.673 0.326 0.311 0.358 0.008 0.004 0.015 0.003 0.001 0.012
othergrusi1(d) 0.531 0.318 0.736 0.047 0.011 0.107 0.065 0.010 0.176 0.299 0.137 0.489othergrusi2 0.326 0.319 0.342 0.670 0.654 0.680 0.001 0.0003 0.004 0.001 0.001 0.005busanga 0.751 0.679 0.942 0.071 0.011 0.185 0.030 0.002 0.106 0.141 0.016 0.273wangara 0.757 0.710 0.778 0.005 0.0003 0.021 0.236 0.210 0.265 0.002 0.001 0.008
othermande 0.400 0.343 0.449 0.344 0.176 0.442 0.060 0.044 0.110 0.011 0.002 0.034other inside 0.350 0.083 0.521 0.064 0.019 0.165 0.083 0.022 0.293 0.429 0.251 0.602
other outside 0.996 0.996 0.997 0.003 0.002 0.003 0.0001 0.0001 0.0003 0.0002 0.0001 0.0004Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
439
Table C-11. 1996 Presidential Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.582 0.533 0.630 0.398 0.350 0.441 0.014 0.001 0.031 0.005 0.002 0.014ahafo 0.492 0.472 0.526 0.501 0.464 0.523 0.001 0.0004 0.004 0.005 0.002 0.008
ahanta(d) 0.341 0.332 0.357 0.596 0.583 0.609 0.060 0.047 0.070 0.002 0.001 0.005akuapem 0.357 0.246 0.482 0.544 0.478 0.611 0.014 0.003 0.040 0.083 0.008 0.184akwamu 0.858 0.711 0.880 0.125 0.111 0.186 0.007 0.001 0.023 0.008 0.0005 0.084akyem(d) 0.264 0.204 0.354 0.642 0.492 0.718 0.006 0.001 0.015 0.086 0.037 0.188aowin 0.492 0.396 0.606 0.151 0.100 0.221 0.012 0.006 0.022 0.344 0.244 0.438
asante(d) 0.116 0.094 0.142 0.638 0.597 0.668 0.006 0.002 0.015 0.232 0.202 0.259asen(d) 0.591 0.566 0.618 0.401 0.370 0.425 0.003 0.0004 0.008 0.004 0.001 0.009boron(d) 0.367 0.326 0.404 0.264 0.237 0.285 0.008 0.004 0.013 0.351 0.318 0.382
chokosi(d) 0.706 0.656 0.761 0.139 0.094 0.172 0.083 0.021 0.123 0.071 0.032 0.129denkyira(d) 0.555 0.494 0.606 0.415 0.325 0.454 0.005 0.001 0.014 0.023 0.004 0.103
evalue 0.348 0.240 0.429 0.557 0.365 0.667 0.030 0.0003 0.075 0.065 0.003 0.250fante(d) 0.346 0.305 0.391 0.362 0.327 0.407 0.009 0.006 0.014 0.267 0.229 0.316kwahu(d) 0.145 0.097 0.292 0.610 0.449 0.754 0.017 0.003 0.068 0.225 0.116 0.378nzema(d) 0.202 0.157 0.267 0.338 0.273 0.382 0.019 0.013 0.026 0.438 0.395 0.482sefwi(d) 0.709 0.665 0.754 0.088 0.065 0.113 0.002 0.001 0.004 0.180 0.134 0.222wasa(d) 0.312 0.216 0.396 0.494 0.432 0.563 0.008 0.003 0.015 0.165 0.082 0.251bawle 0.695 0.645 0.740 0.150 0.125 0.168 0.146 0.109 0.184 0.004 0.002 0.008
other akan 0.658 0.492 0.728 0.285 0.245 0.366 0.047 0.019 0.159 0.007 0.002 0.029dangme(d) 0.499 0.434 0.611 0.142 0.071 0.220 0.010 0.005 0.024 0.340 0.224 0.418
ga 0.517 0.400 0.683 0.312 0.237 0.397 0.018 0.002 0.043 0.152 0.039 0.307other ga 0.251 0.222 0.272 0.286 0.267 0.314 0.460 0.431 0.480 0.002 0.001 0.005ewe(d) 0.731 0.659 0.776 0.025 0.013 0.043 0.007 0.003 0.014 0.233 0.195 0.308
