Improving aid effectiveness in aid-dependent countries : lessons from Zambia
The Effectiveness of Foreign Aid: A Case Study of Nepal
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Transcript of The Effectiveness of Foreign Aid: A Case Study of Nepal
The Effectiveness of Foreign Aid: A Case Study of Nepal
Ph.D Thesis By
Badri Prasad Bhattarai
Thesis Submitted to UWS in Fulfilment of the Requirement for the Degree of Doctor of Philosophy
School of Economics and Finance
University of Western Sydney Sydney, Australia
University of Western Sydney August 2005
Statement of authentication
The work presented in this thesis is, to the best of my knowledge and belief, original except as acknowledged in the text. I hereby declare that I have not submitted this material either in whole or in part, for a degree at this or any other institutions.
………………………………………
Badri Prasad Bhattarai University of Western Sydney
10 August 2005
Contents
Statement of authentication………………………………………………………. iii
Acknowledgement……………………………………………………………….. iv
List of Tables…………………………………………………………………….. ix
List of Figures……………………………………………………………………. xiii
Abbreviations…………………………………………………………………….. xv
Abstract…………………………………………………………………………... xvii
Chapter 1: Introduction………………………………………………………… 1
1.1 Background…………………………………………………………………… 1
1.2 Statement of the problem……………………………………………………... 8
1.3 The scope of the present research…………………………………………….. 12
1.4 Definition of foreign aid……………………………………………………… 14
1.5 Organisation of the study…………………………………………………….. 15
Appendix 1.1 Chapter 2: An Overview of Economic and Social Development in Nepal…… 18
2.1 Introduction…………………………………………………………………… 18
2.2 Political history……………………………………………………………….. 23
2.3 History of economic policy reforms………………………………………….. 26
2.4 Growth and structural change………………………………………………… 29
2.5 Poverty………...……………………………………………………………… 33
2.6 Income distribution…………………………………………………………… 41
2.7 Employment/unemployment………………………………………………….. 42
2.8 Nepal’s poverty reduction strategy…………………………………………… 44
2.9 Policy reforms………………………………………………………………… 47
2.9.1 Foreign trade and liberalisation…………………………………………… 47
2.9.2 Financial sector development and deregulation…………………………... 52
2.9.3 Macroeconomic stability.………………………………………………….. 55
2.10 Corruption and governance reform………………………………………….. 57
2.10.1 Anti-corruption measures in Nepal……………………………………. 59
2.11 Concluding remarks………………………………………………………….. 62
vi
Chapter 3: Foreign Aid to Nepal: An Historical Perspective…………………. 65
3.1 Introduction……………………………………………………………………. 65
3.2 Significance of aid…………………………………………………………….. 67
3.3 Sources of aid…………………………………………………………………. 70
3.3.1 Japan’s aid……………………………….………………………………... 74
3.3.2 India’s aid…………………………………………………………………. 75
3.3.3 China’s aid………………………………………………………………… 77
3.3.4 The World Bank, the IMF and the ADB in Nepal………………………… 79
3.4 Sectoral distributional of aid………………………………………………….. 85
3.5 Types of aid…………………………………………………………………… 88
3.5.1 Project and program aid………………………………………………….. 88
3.5.2 Technical cooperation/assistance………………………………………… 88
3.5.3 Humanitarian and emergency aid………………………………………... 90
3.5.4 Food aid………………………………………………………………….. 91
3.6 Rationale and use of aid………………………………………………………. 91
3.6.1 Savings-investment gap…………………………………………………… 92
3.6.2 Foreign exchange gap…………………………………………………….. 93
3.6.3 Government budget deficit……………………………………………….. 94
3.7 Micro issues of foreign aid…………………………………………………… 96
3.7.1 Aid conditionality and country ownership……………………………….. 96
3.7.2 Fungibility of aid…………………………………………………………. 98
3.7.3 Coordination between donors and recipients…………………………….. 99
3.7.4 Tied aid…………………………………………………………………… 100
3.7.5 Absorptive capacity………………………………………………………. 100
3.7.6 Foreign aid policy………………………………………………………… 101
3.8 Foreign debt burden………………………………………………………….. 103
3.9 Concluding remarks………………………………………………………….. 104
Appendix 3.1
Chapter 4: Review of the Literature…………………………………………... 107
4.1 Introduction…………………………………………………………………... 107
4.2 Aid, economic growth, savings and investment……………………………… 109
4.2.1 Summary………………………………………………………………….. 150
4.3 Aid and fiscal behaviour……………………………………………………… 161
vii
4.3.1 Heller type studies of fiscal response…………………………………….. 161
4.3.2 McGuire type studies of aid fungibility…………………………………... 168
4.3.3 Other major studies of fiscal behaviour…………………………………… 174
4.3.4 Summary………………………………………………………………….. 177
4.4 Concluding remarks…………………………………………………………… 182
Chapter 5: Methodology and Data……………………………………………… 184
5.1 Introduction…………………………………………………………………… 184
5.2 Unit root tests…………………………………………………………………. 186
5.3 Test for cointegration…………………………………………………………. 188
5.3.1 The Engle-Granger (1987) approach……………………………………… 189
5.3.2 Johansen’s approach………………………………………………………. 189
5.3.3 Error correction mechanism (ECM)………………………………………. 192
5.4 Granger causality test…………………………………………………………. 193
5.5 Impulse response function…………………………………………………….. 194
5.6 Data sources and their description…………………………………………….. 197
5.6.1 Statistical summary of data and data limitations………………………….. 199
5.7 Computer programs and software…………………………………………….. 203
Chapter 6: Foreign Aid and Growth in Nepal………………………………… 204
6.1 Introduction…………………………………………………………………… 204
6.2 Model and data……………………………………………………………….. 207
6.2.1 Model specification (aid and growth)……………………………………. 207
6.2.2 Model specification (aid and policy)…………………………………….. 211
6.2.3 Data………………………………………………………………………. 214
6.3 The empirical results and their interpretations………………………………. 216
6.3.1 Unit root tests……………………………………………………………. 216
6.3.2 Cointegration and error correction mechanism………………………….. 220
6.3.3 Effectiveness of different components of aid……………………………. 231
6.4 Aid policies and per capita real GDP………………………………………... 238
6.5 Summary and conclusion……………………………………………………. 248
Appendix 6.1
viii
Chapter 7: Foreign Aid, Savings and Investment…………………………….. 252
7.1 Introduction…………………………………………………………………… 252
7.2 Foreign aid and savings-investment-a brief review of the debate……………. 256
7.3 Theoretical considerations and empirical models…………………………….. 258
7.3.1 Empirical model…………………………………………………………... 260
7.3.2 Data and methodology…………………………………………………….. 262
7.4 Unit root tests…………………………………………………………………. 265
7.5 Empirical results and interpretations…………………………………………. 267
7.5.1 Granger causality test results……………………………………………... 271
7.5.2 Generalised impulse response analysis…………………………………… 273
7.6 Summary and conclusion…………………………………………………….. 278
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour………………… 280
8.1 Introduction…………………………………………………………………… 280
8.2 Fiscal response models……………………………………………………….. 282
8.3 Data and summary statistics of the variables…………………………………. 285
8.4 Unit root test………………………………………………………………….. 286
8.5 Cointegration test results……………………………………………………… 289
8.6 Impulse response function……………………………………………………. 293
8.7 Summary and conclusion…………………………………………………….. 298
Chapter 9: Summary, Conclusion and Policy Recommendations…………… 299
9.1 Summary of findings…………………………………………………………. 300
9.1.1 Aid and per capita GDP…………………………………………………... 301
9.1.2 Aid and the savings-investment gap……………………………………… 302
9.1.3 Aid and the fiscal behaviour……………………………………………… 303
9.2 Concluding remarks…………………………………………………………... 304
9.2.1 Nepal with foreign aid……………………………………………………. 305
9.2.2 Foreign aid could be more effective……………………………………… 306
9.3 Policy recommendations……………………………………………………... 310
References
Appendix 6.2 Appendix 6.3
ix
List of Tables
Table 1.1: Average net official development assistance (ODA), 1960-2002…. 4
Table 2.1: GDP growth rates for South Asian countries, 1970-2003………… 19
Table 2.2: Per capita aid and debt services for South Asian countries,
1970-2002 ……………………………………………………………………….. 21
Table 2.3: Structure of selected South Asian economies-sectoral shares in
GDP, 1983-2002………………………………………………………………… 30
Table 2.4: Selected economic indicators of the Nepalese economy, 1966-
2003………………………………………………………………………………. 31
Table 2.5: Structure of Nepalese economy-sectoral shares in GDP, 1975-
2003………………………………………………………………………………. 32
Table 2.6: Trends in the incidence of poverty (head-count ratio), 1977-1996. 35
Table 2.7: Incidence of poverty under different poverty lines
(head-count ratio), estimated in 1989…………………………………………… 36
Table 2.8: Poverty incidence by region, 1996………………………………….. 36
Table 2.9: Poverty among caste/ethnic groups, 1995/96………………………. 37
Table 2.10: Trends of social indicators of Nepal, 1970-2002………………….. 38
Table 2.11: Social indicators for South Asian countries, 1970-2002…………. 39
Table 2.12: Trends of income distribution, 1977-1996………………………… 41
Table 2.13: Level and sources of household income, 1996……………………. 42
Table 2.14: Unemployment rates, 1999………………………………………… 44
Table 2.15: Export, import and total trade as percentage of GDP, 1970-2002. 50
Table 2.16: Average growth rates of fiscal sector indicators, 1966-2002…….. 56
Table 2.17: Control of corruption index for South Asian countries, 1996-2002 58
Table 3.1: Average total aid, bilateral and grants aid, 1960-2002……………. 66
Table 3.1A: Average aid/GDP ratios in South Asian countries, 1970-2002…. 67
Table 3.2: Average bilateral and multilateral aid, 1960-2002………………… 73
Table 3.3: Japan’s share of total bilateral aid, 1960-2002…………………….. 74
Table 3.4: India’s share of total bilateral aid, 1960-1990……………………… 75
Table 3.5: India’s aid for road projects, 1953-1985……………………………. 76
Table 3.6: China’s share of total bilateral aid, 1960-1990……………………... 77
Table 3.7: China’s aid for road projects, 1963-1990…………………………… 78
x
Table 3.8: Active projects financed by the World Bank, 1999-2004………….. 80
Table 3.9: Road and suspension bridges financed by the World Bank, 1970-
2003……..………………………………………………………………………… 80
Table 3.10: Some educational projects financed by the World Bank and
others, 1970-2003………………………………………………………………… 81
Table 3.11: IMF financial arrangements for Nepal, 1985-2003……………….. 84
Table 3.12: ADB sectoral distribution of cumulative lending as at 31 Dec
2003……………………………………………………………………………….. 85
Table 4.1: Summary of aid-growth and aid-savings empirical analyses…….. 151
Table 4.2: Summary of empirical analyses of aid and fiscal behaviour……… 178
Table 5.1 Sources of data……………………………………………………….. 198
Table 5.2: Statistical summary of data, 1970-2002……………………………. 200
Table 5.2A: Statistical summary of data, 1983-2002………………………….. 203
Table 6.1: Average growth rates of real GDP and policy variables for
South Asian countries, 1980-1990, 1991-2002 and 1970-2002……………….. 205
Table 6.2: Correlation coefficients, 1983-2002………………………………… 215
Table 6.3A: ADF test (Lag = 2) with constant and time trend, 1983-2002…... 217
Table 6.3B: ADF test (Lag = 2) with constant only, 1983-2002……………….. 218
Table 6.4A: PP test (Lag = 2) with constant and time trend, 1983-2002…….. 219
Table 6.4B: PP test (Lag = 2) with constant only, 1983-2002…………………. 220
Table 6.5: Estimate of Johansen’s Likelihood Ratio Test (variables
lnRGDPP and lnAR), 1983-2002………………………………………………. 221
Table 6.6: Estimate of Johansen’s Likelihood Ratio Test (variables
lnRGDPP, lnAR and lnKP), 1983-2002………………………………………… 223
Table 6.7A: Estimate of Johansen’s Likelihood Ratio Test (equation 6.4),
1983-2002………………………………………………………………………… 226
Table 6.7B: Estimate of Johansen’s Likelihood Ratio Test (equation 6.4
with dummy), 1983-2002……………………………………………………….. 228
Table 6.8A: Estimate of Johansen’s Likelihood Ratio Test (taking bilateral
aid only), 1983-2002……………………………………………………………. 232
Table 6.8B: Estimate of Johansen’s Likelihood Ratio Test (taking
multilateral aid only), 1983-2002………………………………………………. 233
xi
Table 6.9A: Estimate of Johansen’s Likelihood Ratio Test (taking grants
aid only), 1983-2002…………………………………………………………… 236
Table 6.9B: Estimate of Johansen’s Likelihood Ratio Test (taking loan
aid only), 1983-2002…………………………………………………………… 237
Table 6.10A: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7a),
1983-2002………………………………………………………………………. 239
Table 6.10B: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7b),
1983-2002………………………………………………………………………. 240
Table 6.10C: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7c),
1983-2002………………………………………………………………………. 241
Table 6.11A: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7d),
1983-2002………………………………………………………………………. 243
Table 6.11B: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7e,
1983-2002………………………………………………………………………. 244
Table 6.12A: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7d
with dummy), 1983-2002……………………………………………………… 246
Table 6.12B: Estimate of Johansen’s Likelihood Ratio Test (equation 6.7e
with dummy), 1983-2002……………………………………………………… 247
Table 7.1: SR, IR, AR and GAP for South Asian countries, 1970- 2002…… 255
Table 7.2: Correlation matrix in growth, 1970-2002………………………… 263
Table 7.3: ADF test (Lag = 2), 1970-2002…………………………………….. 265
Table 7.4: PP test (Lag = 2), 1970-2002………………………………………. 266
Table 7.5 ADF test for residuals for testing cointegration, 1970-2002……... 267
Table 7.6: Estimate of Johansen’s Likelihood Ratio Test (equation 7.6),
1970-2002………………………………………………………………………. 268
Table 7.7: Estimate of Johansen’s Likelihood Ratio Test (equation 7.8),
1970-2002……………………………………………………………………… 269
Table 7.8: Estimate of Johansen’s Likelihood Ratio Test (equation 7.7),
1970-2002……………………………………………………………………… 270
Table 7.9: Estimate of Johansen’s Likelihood Ratio Test (equation 7.4),
1970-2002……………………………………………………………………… 270
Table 7.10: Bivariate Granger causality test results, 1970-2002…………… 272
xii
Table 8.1: Government revenue and expenditure for South Asian
countries, as a percentage of GDP, 1975-2001………………………………... 281
Table 8.2: Correlation matrix of model variables, 1975-2002………………. 286
Table 8.2A: Correlation matrix of variables, 1975-2002……………………. 286
Table 8.3: ADF test with constant only (Lag = 2), 1975-2002……………….. 287
Table 8.3A: ADF test with constant and time trend (Lag = 2), 1975-2002…. 287
Table 8.4: PP test with constant only (Lag = 2), 1975-2002………………….. 288
Table 8.4A: PP test with constant and time trend (Lag = 2), 1975-2002……. 289
Table 8.5: Cointegrating test results (equation 8.1), 1975-2002……………... 290
Table 8.6: Cointegrating test results (equation 8.2), 1975-2002……………... 291
Table 8.7: Cointegrating test results (equation 8.3), 1975-2002……………… 292
xiii
List of Figures
Figure 3.1: Foreign aid to Nepal as percentage of GDP, 1960-2002…………... 68
Figure 3.2: Per capita aid (US$ at current prices), 1960-2002………………… 68
Figure 3.3: Foreign aid as percentage of domestic revenue, 1960-2002………. 69
Figure 3.4: Foreign aid as percentage of government expenditure, 1960-2002. 69
Figure 3.5: Sectoral distribution of aid as percentage of total aid, 1974-83….. 86
Figure 3.5A: Sectoral distribution of aid as percentage of total aid, 1984-00… 87
Figure 3.6: Technical cooperation as percentage of total aid, 1966-2002…….. 89
Figure 3.7: Emergency aid as percentage of total aid, 1995-2002…………….. 90
Figure 3.8: Food aid as percentage of total aid, 1975-2001……………………. 91
Figure 3.9: Aid and savings-investment gap as percentage of GDP, 1970-2002 92
Figure 3.10: Aid and trade balance as percentage of GDP, 1970-2002……….. 93
Figure 3.11: Budget deficit and aid as percentage of GDP, 1960-2002……….. 94
Figure 3.12: Foreign debt as percentage of GDP, 1970-2001………………….. 103
Figure 4.1: A graphical presentation of McGuire model……………………… 169
Figure 5.1: Growth rates of real GDP and foreign aid/GDP ratio, 1970-2002. 202
Figure 7.1: Trends of investment rate (IR) and saving rate (SR), 1970-2002.. 264
Figure 7.2: Trends of aid/GDP ratio (AR) and GAP (=SR-IR), 1970-2002….. 264
Figure 7.3: Generalised impulse response of DlnSR to one S.E. shock in
DlnIR……………………………………………………………………………… 274
Figure 7.4: Generalised impulse response of DlnIR to one S.E. shock in
DlnSR…………………………………………………………………………….. 275
Figure 7.5: Generalised impulse response of DlnAR to one S.E. shock in
DlnIR…………………………………………………………………………….. 275
Figure 7.6: Generalised impulse response of DlnIR to one S.E. shock in
DlnAR……………………………………………………………………………. 276
Figure 7.7: Generalised impulse response of DlnAR to one S.E. shock in
DlnSR……………………………………………………………………………. 276
Figure 7.8: Generalised impulse response of DlnSR to one S.E. shock in
DlnAR……………………………………………………………………………. 277
Figure 7.9: Generalised impulse response of DlnSR and DlnAR to one
S.E. shock in DlnIR……………………………………………………………… 277
xiv
Figure 7.10: Generalised impulse response of DlnSR and DlnIR to one
S.E. shock in DlnAR……………………………………………………………. 278
Figure 8.1A: Generalised impulse response to one S.E. shock in DlnGd……. 294
Figure 8.1B: Generalised impulse response to one S.E. shock in DlnAID…… 295
Figure 8.2A: Generalised impulse response to one S.E. shock in DlnGnd…... 295
Figure 8.3A: Generalised impulse response to one S.E. shock in DlnREV…... 297
Figure 8.3B: Generalised impulse response to one S.E. shock in DlnAID…… 297
Acknowledgements
I would like to express my sincere gratitude to all those who supported me in this work. First of all, with a deep sense of gratitude, I wish to express my sincere thanks to both my supervisors, Professor Anis Chowdhury and Dr. Girija Mallik, for their immense help in planning and executing the work in time. The confidence and dynamism with which Professor Anis Chowdhury and Dr. Girija Mallik guided the work should be no surprise to those who know them. Their company, motivation and assurances during periods of frustration will be remembered for life. Their profound knowledge of the research topic and methodology and their timely feedback and constructive guidance made it possible for me to complete this thesis on time. The cooperation I received from the administrative staff of the School of Economics & Finance is gratefully acknowledged. I would also like to thank research chairs Professor Raja Junankar and Dr. Kevin Daly for their constant encouragement and for providing me with excellent research support. I am also grateful to the School of Economics & Finance for giving me the opportunity to work as a casual tutor. This not only helped me financially, but also gave me an opportunity to sharpen my knowledge of basic economic theories and their application. The Ph.D. Completion Award from the UWS Research Office has been enormously helpful in my final year of study. This helped me to work full-time on my research and allowed me to complete the thesis on time. I would like to share this moment of happiness with my parents, brothers and other family members. My parents endured tremendous hardship to support me financially. I remain ever indebted to their kindness. I express gratitude from deep in my heart to my wife Anu (Janu) for the inspiration and moral support she provided throughout my Ph.D. Her loving support and understanding were critical in moments of doubt and frustration. I would also like to thank all my friends and colleagues who supported me directly and indirectly. They were very patient in listening to my various arguments, and provided valuable suggestions. My final word of thanks goes to Ms. Angela Damis for her excellent copy-editing. Badri Prasad Bhattarai University of Western Sydney
The Effectiveness of Foreign Aid: A Case Study of Nepal
Abstract
This thesis examines the effectiveness of foreign aid in Nepal, and adds to the growing literature on the issue of aid effectiveness. Until the mid 1960s, almost all development projects in Nepal were financed by foreign aid. Since 1970, the average aid/GDP ratio remains at over 6 per cent, and in 2002 foreign aid financed over 50 per cent of Nepal’s development expenditure. Despite the constant flow of foreign aid and decades of aid-financed development efforts in Nepal, it remains one of the poorest countries in the world, with per capita income of about US$ 243 and almost 40 per cent of the total population living in absolute poverty. A casual observer of these facts could easily conclude that foreign aid to Nepal has not been effective, though they would not be able to say what would have happened in the absence of aid. This thesis is the first rigorous study of aid effectiveness in Nepal. It examines the issue from three complementary perspectives. First, it looks at aid’s contribution to per capita GDP within the framework of the neoclassical production function. Aid is assumed to contribute to technological progress via technical assistance and importation of capital goods. Second, it examines aid’s contribution to Nepal’s gross domestic investment within a framework of the two-gap model. Since aid is channelled through the government, the thesis lastly examines the impact of foreign aid on government expenditure and revenue efforts. Our study uses time-series data for the period 1970-2002, and employs cointegration and the error correction mechanism as the estimation procedure. The results show that aid has a positive and significant relationship between per capita real GDP, savings and investment in the long-run. Fiscal response analysis indicates that more aid is spent on non-development expenditure than development expenditure and that aid does not impact negatively on revenue raising efforts. In addition, we find that aid effectiveness improves in a good policy environment, that is, one characterised by a stable macroeconomy, openness to trade and a liberalised financial sector. The study also finds that bilateral and multilateral aid are equally effective in the long-run. However, grants aid has a stronger positive association with per capita real GDP in the long-run than loans aid. Finally, the relationship between aid and per capita real GDP in the short-run is found to be negative in both aggregate and disaggregated forms. This implies that Nepal, as in the case of most other developing countries, suffers from lack of absorptive capacity and high aid volatility.
Abbreviations
ADB/AsDF Asian Development Bank/Asian Development Fund
CBS Central Bureau of Statistics
CIAA Commission for the Investigation of Abuse of Authority
CPI Consumer Price Index
DAC Development Assistance Committee
EC European Council
FDI Foreign Direct Investment
FNCCI Federation of Nepalese Chamber of Commerce and Industry
GDP Gross Domestic Product
GLS Generalised Least Squares
GNP Gross National Product
HMGN His Majesty’s Government of Nepal
IBRD International Bank for Reconstruction and Development (of the
World Bank)
IDA International Development Agency (of the World Bank)
IDS International Development Statistics, (of the OECD)
IFS International Financial Statistics, (of the IMF)
IFAD International Finance for Agricultural Development
IMF International Monetary Fund
INGO International Non-governmental Organisation
MTEF Medium Term Expenditure Framework
NBL Nepal Bank Limited
NIDC Nepal Industrial Development Corporation
NPC Nepal Planning Commission
NRB Nepal Rastra Bank
ODA Official Development Assistance
OECD Organisation for Economic Cooperation and Development
OLS Ordinary Least Squares
PRGF Poverty Reduction and Growth Facility
PRSP Poverty Reduction Strategy Paper
PRSC Poverty Reduction Support Credit
RBB Rastriya Banijya Bank
xvi
SAP Structural Adjustment Program
TPC Trade Promotion Centre
2SLS Two Stage Least Squares
3SLS Three Stage Least Squares
UK United Kingdom
UN United Nations
UNCTAD United Nations Conference on Trade and Development
UNDP United Nations Development Program
UNHCR United Nations High Commissioner for Refugee
UNICEF United Nations Children’s Fund
UNFPA United Nations Population Fund
UNTA United Nations Technical Assistance
USA United States of America
USAID United States Agency for International Development
USSR Union of Soviet Socialist Republics
VAT Value Added Tax
VDC Village Development Committee
WFP World Food Program
Chapter 1
Introduction
“…the general aim of aid (loans, grants and technical assistance) is to provide in each underdeveloped country a positive incentive for maximum national effort to increase its rate of growth. The increase in income, savings and investment which aid indirectly and directly makes possible will shorten the time it takes to achieve self-sustaining growth” (Rosenstein-Rodan, 1961: 107). “Aid is but one resource of many, and its effectiveness depends on many factors, not all of them economic or aid-related” (Cassen and Associates, 1986: 31).
“…the final answer to the [critical question of aid effectiveness depends on further research on] pressing macroeconomic and microeconomic questions surrounding foreign aid, such as whether aid can foment reforms in policies and institutions that in turn foster economic growth, whether some foreign aid delivery mechanisms work better than others, and what is the political economy of aid in both the donor and the recipient” (Easterly et al., 2003: 6).
1.1 Background
Foreign aid to developing countries has been an important source of development finance
for more than half a century.1 However, development practitioners both in donor and
recipient countries remain sceptical about the effectiveness of aid. Between 1960 and
2002, over US$ 1100 billion worth of total foreign aid flowed to the developing
countries. However, only a few countries (mainly in East and South East Asia) could
1 Foreign aid includes grants, concessional loans (with long repayment periods at very low interest rates) for development projects, and assistance for meeting humanitarian needs and emergencies. The first major, official foreign economic assistance was the Marshall Plan, designed by the United States to help war-devastated European countries during the late 1940s. Beginning in 1948 for a four-year period, the United States provided a total of over US$ 12 billion. Of the total amount more than 90 per cent was in grant form. Because of this huge amount of aid, per capita aid increased substantially during the period of aid disbursement in Western Europe. The Marshall Plan significantly contributed to the economic reconstruction of these countries. By 1950, the level of industrial production was found 25 per cent higher than in 1938 (Browne, 1990). The World Bank (the International Bank for Reconstruction and Development) was created to raise and channel long-term development funds, and it became a major source of foreign aid for most developing countries. Conceived during World War II at Bretton Woods, New Hampshire, the World Bank initially helped rebuild Europe after the war. Its first loan of US$ 250 million was to France in 1947 for post-war reconstruction. Reconstruction has remained an important focus of the World Bank’s work, given the natural disasters, humanitarian emergencies, and post conflict rehabilitation needs that affect developing and transition economies. However, it has sharpened its focus on poverty reduction as the overarching goal of all its work.
Chapter 1: Introduction
2
improve their conditions significantly. The weighted average annual GNP per capita
growth rate of low-income countries (excluding India and China) during 1965-89 was
only 1.4 per cent, and that of lower middle income was 2 per cent. The performance of
these countries worsened during the next ten years, despite an increase in aid flows. The
weighted aid/GNP ratio to low income countries (excluding India and China) increased
from 4.1 per cent in 1980 to 12.6 per cent in 1994. Yet the weighted average annual GNP
per capita growth rate in low-income countries (excluding India and China) during 1985-
95 was -1.4 per cent and that of lower middle-income countries was -1.3 per cent.2
Consequently, poverty in many of these low and lower middle-income countries
increased over the past decades as noted by the former President of the World Bank,
James Wolfensohn, “…if we take a closer look, we see something else –something
alarming. In developing countries, excluding China, at least 100 million more people are
living in poverty today than a decade ago. And the gap between rich and poor yawns
wider”.3
Numerous studies of aid effectiveness have failed to arrive at a consensus, and the above
quotations show the changing perspectives on aid and its effectiveness.4 After a brief
period of disillusionment in the late 1960s and the early 1970s about the effectiveness of
aid, there was a renewed hope that countries could be moved out of poverty through the
allocation of aid. This saw a rise in net aid flows to developing countries in real terms
until the early 1990s (White, 2004). However, disillusionment about aid effectiveness
2 Figures quoted here are from World Development Report, 1987 and 1997. 3 Foreword to Thomas et al. (2000), The quality of Growth, OUP for the World Bank. 4 The World Bank has summarised the mood in the following terms: “The complexity of social and economic change means that the impact of aid cannot be separated easily from other factors. Developing countries themselves bear most of the burdens of development, and rightly claim credit when development succeeds … Levels of development assistance are small relative to … the scale of the challenge at hand. Development aid totalled about $54 billion in 2000; this was … only a small fraction of total investment (nearly $1.5 trillion)” (World Bank, 2002a, pp. ix, xv).
Chapter 1: Introduction
3
again set-in, in the mid 1990s, with few signs of world poverty disappearing (Hudson,
2004). This has led to a decline in net aid flows both in real terms and as a percentage of
donor countries’ GNP. In nominal terms, aid flows to developing countries peaked at
US$ 62.7 billion in 1992, but fell by US$ 15 billion in the following four years to reach
US$ 47.9 billion in 1997 (White, 2004). Since then it has recovered slightly, especially
following the Asian financial crisis, but the recovery has been erratic. Aid remains a tiny
share of donor GNP, which fell from 0.35 per cent in the 1960s and 1970s to 0.2 per cent
in the 1990s, in contrast to the United Nation’s (UN) target of at least 0.7 per cent (White
and Woestman, 1994). Table 1.1 presents decade averages of aid from main donors since
1960.
Table1.1: Average net official development assistance (ODA), 1960-2002
Average net ODA at current prices (US$ million) 1960-69 1970-79 1980-89 1990-00 1960-02 DAC countries 6,088 13,760 34,860 55,137 28,681 Non-DAC bilateral donors - 3,870 4,400 1,481 2,915 Multilateral donors 450 3,721 9,251 15,896 8,155 All donors 5,722 17,038 37,945 56,039 31,122 Notes: (a) DAC = Development Assistance Committee of the Organisation for Economic Cooperation
and Development (OECD). (b) Multilateral donors = World Bank, Asian Development Bank and other regional development banks.
Source: OECD, 2004
The economic rationale of foreign aid has evolved in parallel with the evolution of
development theories. During the 1950s, economic growth was regarded as the main
policy objective in developing countries. It was believed that through economic growth,
poverty and social inequalities could be eliminated.5 Foreign aid was considered a
5 GNP growth as both the objective and yardstick of development was central in the work of early development economists such as Rosenstein-Rodan’s (1943) “big push” theory, and Rostow’s (1956) “take-off into sustained growth”.
Chapter 1: Introduction
4
necessary capital resource transfer mechanism that would result in high savings rates and
consequently self-sustained growth for developing countries. In other words, in the
1950s, aid was seen principally as a source of capital that would push economic growth
through higher investment.
During the 1960s, the concept of economic development was still dominated by GNP
growth as the main objective. Insufficient savings at an early stage and foreign exchange
(required to import capital goods) at a later stage of economic development were
identified as the key constraints on economic growth by the two-gap models developed
by Hollis Chenery and his associates. Within the framework of the two-gap models, the
role of foreign aid is supposed to boost investment by reducing the savings gap and/or the
foreign exchange gap. During the 1960s, as sectoral development processes began to be
better understood, the focus was extended to the importance of investment on human
capital and technical assistance (Thorbecke, 2000).
By the 1970s, development economists and practitioners began to realise the
shortcomings of GNP-oriented development strategies. These included concerns about
rising unemployment and inequality and a lack of progress in social developments despite
economic growth in developing countries. Thus, the primary objective of aid shifted
towards raising the standard of living of poor people through increased employment
opportunities. Changing their foreign aid strategy, the World Bank, United States Agency
for International Development (USAID) and other donors focused on anti-poverty
programs. Many investment projects were diverted from traditional sectors such as
power, transportation and telecommunication to projects in agricultural and rural
development and social services, education and health (Brown, 1990). They also placed a
Chapter 1: Introduction
5
greater emphasis on technical assistance. Particularly, in the rural areas, foreign aid was
combined into a package of capital and technical assistance projects constituting
integrated rural development programs.
The foreign debt crisis severely hit the world during the 1980s. The Mexican financial
crisis of 1982 spread to other developing countries; the magnitude of the debt crisis was
huge. These developments changed the strategy of foreign aid. Donors began to
emphasise external (balance of payments) and internal (budget) balance; these became
important objectives and necessary conditions to the restoration of economic growth and
poverty alleviation. More importantly, the World Bank and the IMF used a common
strategy, the Structural Adjustment Program, to tackle the debt crisis.
The new approach shifted aid away from a strategy of aid-financed investment towards a
strategy of aid-induced economic reforms. In other words, access to aid was made
contingent upon the adoption of an appropriate policy framework, through the imposition
of policy conditionality. Thus during the 1980s and 1990s, Stabilisation and Adjustment
Programs became the dominant objectives of aid (Browne, 1990; UNCTAD, 2000).
Under these programs, donors pushed recipient countries for the implementation of
appropriate adjustment policies through conditionality attached to program lending. The
effectiveness of conditional aid became a debatable issue in the 1990s.6
Although donors have been making great efforts to parallel aid strategies with
development doctrines since the 1950s, the effectiveness of aid is still debatable. A large
number of econometric and descriptive analyses have been conducted to measure the
6 See, for example, Oxfam (1995), Killick (1997), Kanbur (1999), and Mussa and Savastano (1999).
Chapter 1: Introduction
6
effectiveness of aid, mainly based on cross-country time-series and panel data. One of the
most influential recent studies is that of Burnside and Dollar (1997, 2000). They find that
aid can work only in a good policy environment, defined as low inflation and low or zero
budget deficits, and a liberalised economy.
The World Bank’s (1998) Assessing Aid is along the same lines as Burnside and Dollar,
and conveys three principal messages. First, aid works in a good policy environment.
Second, aid cannot buy good policy.7 Third, aid allocation does not appear to be based on
the policy environments of recipient countries. The focus therefore has been on the role
of a country’s good policy environment for making aid more effective. The cited studies
have influenced many donors to shift the focus of their aid strategies towards the good
policy environment of recipients (see Easterly, 2003). The studies have, however, been a
source of controversy among policy makers and academic researchers.