guan1(d) 0.853 0.838 0.863 0.140 0.131 0.154 0.006 0.004 0.008 0.001 0.0003 0.003guan2 0.997 0.988 0.999 0.0004 0.00003 0.002 0.002 0.0002 0.006 0.001 0.0001 0.006
guan3(d) 0.420 0.322 0.531 0.275 0.192 0.336 0.016 0.004 0.039 0.278 0.176 0.364guan4 0.341 0.319 0.370 0.642 0.590 0.668 0.006 0.001 0.018 0.010 0.004 0.060
guan5(d) 0.279 0.162 0.450 0.309 0.165 0.507 0.050 0.017 0.113 0.348 0.239 0.548guan6 0.872 0.867 0.876 0.124 0.120 0.129 0.002 0.0001 0.005 0.001 0.0003 0.002guan7 0.941 0.934 0.951 0.056 0.041 0.064 0.002 0.0002 0.010 0.001 0.0003 0.005guan8 0.851 0.770 0.902 0.069 0.013 0.116 0.061 0.041 0.079 0.014 0.001 0.082
other guan 0.614 0.585 0.639 0.327 0.299 0.363 0.054 0.033 0.073 0.005 0.002 0.009
440
Table C-11. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.968 0.966 0.969 0.001 0.0002 0.002 0.031 0.030 0.032 0.0002 0.0001 0.0004kokomba(d) 0.382 0.330 0.429 0.157 0.130 0.194 0.063 0.048 0.080 0.363 0.321 0.420
basare 0.810 0.801 0.818 0.187 0.178 0.194 0.002 0.0003 0.005 0.002 0.001 0.003pilapila 0.238 0.218 0.257 0.750 0.733 0.770 0.007 0.002 0.017 0.003 0.002 0.005salfalba 0.758 0.684 0.798 0.211 0.190 0.233 0.020 0.001 0.088 0.010 0.001 0.036kotokoli 0.719 0.691 0.723 0.274 0.263 0.292 0.007 0.001 0.017 0.001 0.0002 0.005chamba 0.181 0.177 0.185 0.591 0.579 0.599 0.225 0.217 0.235 0.002 0.001 0.004
other gruma 0.520 0.514 0.526 0.475 0.463 0.483 0.003 0.0002 0.018 0.002 0.001 0.003builsa(d) 0.679 0.653 0.698 0.080 0.066 0.093 0.094 0.083 0.109 0.121 0.108 0.136dagarte(d) 0.511 0.430 0.586 0.054 0.028 0.136 0.032 0.025 0.043 0.366 0.308 0.424
wali 0.662 0.597 0.718 0.089 0.058 0.125 0.232 0.152 0.268 0.014 0.003 0.038dagomba(d) 0.397 0.360 0.440 0.363 0.326 0.399 0.020 0.012 0.034 0.211 0.180 0.267kusasi(d) 0.638 0.569 0.695 0.156 0.102 0.204 0.059 0.038 0.068 0.122 0.078 0.175
mamprusi(d) 0.486 0.402 0.557 0.189 0.082 0.245 0.085 0.051 0.106 0.208 0.145 0.299namnam(d) 0.578 0.516 0.621 0.194 0.160 0.247 0.221 0.188 0.247 0.005 0.001 0.016nankansi(d) 0.522 0.428 0.586 0.084 0.059 0.131 0.081 0.071 0.101 0.247 0.198 0.339nanumba 0.693 0.676 0.707 0.299 0.286 0.315 0.005 0.002 0.008 0.003 0.001 0.007
mosi 0.543 0.515 0.554 0.444 0.434 0.475 0.011 0.002 0.016 0.002 0.001 0.006other mole 0.827 0.819 0.833 0.0005 0.0002 0.001 0.171 0.165 0.179 0.001 0.001 0.002kasena(d) 0.412 0.390 0.433 0.432 0.412 0.475 0.152 0.125 0.171 0.003 0.001 0.008
mo 0.579 0.565 0.593 0.300 0.286 0.316 0.118 0.112 0.125 0.002 0.001 0.004sisala(d) 0.470 0.422 0.519 0.228 0.207 0.257 0.177 0.145 0.202 0.098 0.059 0.143vagala 0.545 0.505 0.572 0.358 0.339 0.384 0.089 0.071 0.117 0.004 0.001 0.012
othergrusi1 0.465 0.447 0.503 0.529 0.488 0.548 0.002 0.0002 0.006 0.003 0.001 0.008othergrusi2 0.450 0.443 0.458 0.543 0.531 0.553 0.005 0.0004 0.014 0.002 0.001 0.003busanga 0.175 0.043 0.516 0.111 0.027 0.299 0.031 0.007 0.085 0.663 0.371 0.866wangara 0.374 0.367 0.379 0.624 0.619 0.630 0.001 0.0002 0.003 0.001 0.001 0.002