For example, using the same data set used by Burnside and Dollar (BD), Dalgaard and
Hansen (2001) show that aid spurs growth regardless of the state of a country’s policy
environment. Hansen and Tarp (2000, 2001) also find that aid increases the growth rate
but is not conditional on policy environment. While the formation of a policy index and
its interaction with aid is the main basis of the BD findings, Guillaumont and Chauvet
(2001) reveal that the interaction between aid and the policy index is found to be
insignificant. More recently, Easterly et al. (2003), employing the same methodology as
BD but with an extended data set, find that the link between aid and economic growth
does not necessarily depend on a good policy environment. Further, Easterly (2003) and
many others criticise the BD findings on a number of methodological grounds.
7 The World Bank states “in the past donor agencies have tried to ‘buy reforms’ by offering assistance to governments that were not otherwise inclined to reform. This approach failed”.
Chapter 1: Introduction
7
While these recent empirical works analyse the effectiveness of aid on growth conditional
on policy variables, they fail to explicitly recognise that aid is given primarily to the
government of a country. Any impact of aid on the economy is mediated by government
behaviour. The issue has been addressed by using fiscal response models. These models
begin with the proposition that the governments have a utility function and their basic
task is to allocate revenue among various expenditure categories, subject to a budget
constraint.8 In a developing country foreign aid is treated as another form of revenue.
There are two broad approaches to modelling fiscal responses to aid. One follows the
seminal work of Heller (1975) and the other follows McGuire (1978).
In the Heller type models, if the available revenue (aid plus domestic revenue) fails to
meet the target expenditure, then utility is not maximised. These models thus determine
the optimal level of foreign aid for a target level of expenditure given the available
domestic resources. It is assumed that a utility-maximising government tries to minimise
the loss arising out of the non-availability of necessary aid by adjusting domestic
resources or expenditure. On the other hand, if aid flows are guaranteed, the government
may either reduce its revenue (tax and domestic borrowings) efforts or increase its
expenditure targets. Studies such as Heller (1975) and others (for example, Khan and
Hoshino, 1992; Franco-Rodriguez et al., 1998; Franco-Rodriguez, 2000) find that aid
reduces government revenue efforts. By contrast, researchers such as McGillivray (2000)
find that aid has no significant impact on revenue efforts. Likewise, the findings on the
impact of aid on government expenditure are mixed.
8 The utility function of policy makers can vary. It can coincide either with economic growth, and the overall welfare of society, or with self-enrichment and power. The former regards the government or the state as benevolent. The latter is found in the work of neoclassical political economists who regard the state as a Leviathan.
Chapter 1: Introduction
8
The McGuire type models assume that governments want to maximise utility in terms of
the provision of public goods, subject to a budget constraint (aid plus domestic revenue).
The government determines the allocation of aid plus revenue among various categories
of public expenditure, which may or may not be optimal given the conditions with regard
to the use of aid. Thus, these models examine the extent of deviation of aid use from its
intended uses as stipulated in an aid document. That is, these models investigate the issue
of aid fungibility.9 They also analyse the impact of aid on government revenue. As in the
case of the Heller type models, one cannot derive any conclusive judgement about aid
fungibility and aid’s impact on revenue from the McGuire type studies. For example,
Pack and Pack, (1990 and 1993) find opposing results in the case of Indonesia and
Dominican Republic.
1.2 Statement of the problem
As indicated, aid effectiveness has been a major issue among policy makers and
researchers. After the success of the Marshall Plan, more attention was paid to the
development of developing countries. While a number of developing countries became
independent within a decade from aid dependency, others’ economic condition remained
almost the same, with slow economic growth, and in some cases, the situation turned bad
to worse. For example, in 1966 Ethiopia, India and Thailand were all considered poor
countries. By 2000, India’s per capita real income more than doubled, from US$ 187 in
1966 to US$ 462 in 2000, and its poverty rate fell from 64 per cent in 1977 to 34 per cent
in 2000 (based on income of less than US$ 1 per day). During the same period,
Thailand’s per capita income increased from US$ 609 to US$ 2720, and poverty fell from
9 Aid is said to be fungible if the recipient uses aid for purposes other than those intended by the donors.
Chapter 1: Introduction
9
over 25 per cent to 2 per cent of the population. However, in Ethiopia there was almost
no growth in per capita GDP – it hovered around US$ 115-US$ 120.10 Another two
contrasting cases are Republic of Korea (South) and Pakistan. Both had similar economic
conditions in the late 1950s and received aid amounting to about US$ 7-9 per capita
during the early 1960s. Today South Korea is a member of the OECD and Pakistan’s real
per capita GDP stands at only US$ 546 (in 2003) as opposed to Korea’s real per capita
GDP of US$ 12,332. (See appendix 1.1 for socio-economic indicators and aid flows in
selected aid-dependent countries).
In the case of Nepal, despite the constant flow of foreign aid, and decades of aid-financed
development efforts, it remains one of the poorest countries in the world and the poorest
in the South Asia, with per capita income of about US$ 243. Until the mid 1960s, almost
all development projects in Nepal were financed by foreign aid. Aid as a percentage of
GDP is still over 6 per cent, and aid still finances over 50 per cent of Nepal’s
development expenditure. Yet slow economic growth persists and almost 40 per cent of
the population lives in absolute poverty. Serious doubts about the effectiveness of aid in
Nepal have therefore arisen. A casual observer of these facts could easily draw the
conclusion that aid to Nepal has not been effective; however, they would not be able to
say what would have happened in the absence of aid. Furthermore, aid is only one factor;
there are many other factors that contribute to economic growth.
Only few attempts have been made to date to address the issue of aid effectiveness in
Nepal. For example, Mihaly (1965) and Stiller and Yadav (1979) were early studies that
10 WB/WDI online database. Data are based on constant 2000 prices. See also World Bank (1998). Note the comparison does not identify the exact factor (whether it was aid or something else such as trade) that may have contributed to higher per capita income growth and the reduction of poverty in India and Thailand. In India and Thailand aid/GNP ratios were minimal during the period (on average less than one per cent).
Chapter 1: Introduction
10
addressed the issue of foreign aid in Nepal. Based on descriptive analyses, the authors
argued that policy makers had a poor understanding of the role of aid in the Nepalese
economy. They identified lack of absorptive capacity as a main problem for the effective
utilisation of aid. However, in a regression analysis using data from 1964/65 to 1981/82,
Poudyal (1988) found positive effects of aid on the level of GDP. After almost four
decades later, Mihaly (2002) maintains that aid has not been effective in Nepal due
mainly to the lack of administrative capacity and strong political will.11
Dhakal et al. (1996) performed bivariate Granger causality tests using eight sample
countries – four each from Asia (India, Nepal Pakistan and Thailand) and Africa
(Botswana, Kenya, Malawi and Tanzania). For Nepal they used data from 1960 to 1990.
They did not find any causal relationship between foreign aid and economic growth in
Nepal. However, this study suffers from two problems. First, the authors have taken
grants only as foreign aid data and excluded concessional loans. Second, they did not
elaborate the causes of aid ineffectiveness. Instead as in other developing countries, they
simply believed that political corruption and aid diversion to importing consumption
rather than capital goods attributed to aid’s failure to impact economic growth.
In line with the earlier studies, Singh (1996) in a descriptive analysis found that foreign
aid failed to boost economic growth in Nepal. Singh pointed out that poor people did not
benefit from aid; instead the main beneficiaries of aid were high-ranking officials, ruling
politicians, contractors, and consultants. Thus, aid mainly benefited the rich, which
created inequality across the country.
11 This is the second edition of his 1965 work, Foreign Aid and Politics in Nepal.
Chapter 1: Introduction
11
Khadka (1996) examined the relationships between aid and some key macroeconomic
variables, such as savings, investment and economic growth in Nepal, for the period
1960-90. He found a positive correlation between GDP and per capita aid, which he
believed counter-intuitive given the current state of the economy. Thus, Khadka, based
on his descriptive analysis, concluded that foreign aid failed to improve levels of income,
savings and investment. However, in another study, using a simple regression analysis for
the period 1960-90, Khadka (1997) found that aid had a positive impact on the growth of
GDP. In this study, he used only bilateral disbursements for aid data and excluded
multilateral disbursements. Furthermore, he did not include any policy variables in the
model except exports and imports. Thus, the study does not provide a clear picture of aid
effectiveness in Nepal.
It is apparent that, although these studies have made some efforts in examining the issue
of aid effectiveness in Nepal, they have failed to reach a general consensus. More
importantly, they have not employed time-series econometric techniques that have been
developed recently to enhance the robustness of findings by excluding the possibility of a
spurious relationship. These studies also could not consider the long- run and short-run
dynamics of aid–growth relationship. Furthermore, they have failed to recognise
explicitly that the aid effectiveness issue should also be examined from the perspective of
fiscal behaviour as aid is ultimately channelled through the government.
Chapter 1: Introduction
12
1.3 The scope of the present research
This research is the first-known attempt to empirically investigate the issue of aid
effectiveness in Nepal by using the latest time-series econometric techniques, such as
cointegration and the error correction mechanism. The issue will be examined both at the
aggregate and disaggregated levels of aid for their impact on economic growth. In order
to enhance the understanding of the processes through which aid affects growth, the
research will also investigate the relationships between (a) aid and savings; (b) aid and
investment; and (c) aid and fiscal behaviour. It will also investigate the role of policies.
Hypotheses to be tested
Against the background of the literature survey, the following hypotheses will be tested:
(a) Aid affects growth positively through technical progress.
(b) Aid effectiveness is enhanced in a good policy environment.
(c) Aid has a positive relationship with investment.
(d) Aid leads to an increase in government domestic revenue and both development
and non-development expenditure.
There are a number of factors which can influence the relationship between aid and
economic growth. These factors include: (a) political motives of donors (see Mosley et al.,
1991 for general issues and case studies; Mihaly, 2002 and Khadka, 1997 for Nepal), (b)
corruption (see Knack, 2001 for general issues and Panday, 2001 for Nepal), (c)
misallocation of aid due to domestic politics (see Boone, 1996 and Collier and Anke, 2004
for general issues and Dhakal et al., 1996 for Nepal), (d) lack of coordination and absorptive
capacity (see Killick, 1991 for general issues and Stiller and Yadav, 1979 for Nepal), (e)
weak institutions etc (see Cassen and Associates, 1986 and 1994 for general issues and
Chapter 1: Introduction
13
Panday, 2001 for Nepal). This thesis does not intend to examine these factors that may
affect aid effectiveness. In line with many other studies, it examines aid effectiveness by
looking at aid’s impact on the most important macroeconomic variable, GDP per capita
growth. If the result is positive overall then one can assume that the micro factors were by
and large favourable. Given the data limitations, this is the best one can do econometrically.
However, we have examined three important macroeconomic factors, which may have
implications for the aid-growth relationship. They are policy environment (hypothesis (b)
above), aid’s effect on investment (hypothesis (c) above), and fiscal behaviour (hypothesis
(d) above).
Models, methodology and data
Models
The study uses a modified neoclassical production function for the analysis of the aid–
growth relationship. It is assumed that aid contributes to growth through technological
progress via technical assistance and capital imports. The analysis is augmented by
incorporating policy variables.
In the spirit of the two-gap model, the effectiveness of aid is investigated by examining the
relationships between aid and investment, and between aid and savings. We assume that
investment is influenced by both domestic savings and foreign aid.
Finally, following Heller (1975) and McGuire (1978), fiscal response models are used to
examine fiscal behaviour of governments. In particular, we investigate how aid affects
development and non-development expenditure and domestic revenue raising efforts.
Chapter 1: Introduction
14
Methodology
Since the effect of aid on economic growth and other variables in any one-year depends on
the past years aid (lagged values), it is crucial that we examine the long-run relationships
between aid and other variables of interest. Therefore, this study will use cointegration
technique, which allows us to test for the presence of a non-spurious long-run equilibrium
relationship between the variables under study. The cointegration test also involves error
correction mechanism (ECM). The ECM is considered a dynamic process in that it involves
lags of the dependent and independent variables. While it captures short-run adjustments to
changes, the long-run relationship is established in the level form. Prior to conducting the
cointegration test, we perform two unit root tests (the Augmented Dickey–Fuller and the
Phillips–Perron tests) to ensure that all variables under consideration are of the same order
of integration, in particular I(1). In addition, Granger causality test (in the case of
relationships not cointegrated) is performed.
Data
We use annual time-series data for the period 1970-2002. Data have been obtained from the
IMF, International Financial Statistics (IMF/IFS) and the OECD, International
Development Statistics (OECD/IDS) online databases. For the fiscal response models, data
have been obtained from the Statistical Year Book of Nepal (1983, 1991, 1995 and 2003).
1.4 Definition of foreign aid
According to the OECD (2004), foreign aid is defined as an official development
assistance (ODA) given to the developing countries for the promotion of economic
development and welfare including humanitarian and emergencies aid. There are two
components of foreign aid: grants and loans. Grants component of aid are free resources
Chapter 1: Introduction
15
for which no repayment is required. A loan with at least 25 per cent of grant component
is considered as foreign aid. Grants components are measured in terms of interest rate,
maturity and grace period (interval to first repayment of capital) of a loan. It measures the
concessionality of a loan in the form of the present value of an interest rate below the
market rate over the life of a loan. Conventionally, market rate is taken as 10 per cent as
DAC (Development Assistance Committee) statistics. In other words, a loan carrying an
interest rate of 10 per cent has zero grant component. Thus, if the face value of a loan is
multiplied by its grant component, the amount is considered as grant equivalent of that
loan. However, grants and loans given for military purpose are excluded from aid. This
study is also based on these definitions of aid.
1.5 Organisation of the study
This thesis is composed of nine chapters. The present chapter contains the background of
the study, statement of the problem and objectives of the study. Chapter 2 provides a
comprehensive account of Nepal’s socio-economic development. Chapter 3 discusses the
trends in and patterns of foreign aid to Nepal. Chapter 4 presents the literature review.
Chapter 5 discusses data, models and methodology in detail. The main empirical findings
are analysed in chapters 6, 7 and 8: chapter 6 contains the analysis of aid–growth
relationship within a neoclassical production framework; chapter 7 analyses the
relationship between aid and investment; and chapter 8 examines fiscal response to aid.
The study’s summary of findings, conclusions and policy recommendations are presented
in chapter 9.