othermande 0.198 0.187 0.214 0.559 0.523 0.579 0.237 0.223 0.268 0.003 0.001 0.005other inside 0.386 0.313 0.448 0.451 0.392 0.517 0.155 0.149 0.162 0.007 0.003 0.012
other outside 0.860 0.853 0.871 0.093 0.071 0.102 0.044 0.038 0.057 0.002 0.001 0.005Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
441
Table C-12. 1996 Parliamentary Votes by Tribe (urban covariate, flat priors)
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%
agona 0.635 0.537 0.691 0.353 0.299 0.424 0.001 0.0001 0.007 0.008 0.0002 0.041ahafo 0.980 0.951 0.998 0.015 0.0002 0.043 0.001 0.0001 0.004 0.003 0.0001 0.019
ahanta(d) 0.375 0.198 0.547 0.140 0.089 0.236 0.107 0.014 0.170 0.374 0.192 0.537akuapem(d) 0.519 0.512 0.525 0.477 0.468 0.484 0.001 0.0002 0.002 0.004 0.001 0.008akwamu 0.999 0.997 0.999 0.001 0.0003 0.001 0.0002 0.0001 0.0004 0.0002 0.00003 0.001akyem(d) 0.263 0.204 0.331 0.546 0.358 0.634 0.050 0.030 0.082 0.137 0.060 0.280aowin 0.695 0.562 0.820 0.080 0.001 0.265 0.026 0.001 0.097 0.199 0.049 0.361
asante(d) 0.081 0.064 0.102 0.672 0.614 0.707 0.065 0.046 0.108 0.176 0.142 0.219asen(d) 0.881 0.857 0.897 0.032 0.003 0.082 0.004 0.0002 0.017 0.076 0.026 0.104boron(d) 0.345 0.309 0.382 0.303 0.256 0.337 0.033 0.014 0.053 0.309 0.259 0.353
chokosi(d) 0.709 0.637 0.758 0.025 0.002 0.061 0.103 0.030 0.187 0.161 0.051 0.242denkyira(d) 0.716 0.641 0.787 0.166 0.119 0.233 0.002 0.0004 0.011 0.105 0.032 0.174evalue(d) 0.310 0.089 0.522 0.371 0.067 0.530 0.013 0.002 0.056 0.304 0.102 0.500fante(d) 0.264 0.230 0.301 0.381 0.337 0.432 0.155 0.126 0.187 0.193 0.156 0.240kwahu(d) 0.207 0.113 0.323 0.261 0.209 0.383 0.113 0.030 0.324 0.414 0.209 0.548nzema(d) 0.440 0.368 0.486 0.010 0.001 0.040 0.138 0.101 0.207 0.409 0.336 0.458sefwi(d) 0.710 0.625 0.795 0.149 0.082 0.212 0.001 0.0002 0.002 0.137 0.061 0.214wasa(d) 0.484 0.392 0.565 0.116 0.064 0.186 0.182 0.125 0.262 0.206 0.123 0.291bawle 0.983 0.969 0.990 0.004 0.001 0.009 0.006 0.003 0.012 0.005 0.001 0.017
other akan 0.914 0.912 0.917 0.083 0.081 0.085 0.001 0.0003 0.003 0.001 0.0002 0.003dangme(d) 0.345 0.283 0.436 0.129 0.072 0.205 0.108 0.067 0.169 0.413 0.318 0.490
ga 0.808 0.759 0.877 0.170 0.065 0.233 0.003 0.0001 0.017 0.019 0.0004 0.152other ga 0.997 0.994 0.999 0.0002 0.0001 0.001 0.002 0.0005 0.003 0.001 0.0001 0.003ewe(d) 0.479 0.451 0.510 0.099 0.074 0.142 0.168 0.131 0.199 0.246 0.208 0.281guan1 0.923 0.920 0.926 0.076 0.073 0.079 0.0004 0.00004 0.002 0.0005 0.0002 0.001guan2 0.885 0.849 0.893 0.110 0.103 0.133 0.003 0.001 0.009 0.001 0.0002 0.009