Chapter 1: Introduction
16
Appendix 1.1: Socio-economic indicators for selected aid-dependent countries, (1970-2003) Country/Years 1970s 1980s 1990s 2003 Guinea-Bissau (Per capita GDP US$ 135) Aid/GNI (%) 18.65 50.24 52.07 63.65 Per capita aid (current US$) 29.3 85.74 102.94 97.50 GDP growth 3.2 2.91 1.98 0.60 Per capita GDP growth 0.1 0.23 -0.87 -2.26 Life expectancy at birth (total years) 37 - 44 45 Poverty headcount ratio, US$ 1 per day (PPP) (%) - - - - Rwanda (Per capita GDP US$ 259) Aid/GNI (%) 13.16 10.88 28.82 19.95 Per capita aid (current US$) 16.79 32.25 63.63 39.95 GDP growth 5.60 2.71 2.43 3.19 Per capita GDP growth 2.22 -0.31 -0.32 0.33 Life expectancy at birth (total years) 46 (1982) 40 (1990) 39 (2000) - Poverty headcount ratio, US$ 1 per day (PPP) (%) - 36 (1984) 52 (2000) - Nicaragua (Per capita GDP US$ 766) Aid/GNI (%) 3.83 10.79 29.45 20.06 Per capita aid (current US$) 21.46 51.34 135.46 152.04 GDP growth 1.01 -0.71 3.11 2.31 Per capita GDP growth -2.16 -3.40 0.29 -0.27 Life expectancy at birth (total years) 57(1977) - 64 (1990) 68 Poverty headcount ratio, US$ 1 per day (PPP) (%) - 47 (1993) 44 (1998) - Zambia (Per capita GDP US$ 354) Aid/GNI (%) 3.94 13.99 26.46 13.37 Per capita aid (current US$) 20.63 51.62 93.35 53.84 GDP growth 1.75 1.26 0.66 5.10 Per capita GDP growth -1.36 -1.80 -1.77 3.45 Life expectancy at birth (total years) 49 (1978) - 49 (1990) - Poverty headcount ratio, US$ 1 per day (PPP) (%) - - 65 (1991) 64 (1998) Uganda (Per capita GDP US$ 276) Aid/GNI (%) 2.38 7.45 15.79 15.56 Per capita aid (current US$) 3.39 16.86 35.15 37.95 GDP growth - 3.44 6.73 4.72 Per capita GDP growth - 0.18 3.55 1.90 Life expectancy at birth (total years) 48 (1973) - 46 (1990) 43 Poverty headcount ratio, US$ 1 per day (PPP) (%) - 88 (1989) 85 (1999) - Chad (Per capita GDP US$ 218) Aid/GNI (%) 7.87 12.77 15.20 10.57 Per capita aid (current US$) 15.52 27.42 36.19 28.77 GDP growth -1.03 5.38 1.96 11.30 Per capita GDP growth -2.98 2.66 -1.00 8.17 Life expectancy at birth (total years) 40 - 48 48 Poverty headcount ratio, US$ 1 per day (PPP) (%) - - - - Ethiopia (Per capita GDP US$ 102) Aid/GNI (%) - 8.27 12.90 22.80 Per capita aid (current US$) - 12.15 15.74 21.92 GDP growth - 2.37 3.19 -3.69 Per capita GDP growth - -0.73 0.82 -5.64
Chapter 1: Introduction
17
Life expectancy at birth (total years) - 45 (1990) - 42 Poverty headcount ratio, US$ 1 per day (PPP) (%) - 45.5 (1996) 44 (1998) - Senegal (Per capita GDP US$ 485) Aid/GNI (%) 7.57 14.00 12.38 7.00 Per capita aid (current US$) 27.61 73.51 71.00 43.00 GDP growth 2.44 2.62 3.45 6.45 Per capita GDP growth -0.44 -0.20 0.75 4.03 Life expectancy at birth (total years) 44(1977) - 49 (1990) 52 Poverty headcount ratio, US$ 1 per day (PPP) (%) - - 45 (1991) - Madagascar (Per capita GDP US$ 233) Aid/GNI (%) 3.55 8.86 13.21 10.11 Per capita aid (current US$) 8.95 24.91 31.81 31.93 GDP growth 1.5 0.36 1.61 9.79 Per capita GDP growth -1.04 -2.29 -1.24 6.82 Life expectancy at birth (total years) 46 - 53 56 Poverty headcount ratio, US$ 1 per day (PPP) (%) 49 (1980) 46 (1993) 61 (2001) - Lesotho (Per capita GDP US$ 530) Aid/GNI (%) 11.87 14.31 8.51 5.72 Per capita aid (current US$) 29.57 74.41 61.68 44.00 GDP growth 9.70 4.77 3.74 3.28 Per capita GDP growth 7.37 2.60 2.63 2.35 Life expectancy at birth (total years) 51 (1978) - 57 (1990) 37 Poverty headcount ratio, US$ 1 per day (PPP) (%) - 30 (1986) 36 (1995) - Bolivia (Per capita GDP US$ 1,017) Aid/GNI (%) 3.64 7.48 10.03 12.29 Per capita aid (current US$) 15.02 42.84 85.19 105.48 GDP growth 4.03 -0.44 3.99 2.45 Per capita GDP growth 1.55 -2.60 1.69 0.49 Life expectancy at birth (total years) 50 - 62 64 Poverty headcount ratio, US$ 1 per day (PPP) (%) - 20 (1986) 20 (1997) - Kenya (Per capita GDP US$ 341) Aid/GNI (%) 4.29 7.85 9.43 3.39 Per capita aid (current US$) 10.27 27.44 27.72 15.15 GDP growth 7.15 4.22 2.14 1.80 Per capita GDP growth 3.36 0.63 -0.50 -0.02 Life expectancy at birth (total years) 53 - 47 45 Poverty headcount ratio, US$ 1 per day (PPP) (%) - 34 (1992) 23 (1997) - Ghana (Per capita GDP US$ 275) Aid/GNI (%) 2.93 6.65 10.12 12.15 Per capita aid (current US$) 9.05 23.86 36.46 43.86 GDP growth 1.35 2.11 4.21 5.20 Per capita GDP growth -1.10 -1.09 1.67 3.31 Life expectancy at birth (total years) - 55 (1987) 60 (1997) - Poverty headcount ratio, US$ 1 per day (PPP) (%) - 46 (1987) 44(1998) - Notes: (a) All data are calculated at 10 years average except for 2003 (b) Data for life expectancy and poverty are based on a particular year such as 1977, 1979, 1986,
1988 and 1997 for each decade, if not indicated. (c) Poverty head count ratio at national poverty line is much higher in some countries. (d) Per capita GDP is reported for 2003 at constant prices 2000 for all countries.
Source: WB/WDI online database
Chapter 2
An Overview of Economic and Social Development in Nepal
“Nepal remains one of the poorest countries in the world - per capita income is about $250, around half the children under five are malnourished and progress towards Millennium Development Goal targets remains slow. Growth in the 1990s has been respectable, averaging 5 per cent but its impact on poverty has been dampened by high population growth, by being concentrated in the Kathmandu valley and the escalation of the conflict [with the Maoist insurgents] over the past two years” (World Bank, 2003b: 3).
2.1 Introduction
Nepal’s per capita income of US$ 243 makes it the 12th poorest country in the world
and the poorest in South Asia. In purchasing power parity terms Nepal is the 30th
poorest country in the world.1 According to the Census of 2001, Nepal’s total
population has reached 23.4 million, and the annual population growth rate is 2.4 per
cent. Agriculture is the main source of income: it provides a livelihood for over 80 per
cent of the population and accounts for 40 per cent of GDP (World Bank, 2003a).
Nepal is a landlocked South Asian country, lying between the two giants – India and
China. To the south, west and east is India; the north borders with China. The port
nearest to Kathmandu, the capital city of Nepal, is Calcutta (600 miles) in India.
Almost two-thirds of the total area of Nepal (147,181 square kilometres) is hills and
mountains. The highest peak in the world, Mount Everest, and other world-famous
peaks are situated in the Himalayan range on Nepal’s northern border.
Administratively, Nepal is divided into 5 Development Regions, 14 Zones, 75
Districts, 3,995 Village Development Committees (VDCs) and 36 Municipalities.
1 See further World Bank’s “Economic Update 2002”.
19
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.1: GDP growth rates for South Asian countries, 1970-2003 Year/Average growth rates 1970-75 1975-80 1980-85 1985-90 1990-95 1995-00 2003 Nepal GDP growth rate 1.96 2.22 3.77 4.79 5.13 4.57 2.98 Per capita GDP growth rate -0.05 0.14 1.57 2.45 2.66 2.09 0.74 Per capita GDP* 144 150 157 177 202 228 243 Bangladesh GDP growth rate 0.46 3.33 3.34 3.65 4.65 5.16 5.32 Per capita GDP growth rate -2.08 0.82 0.75 1.07 2.71 3.34 3.5 Per capita GDP* 236 239 254 269 295 342 410 India GDP growth rate 3.3 4.21 5.58 6.14 5.32 6.09 8.00 Per capita GDP growth rate 0.97 1.87 3.33 3.95 3.36 4.27 6.43 Per capita GDP* 210 224 247 292 343 423 525 Pakistan GDP growth rate 4.57 5.88 7.35 6.09 4.61 3.54 5.81 Per capita GDP growth rate 1.33 2.68 4.43 3.35 2.02 1.07 3.29 Per capita GDP* 271 292 353 419 476 506 537 Sri Lanka GDP growth rate 3.62 5.41 5.09 3.7 5.56 5.11 5.49 Per capita GDP growth rate 1.67 3.75 3.84 2.68 4.33 3.77 4.26 Per capita GDP* 357 412 499 576 680 824 937 Note: * US$ at 1995 prices Source: WB/WDI online database
Nepal’s per capita GDP growth has never been very encouraging. It increased
slightly, to over two per cent, in the 1980s and 1990s, perhaps due to economic and
trade liberalisation taking place in the late 1980s. Nepal’s average per capita GDP
growth rate in the last 30 years (1970-2000) has remained at around two per cent, and
thus its per capita GDP of US$ 243 is the lowest among the South Asian countries
(see Table 2.1). Despite a civil war of about 20 years’ duration, Sri Lanka has the
highest per capita income in South Asia with relatively consistent GDP growth rates,
followed by India.
Nepal is an aid-dependent country. Aid is used to finance over 50 per cent of
government development expenditures, and the aid/GDP ratio is currently about six
20
Chapter 2: An Overview of Economic and Social Development in Nepal
per cent. Among its bilateral donors, Japan has been providing the highest amount of
aid, followed by Germany, United Kingdom, Denmark and United States (particularly
since the 1980s). A substantial amount of aid is also given by India and China.
Multilateral institutions such as the Asian Development Bank (ADB), International
Development Agency (IDA), United Nations Development Program (UNDP), World
Food Program (WFP), United Nations Children Fund (UNICEF), United Nations
Technical Assistance (UNTA), United Nations High Commission for Refugees
(UNHCR) and other UN agencies are involved in promoting various sectors of the
economy.
Table 2.2 presents a comparative picture of aid dependence of Nepal and four South
Asian countries. Nepal’s dependency on foreign aid increased substantially until the
mid 1990s. Aid contributed to almost 70 per cent of its total government expenditure
(development and non-development) in the mid 1990s, compared to 34 per cent in the
mid 1970s. During the same period, per capita aid also increased from US$ 2.5 to
US$ 22. The total debt service as a percentage of Gross National Income (GNI)
increased from 0.08 per cent in the mid 1970s to almost 2 per cent in the 1990s.
Although Nepal’s external debt service is relatively low compared to other South
Asian countries, aid to Nepal as a percentage of total government expenditure is still
the highest in South Asia.
21
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.2: Per capita aid and debt services for South Asian countries, 1970-2002
Year/Country 1970-75 1975-80 1980-85 1985-90 1990-95 1995-00 2002 Nepal Aid % of total govt. expenditure 33.81 43.51 50.81 67.83 69.34 50.46 37.59 Per capita aid (current US$) 2.52 6.55 12.72 21.46 22.15 18.23 15.14 Total debt service % of GNI 0.08 0.35 0.67 1.38 1.9 1.9 1.78 Bangladesh Aid % of total govt. expenditure - 98.63 77.9 69.47 - - - Per capita aid (current US$) - 11.87 13.01 15.79 14.87 9.41 6.72 Total debt service % of GNI 0.29 1.18 1.27 1.98 1.87 1.62 1.45 India Aid % of total govt. expenditure - 9.56 6.76 3.87 4.18 2.62 2.05 Per capita aid (current US$) 1.72 2.21 2.51 2.15 2.26 1.69 1.39 Total debt service % of GNI 0.93 0.96 1.15 2.15 3.2 2.94 2.59 Pakistan Aid % of total govt. expenditure 29.8 28.43 17.06 13.44 10.55 5.98 15.18 Per capita aid (current US$) 6.39 10.37 9.76 10.52 10.09 6.15 14.79 Total debt service % of GNI 2.63 3.13 3.89 5.00 5.07 5.08 4.75 Sri Lanka Aid % of total govt. expenditure 10.24 21.94 25.98 27.15 24.59 10.00 7.59 Per capita aid (current US$) 5.80 17.98 28.5 36.45 40.71 21.96 18.01 Total debt service % of GNI 3.14 4.60 4.94 6.19 4.24 4.01 4.38 Source: WB/WDI online database
Nepal pursued an import substitution policy for a long time, through the active
participation of the public sector. Since the early 1960s, emphasis was placed on
protecting the economy from external competition. Under this policy, Nepal
established many public enterprises and protected domestic industries by imposing
high tariffs and quotas for imported goods. As in other developing countries, these
policies were a source of huge inefficiency and corruption. The public enterprises
failed to deliver efficient services and were running with huge losses, causing a
financial burden for the economy. Consequently, these policies led to lower economic
growth and macroeconomic instability.
Historically, India’s economic policies have significantly influenced the Nepalese
economy, mainly because of the free and open border between the two countries.
22
Chapter 2: An Overview of Economic and Social Development in Nepal
Even until the 1960s, 90 per cent of Nepal’s trade was limited to India, a result also of
its lack of physical infrastructure and its landlocked position. India’s economic and
trade liberalisation in the early 1990s has directly influenced Nepal to pursue almost
identical policies.
With the advent of democracy in 1991, Nepal’s government has initiated economic
reform programs to promote a modern market-oriented economy. These reforms have
included a program of privatising public enterprises and the elimination of public
monopolies in domestic air transport and hydro-power generation. Nepal has also
eliminated price controls for most products, reduced consumer subsidies and
established a convertible currency for all current account transactions. Value-added
tax has been introduced to replace the existing sales tax, for the purposes of
broadening the tax base and making the taxation system more realistic and
transparent.
Despite these reform efforts, Nepal’s underdeveloped infrastructure, unskilled human
resources, physical constraints and poor institutional capacity have all served to limit
the country’s growth. Nepal’s problems have been compounded by continued political
instability, with more than nine governments in power in the last 13 years (since
1991), and the Maoist insurgency escalating violence across the nation.
This chapter will provide a comprehensive account of socio-economic development in
Nepal. It will begin with a brief discussion of Nepal’s political history, followed by a
brief historical account of its policy regimes, as both political developments and
policy regimes have possible direct implications for economic and social
23
Chapter 2: An Overview of Economic and Social Development in Nepal
development. Detailed discussion of recent policy reforms that may have had an
impact on aid effectiveness will be provided later in the chapter.
2.2 Political history
Until 1951, Nepal had been ruled by an oligarchy known as the “Rana Regime”2 for
more than a century, leaving the country in a primitive economic condition and
isolated from rest of the world. While Nepal had never in its history been a British
colony, it was completely ruined by the Rana family. When India became independent
from colonial British rule in 1947, Nepal was greatly influenced by the achievement
of the independence movement. The Rana Regime was overthrown in 1951, and
Nepal opened the door to the rest of the world.
Since that time, Nepal made efforts to establish a multi-party political system.
Unfortunately in 1961, the 15-month old elected government was overthrown, and all
political parties were banned by the monarch of the time, King Mahendra. A party-
less political system known as the “Panchayat System” was considered more suitable
in the national interest, and was accordingly adopted.
The Panchayat system continued until the restoration of a multi-party political system
under a constitutional monarchy in 1990. The late King Birendra promulgated a new
constitution that established the multi-party system in November 1990. In the first
multi-party parliamentary election, the Nepali Congress secured the majority of seats
2 The Ranas headed the government (holding the prime ministerial position) and exercised more power than the King. In other words, the King was a lame head of state; political and administrative control remained in the hands of the Ranas.
24
Chapter 2: An Overview of Economic and Social Development in Nepal
and formed the government. With the fall of the Nepali Congress majority
government in 1994, pulled down by a faction of its own party in parliament, a period
of intense fractious politics began.
In the latest election, held in May 1999, the Nepali Congress Party won an absolute
majority in parliament and the Communist Party of Nepal–United Marxist Leninist
(CPN–UML) emerged as the main opposition party. The Nepali Congress Party
formed a majority government and K.P Bhattarai became the Prime Minister. Once
again, due to a power struggle within the Nepali Congress, K.P. Bhattarai was
replaced by G.P. Koirala in March 2000. This government lasted for just over a year;
Sher Bahadur Deuba became the next Prime Minister.
The political turmoil continued, and the royal massacre on 1 June 2001 marked a
black day in the history of Nepal. Crown Prince Dipendra shot dead 10 members of
the royal family including his parents, King Birendra and Queen Aishwarya, and his
siblings, Prince Nirajan and Princess Shruti, before killing himself. The present King
Gyanendra, the younger brother of the late King Birendra, is the head of state and
Supreme Commander of the armed forces.
Nepali politics suddenly took a new turn in May 2002 when Prime Minister Deuba
recommended to the King the dissolution of the House of Representatives, to be
followed by a fresh election on 13 November 2002. As per the Prime Minister’s
recommendation, the King dissolved the parliament. On the eve of the election, Prime
Minister Deuba suggested to the King that the election be postponed for 14 months,
on security grounds. However, this time King Gyanendra sacked Deuba on the
25
Chapter 2: An Overview of Economic and Social Development in Nepal
grounds of incompetence in holding the parliamentary elections, and temporarily took
over all executive powers. At the same time, King Gyanendra made it clear that the
government should be headed by and composed of individuals of “clean image” (that
is, not involved in corruption charges), and who would not run for the office in the
forthcoming election.
Since then, the King’s appointed Prime Minister and his cabinet have governed the
country. The first appointed Prime Minister was Lokendra Bahadur Chand. He
resigned after being in office for less than a year, and the King appointed Surya
Bahadur Thapa as the new Prime Minister. However, Surya Bahadur Thapa also
resigned after heavy pressure from his own as well as the opposition parties; he was
blamed for having failed to maintain law and order in the country. The King surprised
political observers by asking the previously sacked Prime Minster Sher Bahadur
Deuba to form a coalition government. However, on 1 February 2005 the King sacked
the coalition government for the second time, and declared a state of emergency. He
blamed again the Deuba Government’s failure to tackle the Maoist insurgency. The
King assumed power and formed a new 10-member cabinet under his direct
leadership. This has plunged the country into political turmoil.
The Maoists have been escalating violence across the country since 1996 in an
insurgency that has claimed more than 8,000 lives.3 Considerable damage has been
done to Nepal’s infrastructure. Over one-third of the country’s 3,900 Village
Development Committee buildings have been damaged or destroyed; 13 of 75
districts are without telephones; 5 hydroelectric plants are non-operational; 250 post
3 This is an estimate by the World Bank. Some other sources have put forward much higher figures.
26
Chapter 2: An Overview of Economic and Social Development in Nepal
offices have been destroyed, and 6 airports have been closed. Due to the security
situation, local and national elections have been postponed, which has in turn created
more political uncertainty (World Bank, 2003b).
When a state emergency was imposed in November 2001, it lasted nine months but
failed to stop the violence of the insurgency – the killing of innocent people and the
destruction of infrastructure. A ceasefire was announced in January 2003, offering an
opportunity for dialogue between the government and rebels. It failed, however, to
produce any conclusive solutions. In February 2005, the newly formed government
under the King’s leadership proposed unconditional dialogue with the Maoists. The
rebels rejected the proposal and so far there are no signs of any progress.4
2.3 History of economic policy reforms
During the oligarchic regime of the Ranas the country remained closed and isolated
from the rest of the world. The first opening of the economy happened with the treaty
of 1923 with the then British India, which made Nepal pursue a free-trade policy.
Some believe that imported goods from British India had a severe negative impact on
Nepal’s cottage industries (Dahal, 1987). Only limited policies aimed at economic
development were pursued. These included the establishment of the Nepal Industrial
Board, the introduction of the Nepal Company Act and the establishment of a few
match factories, cotton mills, jute mills and rice mills.
4 Nepal’s political landscape remains very uncertain. The regime has come under heavy international pressure to honour human rights and to democratise.
27
Chapter 2: An Overview of Economic and Social Development in Nepal
Nepal initiated planned economic development with the launching of the first
Development Plan in 1956. The plan mainly focused on the establishment of basic
industries, with the aim of creating employment opportunities. In line with the
dominant development philosophy of the time, in 1961 significant steps were taken
towards adopting import substitution policies. For example, legislation was
introduced to protect domestic infant industries from external competition. By the late
1960s, trade barriers and licensing systems had been adopted to protect the domestic
market (Sharma, 1999).
Until the late 1980s, Nepal continued to pursue a closed economy “dirigistic” policy
that involved the creation of public enterprises. Still, new policies were gradually
introduced. In 1982 a new industrial policy designed to increase the share of private
sector in the development of the industrial sector was introduced. At the same time,
the government adopted a policy of privatisation of public enterprises, but it was not
fully implemented.
Similarly, in 1982 the Foreign Investment and Technology Act was enacted. The
Commercial Bank Act was amended in 1984 in order to remove entry and exit
barriers. Under the financial sector reforms, the banking sector was opened to foreign
investors. As a result, in 1984 the Nepal Arab Bank Limited was established as the
first joint venture commercial bank. The commercial banks also began to accept
current and fixed deposits on foreign currencies (US dollar and Pound Sterling). In
1986, the deregulation of interest rates was initiated; this allowed commercial banks
to fix both deposit and lending rates at any level above the Central Bank’s minimum
28
Chapter 2: An Overview of Economic and Social Development in Nepal
prescribed level (Shrestha, 2004). In 1985, the Nepalese Rupee was devalued against
all foreign currencies.
Although the creation of public enterprises had almost ceased by the early 1980s, due
to widespread losses and poor performance they had already become a financial
burden to the government. The government’s involvement in public enterprises over
three decades and the over-expansion of development budgets with low revenue
mobilisation together led to budget deficits, which in turn resulted in high inflation
and unsustainable balance of payments deficits (Khatiwada et al., 2002).
Consequently, the economy faced macroeconomic instability. Thus arose the need for
restoring macroeconomic stability, structural adjustments and economic liberalisation.
An economic stabilisation program designed by the IMF was first pursued in 1985,
with subsequent graduation to a Structural Adjustment Program (SAP) in 1987.
Following the restoration of multi-party democracy in the early 1990s, a far-reaching
program of economic reforms and liberalisation has been adopted. More importantly,
these reforms measures have involved almost all sectors of the economy including
fiscal and monetary policy, trade policy, and financial policy reform.
Since the introduction of the 1987 SAP, Nepal’s macroeconomic and adjustment
policies in the 1990s were strongly influenced by the policy of conditionality applied
by aid donors. The fundamental objectives of conditionality were to reduce fiscal
deficits and to lower domestic deficit financing to less than one per cent of GDP.
These objectives were achieved through raising taxes, reducing subsidies and
29
Chapter 2: An Overview of Economic and Social Development in Nepal
transfers, minimising budgetary support to state-owned public enterprises, and
enhancing the aid absorptive capacity of the economy (see Sonali, 2003).
These programs also intended to restructure government expenditure so as to increase
the share of social sector spending in total expenditure. The full convertibility of the
Nepalese Rupee was implemented with an aim to have market driven exchange rates.
The government also initiated trade policy reforms through the elimination of import
quotas, and the restructure and reduction of tariff bands and average tariff rates.
Initiatives were also made to reform the agricultural sector.
2.4 Growth and structural change
Nepal’s economic growth has never been very encouraging as it has been severely
constrained by slow growth in the agricultural sector. Agriculture dominates the
Nepalese economy; in fact, it remains the main source of income and employment.
Although agriculture’s share in GDP is declining, it still accounts for about 40 per
cent of GDP. Low economic growth and widespread poverty have formed the general
outlook of the country, mainly due to the low productivity of the agricultural sector.
In addition, Nepal’s industrial base is very fragile. The country seriously lacks basic
infrastructure and its domestic market is limited. Its public service is inefficient and
plagued with weak institutions. In short, Nepal is plagued with growth-inhibiting
factors.
30
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.3: Structure of selected South Asian economies – sectoral shares in GDP, (%) 1983-2002
Country 1983 1993 2002 Nepal
Agriculture 60.3 42.2 40.7 Industry 12.8 20.7 21.7
Manufacturing 4.6 8.8 8.3 Service 26.9 37.1 37.5
Bangladesh Agriculture 30.7 26.3 22.7
Industry 21.9 23.8 26.4 Manufacturing 14.7 14.9 15.9
Service 47.4 49.9 50.9 India
Agriculture 36.6 31.0 22.7 Industry 25.8 26.3 26.6
Manufacturing 16.3 16.1 15.6 Service 37.6 42.8 50.7
Pakistan Agriculture 30.3 25.0 23.2
Industry 22.1 24.7 23.3 Manufacturing 15.3 16.7 16.1
Service 47.7 50.3 53.5 Sri Lanka Agriculture 28.3 24.6 20.5
Industry 26.3 25.6 26.3 Manufacturing 14.0 15.2 15.8
Service 45.4 49.7 53.2 Note: manufacturing is a part of industry Source: WB/WDI online database
Table 2.3 shows the structure of selected South Asian economies from 1983 to 2002.
It shows that that even until 1983, the agricultural sector contributed over 60 per cent
to GDP in Nepal, thereby providing a major source of income. The sector’s share in
GDP decreased to 40.7 per cent in 2002, which is still the highest among the South
Asian countries. Trade and economic liberalisation significantly contributed to the
growth of non-agriculture sector, particularly in the mid 1980s. The share of the
manufacturing sector almost doubled from 4.6 per cent in 1983 to 8.8 per cent in
1993.
31
Chapter 2: An Overview of Economic and Social Development in Nepal
Until the late 1960s, Nepal’s statistical system did not have good national account
records. By the early 1970s, only some limited data were available. Thus, an objective
assessment of Nepal’s early growth rate is not possible. As can be seen from Table
2.4, the Nepalese economy grew by around 4 per cent per annum since the mid 1960s.
The growth rate was ordinary (around 2.5 per cent) until 1980, and then picked up
following the introduction of various reform programs in the 1980s. Throughout the
1990s, the average growth rate was maintained at 5 per cent. With the recent political
uncertainty and violence, economic growth has lately begun to falter.
Table 2.4: Selected economic indicators of the Nepalese economy, 1966-2003
Average growth rate
1966-70
1971-75
1976-80
1981-85
1986-90
1991-95
1999-00
1966-00
2000 -03
Real GDP 2.7 1.8 2.4 4.9 4.8 5.1 5.0 5.0 2.7 Agriculture 2.9 1.7 -1.0 5.1 4.1 1.5 3.4 3.4 2.3 Non-agriculture
2.6 2.2 9.0 4.7 5.5 8.1 6.0 6.0 0.4
Inflation 5.1 10.5 5.2 9.7 11.6 11.3 7.9 7.9 3.3 Food 4.8 11.3 4.8 9.4 12.5 11.5 8.3 8.3 - Non-food 2.6 8.7 6.7 10.4 10.0 10.9 7.3 7.3 -
Source: Economic Survey (various issues), Ministry of Finance
An important aspect of Nepal’s growth is that the share of non-agricultural sectors in
GDP has been substantially increasing in the last twenty years. The GDP shares of the
manufacturing and industry, construction, trade, restaurant and hotels, finance and
real state sectors have all increased rapidly since the 1980s (Table 2.5).
32
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.5: Structure of Nepalese economy, sectoral shares in GDP (%), 1975-03 Sector/Fiscal Year 1975 1980 1985 1990 1995 2000 20031. Agriculture, fisheries and forestry
71.6 61.8 51.2 50.6 40.8 39.5 39.3
2. Non-agriculture 28.4 38.2 48.8 49.4 59.2 60.5 60.7 Mining and quarrying 0.1 0.2 0.4 0.5 0.5 0.5 0.5 Manufacturing and industry 4.2 4.3 5.7 6.0 9.3 9.2 8.1 Electricity, gas and water 0.2 0.3 0.4 0.5 1.4 1.6 1.8 Construction 3.7 7.2 8.5 9.0 11.0 10.2 10.4 Trade, restaurant and hotel 3.4 4.1 10.3 10.5 11.6 11.7 10.0 Transport, communications and storage
4.3 7.0 6.0 5.7 6.7 8.0 8.6
Finance and real estate 6.9 8.4 9.0 9.3 9.8 10.1 10.8 Community and social services 5.7 6.8 8.6 7.9 9.0 9.2 10.1
Total (1 + 2) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Note: There are minor differences in the figures in Tables 2.3 and 2.5 as for comparative purposes
they are taken from different sources. Source: Economic Survey (various issues), Ministry of Finance
Historically, Nepal had a moderate level of inflation, with an average rate of inflation
of about 8 per cent during 1966-2000 (see Table 2.4). The inflation rate remained low
at 5 per cent in the 1960s, but increased to over 10 per cent in the 1970s mainly due to
the international oil crisis of the period. However, while the inflation rate came down
to about 5 per cent by the early 1980s, it rose over 10 per cent in the late 1980s until
the mid 1990s, largely due to the devaluation of the Nepalese currency. As mentioned
earlier, the rise in government budget deficit also contributed to the rise in inflation
during this period. Budget deficit as a percentage of GDP increased from less than 2
per cent in the 1970s to almost 6 per cent in the 1980s (including grants). By 2001-02
the inflation rate had fallen to around 3 per cent as budget deficit declined to below 4
per cent of GDP (including grants).
In sum, although substantial progress was made in the 1990s, Nepal still remains one
of the poorest countries in the world. Economic liberalisation in the early 1990s
apparently spurred notable growth, averaging five per cent per annum in the decade.
33
Chapter 2: An Overview of Economic and Social Development in Nepal
However, growth in the past three years has been disappointing, due largely to the
Maoist insurgency and the effects of the global economic slowdown. Still widespread
poverty has persisted as the impact of growth has been dampened by high population
growth.
2.5 Poverty
Poverty is deep-rooted and widespread in Nepal. The Hindu caste system, which
categorises people primarily as either touchable or untouchable, still prevails,
determining the division of labour and work. To a large extent, the untouchable
groups of society are found to be poor, and have been exploited by touchable groups.
Despite the introduction of a number of measures against the caste system, it remains
alive in rural areas because of lack of education, the strong belief in fate held by
untouchables, and strong resistance to change from the upper castes. Poverty is, in
fact, strongly associated with castes and ethnicity.
The World Bank reported (2003a) that almost 42 per cent of the population lives in
absolute poverty and that 70 per cent have incomes of less than US$ 1.5 per day. The
most striking aspect is that there is a high regional variation in the incidence of
poverty in Nepal. Poverty is more acute and pervasive in rural areas, particularly in
the mountain regions.
No proper assessment of the poverty situation in Nepal was done until the late 1970s.
The National Planning Commission (NPC) conducted the first survey of poverty in
1977. The NPC report used a nutritional poverty line based on the income needed to
supply a minimum calorie requirement of 2,256 kilojoules per person per day. Daily
consumption of 605 grams of cereals (rice, maize, millet or wheat) and 60 grams of
34
Chapter 2: An Overview of Economic and Social Development in Nepal
pulses (lentil, black gram etc) was taken to meet this requirement. The expenditure
required to obtain that minimum level of consumption was estimated to be two
Rupees (Rs.) per person per day. The proportion of households and population living
below the poverty line was found to be higher in the far-west Development Region.
Moreover, while 17 per cent of people were found to be living below the poverty line
in urban areas, the poverty rate was more than double, 37.2 per cent, in rural areas.
The survey found that the national poverty rate was about 36 per cent.
Two more surveys were later conducted, by the Nepal Rastra Bank (NRB). These
included the 1984-85 Multi-Purpose Household Budget Survey (MPHBS), and the
1991-92 Nepal Rural Credit Survey. The MPHBS provided for different minimum per
capita daily calorie requirements to examine the incidence of poverty in the mountain
and Tarai (Plain) regions. It was fixed at 2,340 kilojoules for the hills and mountain
regions, and 2,140 kilojoules for the Tarai. The minimum per capita daily calorie
requirement was fixed at 2,250 kilojoules for the national average.
The World Bank (WB) in collaboration with the United Nations Development
Program (UNDP) carried out a survey of poverty in Nepal in 1989. This survey used a
poverty line based on the 1988-89 prices. That is, income was fixed at Rs. 210 per
person per month in the hills and Rs. 197 in the Tarai (Plain). In addition, in 1995-96,
the Nepal Living Standards Survey (NLSS) was conducted by the Central Bureau of
Statistics (CBS). This survey defined the poverty line based on a daily per capita
calorie requirement of 2,124 kilojoules. Expenditure was estimated to be Rs. 2,637
per annum; adding non-food requirements, the total minimum requirement was
estimated to be Rs. 4,404 per annum (CBS, 1996 and 1997; see also NPC, 1998). A
summary of the findings of these surveys is provided in Table 2.6.
35
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.6: Trends in the incidence of poverty (head-count ratio), 1977-1996
Population below poverty line (%) Source Year Urban Rural Nepal
NPC (2256 kj) 1977 17.0 37.2 36.2 MPHBS/ NRB (2250 kj) 1985 19.2 43.1 42.5
WB/UNDP (Income) 1989 15.0 42.0 40.0
NLSS/CBS (2124 kj) 1996 18.0 47.0 42.0
Source: NESAC, 1998
As can be seen from Table 2.6, all the surveys reveal that the poverty rate in rural
areas has been more than double the rate in urban areas. Most disturbingly, the
poverty rate in Nepal increased from 36 per cent to 42 per cent in the space of two
decades, even when a lower poverty line was used in the NLSS/CBS. This is despite
the fact that the economy grew at an average rate of 5 per cent per annum in the
1990s. This indicates that most of the increase in income has accrued to the richer or
upper castes of the society, and hence income distribution has worsened (see Table
2.12) – an issue to be discussed later.
The poverty situation in Nepal appears alarming when poverty is defined using other
measures. For example, Lipton (1983) defines poor as those who spend 70 per cent or
more on food. The World Bank used US$ 150 per capita per annum to define absolute
poor (see World Bank, 1991). In 1989, the World Bank estimated the poverty rate in
Nepal using three different poverty lines: 2,256 kilojoules (based on NPC poverty
line), US$ 150 (World Bank) and Lipton’s. The estimates of poverty according to
these measures are given in Table 2.7. As can be seen, both the Lipton and World
Bank measures give a much higher poverty rate for Nepal.
36
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.7: Incidence of poverty under different poverty lines (head-count ratio), estimated in 1989
Region (% in population) Hills Tarai (Plains) Nepal
Poverty
line Rural Urban Total Rural Urban Total Rural Urban Total
2,256 kilojoules
55 13 52 29 17 28 42 15 40
US$150 78 32 75 69 51 68 74 42 71 Lipton 65 52 64 70 50 68 68 51 66
Source: World Bank, 1991
Table 2.8 shows the incidence of poverty by region based on the Nepal Living
Standards Survey (NLSS) of 1995-96. The report reveals that the mountain regions
have the highest poverty rate (56 per cent). It also shows that the rural poverty rate is
about double the rate in urban areas. As mentioned earlier, the NLSS of 1995-96
defined the poverty line as based on a daily per capita calorie requirement of 2,124
kilojoules. Adding some essential non-food items, the incidence of poverty was
estimated at 42 per cent. A more recent estimate puts it at 38 per cent (NPC, 2001).5
Table 2.8: Poverty incidence by region, 1996
Region Population below poverty line (%)
Poor Ultra-poor Total Mountain 29.3 26.7 56.0 Hills 21.3 19.7 41.0 Tarai (Plains) 28.7 13.3 42.0 Nepal 24.9 17.1 42.0 Urban 13.2 9.8 23.0 Rural 26.4 17.6 44.0
Source: NPC, 1998
According to the 1995-96 NLSS, poverty in Nepal varies according to the various
caste/ethnic groups (see Table 2.9). The incidence of poverty is much higher among
the lower caste groups, particularly the Dalits who are untouchables (Damai, Kami
5 The NPC conducted this survey for the mid-term evaluation of the Ninth Plan (1997-2002).
37
Chapter 2: An Overview of Economic and Social Development in Nepal
and Sarki). While among the Dalits 65-68 per cent live below the poverty line, the
poverty rates among the Brahmins and Newars (two upper castes) are only 34 and 25
per cent respectively. Likewise, the poverty rate varies among the minority ethnic
groups. For example, the poverty rate is 38 per cent for the Muslims compared to 71
per cent for the Limbus and 45 per cent for the Gurungs.