guan3(d) 0.467 0.399 0.569 0.232 0.015 0.411 0.030 0.001 0.108 0.265 0.110 0.415guan4 0.296 0.130 0.414 0.155 0.070 0.304 0.091 0.012 0.169 0.456 0.348 0.588
guan5(d) 0.608 0.509 0.692 0.141 0.092 0.183 0.066 0.048 0.093 0.176 0.120 0.238guan6 0.983 0.874 1.000 0.002 0.00002 0.013 0.003 0.00003 0.018 0.012 0.00003 0.098guan7 0.998 0.995 0.999 0.001 0.0002 0.001 0.0004 0.0002 0.001 0.0005 0.00004 0.003guan8 0.999 0.998 1.000 0.0001 0.00001 0.0005 0.0003 0.00001 0.001 0.0002 0.00003 0.001
other guan 0.454 0.452 0.461 0.544 0.535 0.546 0.001 0.0002 0.001 0.001 0.0003 0.003
442
Table C-12. Continued
NDC NPP Third Party No Votetribe Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5% Mean 2.5% 97.5%bimoba(d) 0.998 0.995 0.999 0.001 0.00003 0.004 0.001 0.0001 0.001 0.0002 0.00004 0.001kokomba(d) 0.189 0.145 0.250 0.171 0.119 0.230 0.350 0.265 0.432 0.276 0.179 0.364
basare 0.926 0.901 0.949 0.072 0.050 0.096 0.001 0.0001 0.003 0.001 0.0001 0.004pilapila 0.987 0.985 0.990 0.008 0.007 0.010 0.003 0.0003 0.005 0.001 0.0002 0.002salfalba 0.997 0.996 0.998 0.0003 0.00005 0.001 0.002 0.001 0.002 0.0003 0.00002 0.001kotokoli 0.809 0.801 0.814 0.190 0.184 0.197 0.0004 0.00005 0.002 0.001 0.0002 0.003chamba 0.749 0.694 0.763 0.244 0.223 0.291 0.004 0.0002 0.030 0.002 0.0003 0.010
other gruma 0.997 0.991 0.999 0.0001 0.00003 0.0003 0.002 0.001 0.008 0.001 0.0001 0.003builsa(d) 0.763 0.748 0.778 0.015 0.002 0.020 0.113 0.107 0.117 0.093 0.079 0.107dagarte(d) 0.334 0.282 0.400 0.165 0.112 0.231 0.106 0.075 0.135 0.366 0.272 0.457
wali 0.994 0.990 0.997 0.003 0.002 0.005 0.001 0.0003 0.001 0.001 0.0002 0.005dagomba(d) 0.319 0.267 0.373 0.198 0.155 0.259 0.155 0.127 0.188 0.322 0.264 0.385kusasi(d) 0.209 0.124 0.302 0.051 0.028 0.086 0.249 0.232 0.267 0.471 0.376 0.554
mamprusi(d) 0.405 0.305 0.514 0.034 0.008 0.097 0.163 0.128 0.213 0.379 0.284 0.474namnam(d) 0.695 0.246 0.998 0.038 0.001 0.161 0.055 0.00002 0.205 0.086 0.0001 0.244nankansi(d) 0.319 0.246 0.456 0.162 0.113 0.268 0.156 0.129 0.201 0.321 0.204 0.425nanumba 0.503 0.437 0.556 0.015 0.001 0.100 0.022 0.002 0.082 0.459 0.378 0.527
mosi 0.995 0.987 0.999 0.004 0.001 0.012 0.0003 0.0001 0.001 0.001 0.0001 0.002other mole 0.359 0.152 0.588 0.281 0.065 0.559 0.031 0.006 0.102 0.319 0.127 0.636kasena(d) 0.814 0.756 0.844 0.002 0.001 0.009 0.066 0.001 0.119 0.101 0.033 0.179
mo 0.956 0.739 0.999 0.002 0.0001 0.012 0.002 0.00004 0.023 0.035 0.0001 0.209sisala(d) 0.739 0.682 0.788 0.009 0.001 0.028 0.145 0.124 0.156 0.088 0.031 0.146vagala 0.998 0.998 0.999 0.0005 0.0001 0.001 0.001 0.001 0.001 0.0001 0.00004 0.0003
othergrusi1 0.284 0.113 0.448 0.019 0.006 0.051 0.126 0.023 0.222 0.544 0.392 0.694othergrusi2 0.844 0.798 0.920 0.152 0.061 0.196 0.001 0.0001 0.006 0.003 0.0002 0.020busanga 0.999 0.999 1.000 0.0002 0.0002 0.0004 0.00004 0.00001 0.0001 0.0001 0.00004 0.0002wangara 0.823 0.781 0.836 0.174 0.162 0.212 0.001 0.0001 0.005 0.001 0.0002 0.005