Table 2.9: Poverty among caste/ethnic groups, 1995-96
Caste/Ethnicity Poverty (%) Caste/Ethnicity Poverty (%) Newar 25 Magar 58
Brahmin 34 Tamang 59
Muslim 38 Sarki 65 Gurung 45 Damai 67 Tharu 48 Kami 68
Chhetri 50 Limbu 71
Rai 56 Others 40
Source: CBS, 1997 Income poverty is not the only kind of poverty, as increase in income alone does not
necessarily represent an improvement in human development. The UNDP’s Human
Poverty Index (HPI) seeks to measure the degree of deprivation using various social
indicators such as illiteracy, malnutrition among children, life expectancy at birth,
poor health care and poor access to safe water. According to the UNDP’s Human
Development Report 2004, Nepal’s HPI value is 41.2, which ranks Nepal at 69. There
is a wide regional disparity in HPI. For example, the HPI value in rural areas is 42.0
as opposed to 25.2 in urban areas. The corresponding measure of achievements in
human capabilities, the Human Development Index (HDI) in Nepal is 0.504, which is
lower than that of India (0.595), Bhutan (0.536) and Bangladesh (0.509). Nepal’s HDI
rank is 140. Achievements in human development in Nepal also vary significantly
across regions. The HDI in the mountain regions is the lowest (0.386) followed by the
38
Chapter 2: An Overview of Economic and Social Development in Nepal
Tarai (0.478) and the hills (0.512). The central, eastern and western regions of the
country have higher HDI (0.490, 0.493 and 0.491, respectively) than the far and mid-
western regions (0.404 and 0.402, respectively).
Table 2.10: Trends of social indicators of Nepal, 1970-2002
Indicators
1970-75
1980-85
1993-98
2000
2002
Average annual population growth rate
2.4 2.6 2.2 2.3 2.3
Life expectancy (years) 43 49 58 58.9
59.9
Infant mortality rate (per 1,000 live births)
160 125 77 72 62
Under 5 mortality rate (per 1,000 children)
234 180 107 95 83
Adult literacy rate 16 22 33 41.8 44
Net primary school enrolment rate
- 60 78 - -
Access to safe water (per cent of population)
8 24 59
-
84
Note: – indicates unavailability of data Source: World Bank, 2003
Table 2.10 shows the trends of social indicators of Nepal. For example, life
expectancy increased from 43 years in the early 1970s to 59.9 years in 2002, the adult
literacy rate increased nearly threefold during the same period and the infant mortality
rate decreased, from 160 in 1970 to 62 in 2002 (see also Table 2.11). There was also a
notable increase in the access to safe water, from 8 per cent in 1970s to 84 per cent in
2002. The only discouraging figure is found for annual population growth rate, which
remained almost the same throughout the three decades.
39
Chapter 2: An Overview of Economic and Social Development in Nepal
Table 2.11: Social indicators for South Asian countries, 1970-2002
Year Life expectancy
Adult literacy
Less than US $1 per day,
% of total people
Less than US $2 per day,
% of total people
Under five
mortality rate Country at birth rate (PPP) (PPP) (per 1000)
Nepal 1970 42.36 16.36 - - 234 1980 47.95 22.4 - - 183 1990 53.57 30.44 41.81 87.47 143 2002* 59.85 44.01 39.13 80.94 83
Bangladesh 1970 44 24.5 - - - 1980 48.5 28.9 26.16 84.02 239 1990 54.7 34.2 35.8 86.4 205 2002* 62.1 41.01 36.03 82.82 73 India 1970 49.37 33.09 - - 202 1980 54.17 41.03 60.24 93.39 173 1990 59.12 49.33 48.14 91.17 123 2002* 63.38 61.3 34.7 79.9 90
Pakistan 1970 49.43 20.9 - - 177 1980 55.11 27.81 - - 156 1990 59.09 35.37 33.9 80.56 138 2002 63.81 41.45 13.36 65.56 101
Sri Lanka 1970 64.64 80.45 - - 100 1980 67.63 83.01 - - 46 1990 70.23 87.09 3.82 40.56 26 2002 73.79 92.08 - - 19
Notes: (a) * indicates that poverty data are for 2000, and some data may be one or two years back or
forward for a comparison purpose. (b) – indicates unavailability of data Source: WB/WDI online database
Although Nepal’s social indicators have showed marked progress since 1970, it still
lags far behind than other South Asian countries. For example, while the adult literacy
rate increased substantially from 16 per cent in 1970 to almost 44 per cent in 2002,
during the same period Sri Lanka’s adult literacy rate increased to over 90 per cent
(from 64 per cent in 1970) followed by India 61 per cent (from 33 per cent in 1970).
40
Chapter 2: An Overview of Economic and Social Development in Nepal
Similarly, Nepal’s life expectancy increased to almost 60 years in 2002 from 42 years
in 1970; but it is still the lowest in South Asia.
Why is Nepal behind other South Asian countries in social development despite the
fact that it received the highest aid flows in relation to its GDP?6 One may find the
answer in the political economy of aid allocation. As argued by Svensson (2000) and
Murshed and Sen (1995) recipient governments represent a variety of stake holders,
including wealthy individuals who might influence aid allocation. Boone (1996)
claimed that recipient governments divert aid to benefit the wealthy elite. These
arguments are relevant for Nepal, which has an entrenched class structure along ethnic
lines and caste system. As illustrated previously, poverty rate is the highest among the
low caste and certain ethnic groups who live mostly in the rural and mountain areas
(see Tables 2.8 and 2.9). It seems that aid did not favour the disadvantaged people in
the society.
The upper cast groups always take advantage of the poor governance and use their
local political power to capture aid financed projects. This generated more inequality
along ethnic and caste lines, and Nepal has the highest inequality in South Asia. Its
Gini-coefficient is found to be 0.57 (Table 2.12) compared to around 0.33 in
Bangladesh and Pakistan. Poverty among the low caste people and disadvantaged
rural areas has been fuelling ethnic conflicts in the country led by the Maoist
insurgents (see Murshed and Gates, 2005).
6 Aid/GDP ratio in Nepal during 1970-2002 was over 8 per cent (see Table 3.1A and Table 7.1 for detail)
41
Chapter 2: An Overview of Economic and Social Development in Nepal
2.6 Income distribution
Income distribution in Nepal is largely influenced by land ownership patterns.
Agriculture is the main source of income and the majority of people live in the rural
areas where land is the key asset. Ineffective governance has failed to eliminate the
feudal system, which has a substantial role in creating income inequality in rural areas.
The Agriculture Census of 1981 revealed that 50 per cent of households, each having
less than 0.5 hectares, owned only 7 per cent of land. On the other hand, the top 10
per cent of households, with 3 hectares and above, owned nearly 48 per cent of the
total cultivated land. Similarly, the Agriculture Census of 1991 showed that around 43
per cent of households having less than 0.5 hectares owned only 11 per cent of
cultivated land, whereas the top 10 per cent of households having 3 hectares and more
owned around 42 per cent of the total cultivated land (Sharma, 2003).
Table 2.12: Trends of income distribution (1977, 1985 and 1996) Household income share of Gini coefficient Year First 40% Next 50% Top 10% Rural Urban Nepal
1977 12.6 28.2 59.2 0.60 0.50 - 1985 23.0 54.0 23.0 0.55 0.85 0.57 1996 11.0 37.1 52.0 0.51 0.55 0.57
Source: CBS, 1996
Table 2.12 shows trends of income distribution in Nepal. In 1977, around 90 per cent
of households shared less than 41 per cent of income while the top 10 per cent shared
almost 59 per cent of household income. The share of the top 10 per cent declined
42
Chapter 2: An Overview of Economic and Social Development in Nepal
slightly to 52 per cent in 1996. However, the Gini coefficient of 0.57 indicates that
nationally, income distribution is highly skewed in favour of the rich part of society.7
There are also widespread regional disparities; the average income varies with
geography as well as location in rural or urban areas (Table 2.13). In the mountains,
the average household income is the lowest. The average household income in urban
areas is more than double the average household income in rural areas.
Table 2.13: Level and sources of household income, 1996
Income by sources (%) Region
Income per annum
(000 Rs.) Farm Non-farm Others
Mountains 32.3 62.0 18.0 20.0
Hills 45.0 58.0 24.0 18.0
Tarai (Plains) 44.5 64.0 22.0 14.0
Nepal 43.7 61.0 22.0 16.0
Rural 40.4 65.0 20.0 15.0
Urban 86.8 16.0 54.0 31.0
Source: CBS, 1997
2.7 Employment/unemployment
Employment opportunity is very limited in Nepal. Underemployment and disguised
unemployment are high and have been major problems.8 In 1977, a study conducted
by the Nepal Planning Commission indicates that the unemployment rate was 5.6 per
cent in rural and almost 6 per cent in urban areas. Underemployment was estimated to
be about 63 per cent in rural and about 45 per cent in urban areas.
7 The UNDP (2004) and the World Development Report (2000/2001) used consumption based data and reported a Gini coefficient of 0.37 in 1995-96. 8 Underemployment is generally defined as those who work less then 40 hours a week.
43
Chapter 2: An Overview of Economic and Social Development in Nepal
Similarly, in 1981 a study conducted by the Asian Regional Team for Employment
Production revealed that unemployment and underemployment rates ranged from 21
to 28 per cent in the Tarai (Plains) and from 37 to 47 per cent in the hills respectively.
Underemployment in the country was reported to range from 25 to 40 per cent in
1987, while the unemployment rate stood at 5 per cent (Library of Congress, 1991).
According to the Census of 1991, the economically active population was found to be
56.6 per cent. Of the 10-14 and 15-59 year age groups, 22.9 and 67.9 per cent
respectively were found to be economically active (CBS, 1991).
The Central Bureau of Statistics (CBS) carried out the Nepal Labour Force Survey in
1998-99. According to this survey, the economically active population in the age
group 15 and above was 85.8 per cent. The survey further showed that out of a labour
force of 11.2 million (aged 15 years and above), 9.6 million people were found to be
active in the labour market. Since 178,000 were found to be unemployed, the total
number of employed workers was estimated at 9.46 million. The survey also reported
that out of 4.9 million children (in the age group of 5-14 years), 2.6 million were
involved in the labour market (CBS, 1999) showing a very high incidence of child
labour.
Out of 9.46 million in employment, 7.2 million were engaged in agricultural
employment, which shows the dominance of agriculture. Until 2001, 66 per cent of
the economically active population was involved in agriculture (CBS, 2001). The
second category of employment is elementary occupation, which includes
manufacturing, construction, transport, porters, domestic workers and street vendors,
along with firewood collection and water fetching. The CBS survey (1999) reported
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Chapter 2: An Overview of Economic and Social Development in Nepal
that 1.5 million were paid employees in various sectors, and 4.1 million were unpaid
family workers, while 3.8 million were self-employed.
Table 2.14: Unemployment rates in’000 and %, 1999
Areas Urban Rural Nepal
Total 77 (7.9%) 101 (1.2%) 178 (1.8%)
Male 35 (5.9%) 63 (1.5%) 98 (2%) Female 42 (9.4%) 37 (0.9%) 80 (1.7%)
Source: CBS, 1999
One of the evident weaknesses of these survey reports is that there is no consistent
definition of work (that is, employment), and hence the actual picture of
unemployment and employment could be misleading. For example, some activities
such as fetching water and collecting firewood (for cooking) are counted as an
economically productive activity. In Nepal these kinds of activities are not related to
employment; instead they reflect the minimum survival conditions of people. Thus,
the figures in Table 2.14 are to some extent misleading and do not provide the real
picture of the unemployment situation of the country.
2.8 Nepal’s poverty reduction strategy
As noted earlier, despite remarkable economic growth in the 1990s and significant
progress in social indicators such as infant and child mortality, literacy, and life
expectancy, Nepal remains one of the poorest countries in the world. Widespread
poverty persists and large inequalities prevail across ethnic groups. To cope with the
problem, the Poverty Reduction Strategy Paper (PRSP) was prepared as part of the
45
Chapter 2: An Overview of Economic and Social Development in Nepal
Tenth Plan (2002-03 to 2006-07).9 Nepal identified four key pillars for the PRSP in
the Tenth Plan: (1) generating economic growth; (2) improving service delivery; (3)
promoting social inclusion; (4) improving governance (NPC, 2003). At the same time,
the Medium Term Expenditure Framework (MTEF) was prepared to help implement
the Tenth Plan effectively, by prioritising expenditure and managing public resources
more efficiently.10
The preparation of the MTEF was an important effort by the government to reorganise
the public expenditure program in order to achieve poverty reduction as targeted in
the Tenth Plan, within a realistic medium-term budget structure. Thus, the MTEF
indicates a strong country ownership with the formulation of its own strategy and
national priorities.11 In other words, it was a national response to those donors
concerned about Nepal’s lack of appropriate policies for the management of
development priorities and aid resources.
Donor responses to the PRSP were positive, particularly those of the World Bank and
other multilateral donors. In October 2003, to support the implementation of the
PRSP, the World Bank (via IDA) provided US$ 70 million credit to Nepal, to be
followed by further instalments. The IMF also expressed appreciation for Nepal’s
9 The PRSP must be approved by the joint board of the World Bank and the IMF for a country to be eligible for soft loans from these institutions. 10 The PRSP/Tenth Plan was prepared in mid 2001 (NPC, 2003). The Tenth Plan itself was considered as a comprehensive Poverty Reduction Strategy, while the MTEF, established in November 2001, was intended as a “complementary” tool in the implementation of the Tenth Plan. The Tenth Plan was a departure from previous development plans, which had little involvement of stakeholders other than the government. This led the NPC to note: “A major deficiency of Nepal’s planning and budgeting process has been the over-optimism of five-year plans and annual budgets in relation to both resource availability and implementation capacity…Lack of effective prioritisation of programs and expenditures related to planned goals and objectives have also led to wide gaps in plans and actual achievements. The MTEF aims at correcting these persisting problems…” (NPC, 2003: 2). 11 See NPC (2003, 2004) for a review and detailed discussion of the first, second and third MTEFs.
46
Chapter 2: An Overview of Economic and Social Development in Nepal
formulation of the PRSP and recognised the government’s intention to strengthen the
participatory approach for the implementation and monitoring stages of the PRSP. It
agreed to help Nepal achieve the goals of the PRSP under the Poverty Reduction and
Growth Facility Program, approving US$ 72 million in November 2003.
However, these key donors stressed the need for further reforms to reduce the
pervasive poverty in Nepal. The World Bank’s first Poverty Reduction Strategy
Credit was based on a number of conditions, such as dropping 160 projects to
reduce/and prioritise development budgets, increasing the price of petroleum product
to cover losses, and prosecuting high-profile corruption cases (World Bank, 2003b).
Further, the IMF placed conditions on the use of its fund. For example, the
government was to meet revenue targets and resist spending pressures. It had to apply
tough measures such as cuts in exemptions, improvements in tax and custom
administration, and an increase in the value-added tax rate. The IMF noted that much
still remains to be done in the financial sector, and in the area of privatisation and
restructuring of public enterprises (IMF, 2003a).
Although it is too early to evaluate the effectiveness of the PRSP, the review of the
first and second MTEFs shows encouraging results in terms of restructuring and
managing the government budget. The government, for instance, claims that the
macroeconomic objectives of the Tenth Plan have been more realistic than previous
plans. The Tenth Plan/PRSP represents a broad strategy for poverty reduction with
many aspects, focusing, as it does, on areas such as growth (particularly in rural
areas), social inclusion, improved governance, and better delivery of social and
economic services.
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Chapter 2: An Overview of Economic and Social Development in Nepal
2.9 Policy reforms
This section provides a detailed discussion of policy reform measures in Nepal. In
particular, it looks at reforms in three areas: trade, the financial sector and
macroeconomic stability. Policies operating in these areas are claimed to have direct
impacts on aid effectiveness.
2.9.1 Foreign trade and liberalisation
In the past Nepal’s trade base was very narrow and limited to trade with India and
Tibet. Nepal pursued a restrictive trade policy until the mid 1980s, for the purposes of
promoting import substitution industrialisation and the growth of infant industries.
While restrictive trade policies failed to promote industrialisation in the country, the
international trading system began to move towards more liberalised trade regimes.
Thus, Nepal began trade liberalisation as part of the Structural Adjustment Program in
1987 with the financial support of the International Monetary Fund (IMF) and the
World Bank.
Nepal’s trade policy has always been influenced by two important factors. First,
Nepal is a landlocked country, located 600 miles away from the nearest port (Calcutta
in India). Second, Nepal is surrounded by India on three sides of its border, which is
largely open or unguarded. The high cost of transit to ports for access to the rest of the
world, and India’s control over the terms of transit as well as the open border, place
Nepal in a situation of de facto free trade with India. Therefore, any attempt to
establish trading relationships with the rest of the world through standard trade policy
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Chapter 2: An Overview of Economic and Social Development in Nepal
instruments are likely to be constrained by the unofficial movements of goods and
services across the open border with India (Karmacharya, 2000).
Since the early 1990s, with the advent of democracy, the trade regime has been
opened and it is being liberalised in the context of multilateral trading system. More
importantly, India has initiated reforms to liberalise its trade and economic policies
during the same period. Thus, it has been more convenient for Nepal to follow almost
identical trade and economic policies as India. Furthermore, with the review of
various treaties, trade with India has become more transparent. India has allowed
transit facilities to ports in Bangladesh so that Nepal does not have to depend on the
Calcutta port alone.12
Many measures have been adopted for the promotion of trade and its further
liberalisation. For example, the role of the public sector in trade has been gradually
reduced, with more emphasis placed on the private sector. More attention has been
paid to promote and diversify trade both in the range of commodities and in market
directions. Import licensing was eliminated. The tariff rates and slabs have been
gradually reduced. The highest tariff rate was reduced from more than 400 per cent in
1980s to 40 per cent in 1990s.The number of tariff slabs has also been reduced from
12 The trade policy, introduced in 1992 and amended in the late 1990s, helped liberalise trade by reducing tariff rates and slabs, and abolishing licensing of imports. Nepal and India signed a trade treaty in December 1996, which facilitated Nepal’s preferential market access to India. Nepal can export to India, free of custom duty and quantitative restrictions, all manufactured products, except three (cigarettes/tobacco, perfumes/cosmetics with foreign brand names, and alcoholic liquor/beverages). Since 1997, Nepal has benefited from the opening of the Phulbari–Banglabandh road transit access. The latest agreement, the Treaty of Transit of 1999, has also been an important milestone for Nepal. Many efforts have been made to identify potential markets for Nepal’s goods and services. Existing treaties agreements with various countries have been effectively reviewed implemented and reviewed. See Trade Promotion Centre (1999) for details of Nepal’s trade and transit agreements with India.
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Chapter 2: An Overview of Economic and Social Development in Nepal
more than 100 to 5. The prevailing basic tariff rates are 5, 10, 15, 25 and 40 per cent
(IMF, 2001).
Following India, Nepal introduced partial current account convertibility of its
currency in 1992 and full current account convertibility in 1993. The exchange rate
against convertible currencies was unified with the abolition of a dual exchange rate
system and it became market determined. Subsequently, the market exchange rate
became the basis for all current transactions. On the other hand, the exchange rate of
the Nepalese Rupee against Indian currency still continues to be officially determined.
This exchange rate regime has led to a real depreciation of the Nepalese Rupee
against the US$ and a real appreciation against Indian Rupee (Deraniyagala, 2003).
For export promotion, a number of export strategies were introduced in the 1990s.
Exporters were allowed to retain up to 100 per cent of their export earnings as their
convertible currency accounts in the domestic banks. Export duty drawback schemes
aimed to provide a refund paid on taxes of imported goods were introduced, as was
the bonded warehouse system, which facilitated tax refunds on imported raw
materials for specific exports such as garments. Export licences were abolished
(Deraniyagala, 2003).
A bilateral trade treaty was signed with India in 1996. The treaty eliminated most non-
tariff barriers to trade with India, including the value-added tax requirements, which
required at least 50 per cent content in Nepalese or Indian raw materials for duty free
access to the Indian market. In other words, the treaty allowed Nepalese manufactured
goods to be exported to India free of any duty or quota. As a consequence, Nepal’s
50
Chapter 2: An Overview of Economic and Social Development in Nepal
exports to India increased by an average rate of more than 41 per cent per annum
during 1996-99 (Kaphley, 2000).
During the mid 1990s, trade with the autonomous region of Tibet in China was
formalised through a bilateral agreement on trade procedure and the mode of
payments. More importantly, a bilateral settlement agreement was signed allowing
use of the Chinese currency by Chinese tourists in Nepal. The accumulated Chinese
currency can be used for the payment of imports from China.
Table 2.15: Export, import and total trade as percentage of GDP, 1970-2002
GDP (%) 1970-75 1975-80 1980-85 1985-90 1990-95 1995-00 2002 Export 6.15 10.89 11.40 11.33 17.41 23.62 15.82 Import 9.93 15.33 19.65 20.75 27.39 34.01 28.39
Total trade 16.09 26.23 31.06 32.08 44.8 57.64 44.21 Source: IMF/IFS online database
Table 2.15 shows that there has been a gradual increase in Nepal’s international trade.
The total trade/GDP ratio increased to over 57 per cent in the late 1990s from around
31 per cent in the 1980s. But it decreased to 44 per cent in 2002 due mainly to the
political instability. However, throughout the 1980s the export/GDP ratio remained
almost unchanged. It increased only after the trade liberalisation of the early 1990s.
Thus, the export/GDP ratio increased to over 17 per cent in the first half of the 1990s
and to over 23 per cent in the second half of the 1990s, from 11 per cent in the 1980s.
The growth of exports in the 1990s was mainly driven by the growth of manufactured
exports. Throughout the period, the import/GDP ratio also increased almost in a
similar manner.
51
Chapter 2: An Overview of Economic and Social Development in Nepal
Nepal’s new policy allowed foreign investments in almost all sectors of the economy.
Important steps were taken to attract direct foreign investment. One hundred per cent
foreign ownership was permitted in most sectors, except those with strategic
importance. Full repatriation of the return on investment in convertible currencies was
also permitted. Furthermore, foreign investors were allowed to own up to 25 per cent
of listed companies.
Although many efforts have been made to expand and promote trade, some
weaknesses and obstacles still remain. Because of Nepal’s landlocked position, Nepal
has to bear extra transportation costs for consignments going to and from Calcutta
port in India. Trade is also hampered by the lack of sound management, inadequacy of
skilled manpower and technology. There is also a shortage of financial and material
resources and modern communication and technological facilities.
Since 2002, political instability and the Maoist violence and strikes across the country
have been hindering export promotion. In addition, Nepalese exports are characterised
by a very high level of market concentration. Over 85 per cent of total exports from
Nepal go to three countries: United States, Germany and India. This makes exports
subject to a high degree of volatility. For example, increased dependence on the
Indian market, particularly since 1996 following the new treaty, has elevated risks
arising from Indian policy shifts. Thus, the recent slowdown in exports is not only
caused by domestic instability, but also by excessive concentration in a few limited
markets (IMF, 2002).
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Chapter 2: An Overview of Economic and Social Development in Nepal
In sum, trade policies have significantly improved in Nepal. There has been a shift
from the earlier regime of trade restrictions towards a more open regime. Nepal has a
higher degree of openness than most other South Asian countries. Nepal achieves a
score of 2 on the IMF trade restrictiveness index that clearly indicates an open
regime.13
2.9.2 Financial sector development and deregulation
The history of financial sector development of Nepal has been short. It started with
the opening of the first ever commercial bank in the country, the Nepal Bank Limited
(NBL), in 1937. The NBL was established as a joint venture between the government
(51 per cent share) and the private sector (49 per cent share). It was the only bank or
financial institution in the country until 1956. The Central Bank of the country, the
Nepal Rastra Bank (NRB), was established in 1956.
Before the establishment of the NRB, Nepalese foreign exchange reserves used to be
held in India. In exchange, Nepal used to receive Indian currency, which despite its
inconvertibility with other currencies, was fully acceptable in Nepal. Thus, until the
establishment of the NRB, Nepal had no monetary policy of its own and its currency
was not linked to any other currency except India’s. Therefore, 1956 marked the
beginning of the real history of financial development in Nepal.
13 This index gives countries a score between 1 and 10. Scores 1-4 indicates open regimes; scores 7-10 indicates restrictive regimes. See Deraniyagala (2003).
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Chapter 2: An Overview of Economic and Social Development in Nepal
Within a decade, a number of institutions were established in the public sector. These
included the Nepal Industrial Development Corporation, the Agricultural
Development Bank, the Employees Provident Fund Corporation, the Nepal Insurance
Corporation and the Securities Marketing Centre. During 1970-89, the branches of
commercial banks expanded in many rural areas with partial subsidies from the NRB.
The vigorous drive for branch expansion significantly contributed to the institutional
development of the banking system. Commercial bank branches increased from 80 in
1970 to 439 in 1990. At the same time, the authorities gradually tightened their
control over the financial system by introducing interest rate controls, higher liquidity
requirements and directed credit programs (Acharya, 2003).
Nepal initiated financial reform measures in the mid 1980s. Following the financial
sector reforms, a number of new financial institutions were established. For the first
time, foreign banks were allowed to operate as joint ventures with Nepalese investors.
As a result, three joint venture banks – the Nepal Arab Bank Limited, the Nepal
Indosuez Bank Limited and the Nepal Grindlays Bank Limited – were established
between 1984 to1987.
For the first time, in 1985, commercial banks were allowed to accept current and fixed
deposits in foreign currencies (US dollar and Pound Sterling). Until 1986, the interest
rates of commercial banks were fully controlled by the NRB. The NRB deregulated
the interest rate regime in 1986 and authorised commercial banks to fix interest rates
at any level above its prescribed levels. The financial sector was further liberalised
under the Structural Adjustment Programs of the World Bank and the IMF. The
54
Chapter 2: An Overview of Economic and Social Development in Nepal
creation of the auction market for government securities also contributed to the
development of the financial sector (Shrestha, 2004).
As a result of financial sector deregulation the financial sector has grown rapidly.
Since the early 1990s there has been a dramatic increase in the number of banking and
non-banking financial institutions. By 2000, there were 1,060 commercial bank
branches. By July 2000, there were 11 private commercial banks, 2 development
banks, 5 regional rural development banks, 48 finance companies, 2 insurance
companies, 34 savings and credit cooperative societies, and some other financial and
quasi-financial institutions. Total financial assets as at mid July 2000 were estimated
at more than Rs. 277 billion. The total financial assets/GDP ratio increased from 29
per cent in 1985 to almost 76 per cent in 2000 (Acharya, 2003). The M2/GDP ratio
increased from 10.62 per cent in 1970 to 53.54 per cent in 2002. The commercial
bank deposit as a percentage of GDP increased from 10 per cent in 1980 to 42 per
cent in 2000. During the same period, credit as a percentage of GDP increased from
12 per cent to 32 per cent. Thus, all indicators show that the financial sector of Nepal
has deepened significantly.
However, some serious problems have remained for the two largest commercial
banks, the Nepal Bank Limited (NBL) and the Rastriya Banijya Bank (RBB). These
two banks have a high proportion of non-performing loans. As of mid 1998, they had
losses of around US$ 450 million, equivalent to around 46 percentage of their annual
budget, with the share of non-performing loans around 18 per cent of total loans in
2000. The share of these two banks in the assets and liabilities of the banking sector is
55
Chapter 2: An Overview of Economic and Social Development in Nepal
around 50 per cent (Shrestha, 2004). To ensure sound and effective management, the
government has contracted out their management to foreign private sector parties.
Additionally, the World Bank and the IMF have indicated that there are weaknesses in
the NRB’s regulatory and supervisory capacities, and have recommended further
measures to address these issues. The IMF (2003) revealed that the NBL and the RBB
suffer from weak management, poor accounting practices, considerable political
interference, and high numbers of non-performing loans. Still, the new management
teams are making progress in recovering non-performing loans and have produced
updated financial accounts. They are also improving human resource and treasury
management.
2.9.3 Macroeconomic stability
The fiscal situation in Nepal has been historically weak, with budget deficits being a
permanent feature of the budgetary system. During the 1960s, the nominal rate of
growth of government expenditure was around 15 per cent on average. This increased
to more than 17 per cent in the 1970s and further to more than 19 per cent in the
1980s (see Table 2.16). During the 1980s, the budgetary situation was marked by high
expenditure growth followed by high deficits. In the first half of the 1980s,
government expenditure increased by 19.7 per cent compared to the growth of
revenue at 16.1 per cent only. The mismatch between expenditure growth and revenue
growth widened the budget deficit; this period saw the fastest widening of the deficit
in three decades. This was financed mainly by borrowing from the NRB. Higher
56
Chapter 2: An Overview of Economic and Social Development in Nepal
monetary expansion pushed inflation to over 10 per cent, and Nepal faced a serious
balance of payments crisis in the first half of the 1980s.
Table 2.16: Average growth rates of fiscal sector indicators, 1966-2002 Average growth rates
Government expenditure
Regular Development Revenue Grants Deficit
1966-70 14.7 13.4 15.8 19.4 13.1 18.4 1971-75 17.4 20.6 16.3 17.4 5.1 -0.7 1976-80 18.2 16.5 19.2 13.4 23.6 33.0 1981-85 19.7 20.2 19.7 16.1 3.5 41.8 1986-90 18.7 18.1 19.2 19.1 19.3 22.0 1991-95 14.8 24.7 9.3 21.7 28.8 5.3 1996-00 11.2 12.4 10.2 11.8 8.6 12.0 1966-00 16.6 18.0 15.7 17.0 14.6 18.8 2001-02 11.8 14.4 3.2 8.6 23.6 16.4 Source: Economic Survey (various issues), Ministry of Finance
Restructuring of the fiscal sector in Nepal was initiated with the adoption of an
economic stabilisation program in 1985 and the subsequent graduation to the
Structural Adjustment Program in 1987. The primary objectives of the fiscal sector
restructuring were to improve the buoyancy and elasticity of the tax system, increase
budget allocations to social sectors, reduce the fiscal deficit, and contain net domestic
financing to less than one per cent of GDP.
The restructuring also aimed to minimise the budgetary drain to public enterprises,
and rationalise subsidies and transfers. From the early 1990s onwards, the
government’s role was to increase the participation of the private sector in industrial
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Chapter 2: An Overview of Economic and Social Development in Nepal
and other enterprises. At the same time, to reduce the government’s role in industry
and public enterprises, three public enterprises were privatised.14
Following the introduction of stabilisation and adjustment policies, the 1990s witnessed
an improvement in revenue collection. The revenue/GDP ratio was 9 per cent in the
1980s; it rose to 10.7 per cent on average during the 1990s. At the same time the
expenditure/GDP ratio declined to 17.5 per cent in 2000 compared with 19 per cent in
1990. As a result, a significant improvement can be seen in fiscal deficit, which declined
from 7.8 per cent of GDP in the 1985-90 to 5.5 per cent during 1996-2000.
However, there remain some concerns. The decline in expenditure exceeds the increase
in revenue. Thus, the burden of reducing government deficit has fallen disproportionately
on the expenditure side. Since reduction of current expenditure is politically difficult, the
objective of reducing the budget deficit has been achieved by cutting development
expenditure (Table 2.16). This is likely to have long-term implications for the economy.
Foreign economic assistance can play a crucial role in maintaining development and
social sector expenditure.
2.10 Corruption and governance reform
In developing countries like Nepal corruption is a major impediment to progress. While
it reduces public revenue, it increases public spending. Thus, it can contribute to larger
fiscal deficits. Corruption is likely to increase income inequality because it allows high-
14 These were Harisiddhi Brick and Tile Factory, Bansbari Leather and Shoe Industry, and Bhrikuti Paper and Pulp Industry.
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Chapter 2: An Overview of Economic and Social Development in Nepal
ranking officials to take advantage of government activities at the cost of the entire
population (Gupta et al., 1998).
Mauro (1995) showed that corruption reduces investment and in turn the rate of growth. It
also distorts markets and the allocation of resources. Thus, it is likely to reduce economic
efficiency and growth. Mauro (1995) estimated that an increase in corruption of one
standard deviation decreases investment and growth by 5 and 0.5 per cent of GDP
respectively.
Table 2.17: Control of corruption index for South Asian countries, 1996-2002
Year/Country 1996 1998 2000 2002 Nepal -0.26 -0.59 -0.42 -0.30
Bangladesh -0.43 -0.40 -0.64 -1.12 India -0.29 -0.17 -0.21 -0.25
Pakistan -0.91 -0.75 -0.70 -0.73 Sri Lanka -0.21 -0.24 -0.05 -0.14
Note: The index ranges from -2.5 (most corrupt) to +2.5 (least corrupt). Source: World Bank, 2002c15
Nepal is considered among the most corrupt developing countries in the world.
Transparency International (2004) gives Nepal a corruption index of 2.8 out of 10. For
Bangladesh, India, Pakistan and Sri Lanka the indices were 1.5, 2.8, 2.1 and 3.5
respectively.16 Although the extent and magnitude of corruption varies with the
definition and methodological procedures, observers believe that corruption in Nepal is
deep-rooted and widespread. As can be seen from Table 2.17, the governance indicator
(only control of corruption is presented) reveals that Nepal experiences a high level of
corruption. Among South Asian countries, only Sri Lanka is found less corrupt,
15 See World Bank (2002c) for details. 16 The index ranges from 0 (most corrupt) to 10 (most clean). See http://www.transparency.org/cpi/2004.en.html.