othermande 0.983 0.979 0.987 0.013 0.010 0.015 0.002 0.0002 0.003 0.001 0.0001 0.002other inside 0.999 0.999 1.000 0.0004 0.0002 0.001 0.0001 0.00003 0.0001 0.0001 0.00003 0.001other outside 0.999 0.999 1.000 0.0005 0.0003 0.001 0.0001 0.0001 0.0001 0.0001 0.00001 0.0002Note: bold = spread of at least 10 points between party CIs; italics = Party CIs don’t cross over;
(d) = deterministic bounds info. contributed to this group’s vote estimates
443
APPENDIX DSURVEY: MISSING RESPONSE BIAS CHECK
Table D-1. Logit Models Missing Response Bias Check
miss- swingvoter miss-partymember
miss- familyvotes the same
miss- 2012 NDCDev.
(1) (2) (3) (4)
female -0.239 -0.065 -0.013 0.287(0.201) (0.191) (0.190) (0.214)
age -0.255∗∗∗ -0.018∗∗ -0.001 -0.005(0.020) (0.007) (0.007) (0.007)
rally -0.197 0.338∗ -0.866∗∗∗ -0.397∗
(0.198) (0.195) (0.198) (0.214)living 0.119 0.028 -0.061 0.055condition1 (0.104) (0.101) (0.102) (0.112)cell own -0.166 0.135 0.253 -0.100
(0.281) (0.262) (0.263) (0.257)water inside 0.638∗∗ 0.219 0.623∗∗ 0.181
(0.312) (0.287) (0.248) (0.338)Bosome Freho 0.371 0.229 0.802∗∗
(0.441) (0.370) (0.364)Birim South 0.134 -0.144 -1.140∗∗ -0.316
(0.428) (0.368) (0.466) (0.402)Adaklu 0.911∗∗ 0.601 -0.234 -0.833∗
(0.385) (0.314) (0.372) (0.455)Ketu South 0.767∗∗
(0.337)Mfantsiman 0.276 -0.255 0.211 -0.359
(0.408) (0.381) (0.332) (0.417)AOB 0.256 0.105 -0.012 0.230
(0.439) (0.360) (0.345) (0.380)Constant 5.257∗∗∗ -2.223∗∗∗ -2.461∗∗∗ -2.440∗∗∗
(0.672) (0.502) (0.457) (0.542)
Obs. 1,669 1,669 1,669 1,669Log Likelihood -335.659 -432.415 -422.732 -364.937AIC 695.318 888.830 869.464 753.875
Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01
444
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BIOGRAPHICAL SKETCH
Jennifer C. Boylan started her education as a student in the racially-diverse Maryland
suburbs of Washington, DC. Formally trained in Political Science and Leadership Studies at the
University of Richmond, Jennifer found her interest in domestic racial politics in the U.S. akin
to the study of ethnic divides within sub-Saharan Africa after a study abroad trip to Ghana in
2007. After college, she began graduate school within the Department of Political Science at
the University of Florida. Her research interests expanded beyond ethnic politics to include the
effects of constitutions, institutions and political parties on identity-driven divides, leading to
a dissertation on the effects of local government institutions on vote decisions in Ghana. Her
other research interests include development initiatives and local-service delivery in sub-Saharan
Africa.
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