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Chapter 2: An Overview of Economic and Social Development in Nepal
followed by India.17 Thus, Nepal’s low rate of growth may be associated with high
levels of corruption.
The deep-rooted and widespread corruption has also fuelled the ongoing civil unrest in
Nepal. The poor governance and pervasive corruption have shattered people’s high
expectation that arose from the restoration of the democracy in 1991 (see Panday, 2001).
Poor and landless people, in particular low caste ethnic groups, did not find any change
in their life except new government of a bit different elite politicians. The persistent
social injustice among various low caste ethnic groups has not been addressed
adequately. On the other hand, local politicians, high level government officials and
Ministers are found directly involved in various corruption scandals (see the following
section). Thus, it is not only poverty, but also corrupt practices associated with aid
allocation, that is fuelling the Maoist uprising. This has almost ended the people’s faith
in democratically elected governments in various parts of remote areas. Consequently,
many poor, uneducated and low caste people are voluntarily joining the Maoist war (see
Murshed and Gates, 2005 for details).
2.10.1 Anti-corruption measures in Nepal
Corruption is not a new phenomenon in Nepal. King Prithivi Narayan Shah, who unified
Nepal as a sovereign nation in 1768, made it clear that both bribe takers and givers
commit the worst crimes against the country. During the autocratic Rana Regime of
17 Kaufmann et al. (2004) have defined corruption as the exercise of public power for private gain, and have treated corruption as a governance indicator. The index ranges from -2.5 to 2.5 (higher is better). See the World Bank’s Policy Research Working Paper 3106 for the data and methodology used to construct the governance indicators.
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Chapter 2: An Overview of Economic and Social Development in Nepal
1846-1951, some efforts were made to control corrupt practices. However, until 1950,
due to the limited economic activity, there were few opportunities for corruption.
After the popular democratic movement in 1951, the then government introduced the
Anti-Corruption Act 1952 to tackle corruption. The Anti-Corruption Department was
established in 1960. At the same time, the Special Police Department was used to
control growing corruption practices. In 1977, the Commission on Controlling Abuse of
Authority was established. After the restoration of democracy in 1990, the Commission
for Investigation of Abuse of Authority (CIAA) was set up to combat corruption.
Some efforts have since been made to control widespread corruption. In 1999, the
government announced a plan to combat corruption through three proposed anti-
corruption measures: a prevention of corruption bill, an amendment to the Commission
for Investigation of Abuse of Authority Act, and the establishment of the Special Anti-
corruption Court. Ironically, parliament remained deadlocked in early 2001, with
opposition parties calling for Prime Minister Koirala’s resignation for his alleged
involvement in a controversial Boeing lease fraud. After months of investigation, the
CIAA filed corruption charges against officials accused in the case, including the civil
aviation minister at the time.18
In March 2001, the CIAA sought the Prime Minister’s permission to proceed against
Govinda Raj Joshi, the Minister for Local Development, for his allegedly dubious
18 “Riddle in the Middle: Koirala and Current Crisis”, Kathmandu Post, 26 March 2001; “CIAA Charges Ex-Minister of Corruption”, The Rising Nepal, 30 October 2002. For more information about corruption charges and related issues see www.kantipuronline.com, www.nepalnews.com and the CIAA website, www.akhtiyar.org.np/reports.htm. See also Nepal Times on 20-26 September 2002 and Kathmandu Post on 18 August, 30 October, and 27 November in 2002.
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Chapter 2: An Overview of Economic and Social Development in Nepal
intentions in amending selection guidelines for teachers when he was Minister for
Education in 1997. Joshi filed a petition in the Supreme Court challenging the CIAA’s
action. The CIAA was fighting another battle in the Supreme Court against the Attorney
General, who filed a writ petition challenging the CIAA’s authority to question his
decision to drop proceedings in a currency smuggling case.
The government also proposed an array of anti-corruption legislation in 2002, including
the Corruption Control Bill, the CIAA Bill, the Special Court Bill, the
Impeachment/Regulation Working Procedure Bill and the Management of Political
Parties Bill. All these bills, intended to make the detection and prosecution of corruption
in state and non-state sectors more effective, were adopted by parliament in April 2002.
The Corruption Control Bill and the Special Court Bill received royal assent in June
2002. With the establishment of the Special Court and the empowerment of the CIAA,
action taken by the CIAA has been more effective.
The CIAA filed corruption cases against high-profile officials and ex-Ministers, and
rebuked the Prime Minister for approving the Lauda Air deal. It is too early to assess the
long-term impact of these developments on official corruption levels, but they clearly
represent a beginning. CIAA initiatives have demonstrated that autonomous, public anti-
corruption agencies backed by constitutional power can make a difference, and can avoid
falling under the sway of partisan objectives.
However, the actions of the CIAA have not escaped criticisms. For example, although
many cases of corruption were investigated by the CIAA on the basis of the findings of
the Judicial Commission for Property Investigation, the commission’s report has not been
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Chapter 2: An Overview of Economic and Social Development in Nepal
published yet. General public perception is that corruption has grown in the last 12 years,
that is, during the multi-party democratic system. The belief is that corruption is
encouraged and promoted by the government, ministers, parliament and the (weak)
judicial system.
The prevailing climate of political competition mobilised around corruption issues
remains a threat to the fight against corruption in Nepal as elsewhere. A further problem
is the absence of a functioning judicial system. While there is a rigorous anti-corruption
law, conviction rates are low, and sentences rarely carried out. The judicial process is
open to manipulation and cases drag on for years (Transparency International, 2001). For
example, Panday (2001) noted, “the auditor general of the country regularly identifies
arrears amounting to billions of rupees in government financial transactions every year
and draws the attention of the authorities for necessary actions….but nothing happens in
terms of taking action or executing the needed reform. This is a tradition from the days
of the ancient regime faithfully continued into the present political order” (2001: 19-20).
2.11 Concluding remarks
Nepal’s economic performance improved during the 1990s due mainly to trade and
economic liberalisation, initiated in the early 1990s. Since then, Nepal has made
significant progress in liberalisation of the trade, financial, monetary and industrial
sectors, and has thereby created an environment more conducive for growth. Despite
notable progress in the 1990s, the pace of reform implementation has slowed and
economic growth has been persistently hindered by political instability and the Maoist
insurgency.
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Chapter 2: An Overview of Economic and Social Development in Nepal
Nepal also made considerable progress in social indicators such as life expectancy,
literacy and access to safe drinking water. However, even now almost half of its
population lives in absolute poverty. Thus, a comprehensive Poverty Reduction Strategy
Paper (PRPS) has been incorporated in the Tenth Plan. The strategy is based on
extensive consultation within the public sector and with civil society, and is approved by
main multilateral donors. It aims to reduce poverty from 38 per cent in 2001 to 30 per
cent by 2007. To meet this target, the PRSP’s public expenditure program is based on the
Medium Term Expenditure Framework (MTEF), which is designed to help prioritise
expenditures. Under the MTEF, development expenditures have been prioritised in three
different categories. In addition, a performance based fund-release mechanism has been
implemented for development projects.
The PRSP has been welcomed by many donors who have begun to provide support for
the program. However, the IMF Joint Staff Assessment of the Poverty Reduction
Strategy Paper (2003) pointed out some weaknesses in the strategy. It noted: “While the
PRSP discusses the nexus between patterns of growth and poverty, especially in rural
areas and the importance of agricultural growth, discussion is limited to causal links
between policies and changes in poverty levels. Similarly, there is no explicit link
between past policies or programs and implications for prioritisation” (IMF, 2003: 4).
The IMF stressed the need for reform to further improve public expenditure
management, and imposed various conditions on the use of funds.
Nepal implemented the conditions prior to the disbursement of credit. For example, to
fulfil the conditions of the first Poverty Reduction Strategy Credit of the World Bank, the
government dropped many projects, appointed new professional management teams at
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Chapter 2: An Overview of Economic and Social Development in Nepal
the two main commercial banks (the NBL and RBB), and handed over 150 public
primary schools to local management and 400 sub-health posts to district level
management. More importantly, for the first time in Nepal’s history, corruption charges
have been laid to prosecute three former ministers and 22 tax officials. However, more
still needs to be done to strengthen key institutions charged with fighting corruption,
including the CIAA and the National Vigilance Center. Nepal also needs to continue its
reform of the financial and monetary sectors and the public sector.
Chapter 3
Foreign Aid to Nepal: An Historical Perspective
“…foreign aid has proved to be an effective instrument contributing to significant improvements in the socio-economic development of the country; and much of the physical infrastructure such as roads, irrigation facilities, hydropower as well as education and health services, drinking water and sanitation facilities have been built with foreign assistance. It has also contributed to the development of policy dialogue, catalysed economic reforms, enhanced the capability of policy makers; and provided financial assistance for public services…notwithstanding these achievements, foreign aid in Nepal has had its shortcomings as well. Progress in economic growth and poverty reduction has not been commensurate with the inflow of aid into the country” (HMG/N, Foreign Aid Policy, 2002: 3).
3.1 Introduction
Foreign aid has been an important instrument in the socio-economic development of
Nepal. Since the early 1950s, almost all physical infrastructures have been financed
by foreign aid. Nepal’s geographical location, topography (its mountainous terrain)
and widespread poverty combined with high rates of population growth have
persistently made the country aid-dependent for more than half a century. The average
aid to GDP ratio increased from about 2 per cent in the 1960s to almost 10 per cent in
the 1990s.
Until the mid 1960s, Nepal was almost fully dependent on foreign grants for all its
development projects. The first Five Year Plan (1956-60) was entirely financed by
foreign aid. Most of these grants were on a bilateral basis and concentrated on the
establishment of public enterprises and building physical infrastructures. For example,
grants from India helped to build the airport in Kathmandu, the Kosi dam and various
irrigation projects. The former Soviet Union provided assistance to build cigarette and
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
66
sugar factories, a hydroelectric plant, and part of the East–West highway. China
assisted to construct roads, a trolley bus line in Kathmandu, and leather and shoe, and
brick and tile factories. US grants supported village development, agriculture,
education and public health. The US also helped start the Nepal Industrial
Development Corporation, which granted loans to several industries. Although during
the 1950s and 1960s the top priority was given to the development of infrastructure,
later, in the 1970s, the agricultural sector received high priority for the allocation of
aid.
Table 3.1: Nepal’s average total aid, bilateral and grants aid, 1960-2002 Year Total aid
(% of GDP) Bilateral aid (% of total aid)
Grants aid (% of total aid)
1960-69 1.95 96.83 99.79 1970-79 4.34 66.31 72.52 1980-89 10.39 54.22 64.17 1990-99 10.04 60.48 67.57 1960-02 6.62 69.99 76.85 Source: OECD/IDS online database
Over the years, Nepal’s aid dependency increased considerably. As can be seen from
Table 3.1, the average total aid increased from about 2 per cent of GDP in the 1960s
to 10 per cent in the 1980s and aid flows remained at around 10 per cent of GDP in
the 1990s. Although bilateral aid still dominates, its share has declined. For example,
the share of bilateral aid decreased from almost 97 per cent in the 1960s to around 60
per cent in the 1990s. With it, the share of grants in total aid also declined. In the
1960s, almost all aid was grants; it decreased to around 67 per cent in the 1990s.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
67
Although Nepal’s overall aid dependency has increased, one can argue that its
increased access to loans and decreasing dependency on grants is a sign of Nepal’s
improved status among the donors. It is hoped that Nepal can eventually graduate
from a receiver of concessional loans to commercial borrowings. This chapter will
provide a comprehensive picture of foreign aid to Nepal from an historical
perspective. It begins by discussing the significance of aid. It then examines the
sources (bilateral and multilateral), sectoral distribution and rationale (use) of foreign
aid. The chapter will also reflect on micro issues such as country ownership, aid
coordination and absorptive capacity.
3.2 Significance of aid
One can use a number of indicators to assess the importance of foreign aid. The most
common indicator is the ratio of foreign aid to GDP. This shows the overall
significance of foreign aid in the economy. Among the South Asian countries, Nepal
had the highest aid/GDP ratio (over 8 per cent) during 1970-2002 (see Table 3.1A).
Table 3.1A: Average aid/GDP ratios in South Asian Countries (%), 1970-2002 Year/Country Nepal Bangladesh India Pakistan Sri Lanka
1970-2002 8.29 6.84 1.14 3.92 6.12 Source: OECD/IDS online databases
As can be seen from Figure 3.1, aid to Nepal sharply rose until the late 1980s. It
increased from around 2 per cent of GDP in the 1960s to over 10 per cent in the late
1980s. Aid flows peaked at 15 per cent of GDP in 1990. Since then aid flows to Nepal
started declining, as elsewhere. The aid/GDP ratio stood at 6 per cent in 2002. This
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
68
decline in aid dependence coincided with Nepal’s policy reforms and improved
economic performance in the 1990s.
Figure 3.1: Foreign aid to Nepal as percentage of GDP, 1960-2002
0
5
10
15
20
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
AR (Total Aid % GDP)
Source: OECD/IDS online database
Figure 3.2 presents per capita aid to Nepal, which shows almost a similar trend as the
aid to GDP ratio. Despite population growth, per capita aid rose steadily from less
than US$ 2 in the 1960s to over US$ 25 (at current prices) by 1990. However, since
1990, it started to decrease and stood at about US$ 15 in 2002.
Figure 3.2: Per capita aid (US$ at current prices), 1960-2002
05
1015202530
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
Per capita aid ($US atcurrent prices)
Source: OECD/IDS and IMF/IFS online databases
The importance of foreign aid can also be assessed by examining the aid to revenue
ratio and aid to government expenditure ratio. For example, in Nepal, throughout the
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
69
1980s until the early 1990s, foreign aid as a percentage of domestic revenue was over
100 per cent. After steadily declining since 1965, from 71 per cent to nearly 26 per
cent in 1969, it increased to over 180 per cent in 1989.1 While it remained at over 90
per cent in the early 1990s, it declined from the mid 1990s to about 62 per cent in
2001 (Figure 3.3).
Figure 3.3: Foreign aid as percentage of domestic revenue, 1960-2002
0
50
100
150
200
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
Total aid as % of revenue
Source: IMF/IFS and OECD/IDS online databases
Figure 3.4: Foreign aid as percentage of government expenditure, 1960-2002
0102030405060708090
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
Total aid % of govt.expenditure
Source: IMF/IFS and OECD/IDS online databases 1 The sudden rise in the aid/revenue ratio was due to disbursement of aid following Nepal’s signing on Structural Adjustment Program with the IMF and the World Bank. Nepal also was able to attract larger aid flows from other donors following its dispute with India over the trade and transit treaty. When India closed its all transit points to Nepal except two in 1989, the crisis hit the Nepalese economy severely, and needed support from donors.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
70
The importance of aid is also evident from government expenditure financed by aid
(Figure 3.4). Between 1960 and 2002, aid’s share in total government expenditure
was over 40 per cent on average. Foreign aid financed nearly 20 per cent of total
expenditure in 1960, while it increased to about 48 per cent in 1964-65. Foreign aid
financing rose to over 80 per cent of total expenditure in 1992.
In sum, all indicators show that foreign aid has played a major role in Nepal, and it
remains a highly aid-dependent country. However, Nepal’s aid dependence has been
declining since the early 1990s.
3.3 Sources of aid
The United States was the first country from which Nepal received foreign aid. A sum
of US$ 2000 was provided by the United States to the Rana Regime in January 1951,
just a month before the regime collapsed. Soon after, foreign aid from diverse sources
came into the country. Since 1952, India, despite being a recipient country itself,
became involved in providing aid to Nepal. In 1956, China also began to help Nepal,
followed by the former Soviet Union. These two regional powers (India and China)
and two superpowers (the United States and the former USSR) had their own strategic
interests in competing for aid to Nepal (see Khadka, 1997).
Nepal has been successful in tapping aid from various sources. While its neighbouring
countries of India and China are two traditional sources, Nepal has expanded its
diplomatic relations with a large number of donors, resulting in increased aid flows to
the country. By the late 1980s over 35 countries provided aid to Nepal (Khadka,
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
71
1997). In addition, 11 UN agencies, 7 multilateral lending agencies such as the World
Bank, and 8 private agencies (for example, the Ford Foundation) were involved in aid
programs.
Under the auspices of the World Bank, the Nepal Aid Group was established in 1976.
By 1987 16 countries and six international agencies were involved in the group. 2
After 1976, a large part of foreign aid came from this group. The level of commitment
from the Nepal Aid Group increased from Rs. 1.5 billion in 1976-77 to Rs. 5.6 billion
in 1987-88. The aid commitment further increased from Rs. 16.5 billion in 1995-96 to
Rs. 18.8 billion in 2000-01(Library of Congress, 1991; Paudyal, 2003). The increased
commitment by the group might be attributed to the Structural Adjustment Program
that was initiated in the late 1980s.
In the 1980s, bilateral US economic assistance, provided through the Agency for
International Development (USAID), averaged US$ 15 million annually. The US also
contributed to various international institutions and private voluntary organisations
that serviced Nepal. Its total contribution to multilateral aid agencies working in
Nepal was in excess of US$ 250 million in the 1980s. The members of the
Organisation of Petroleum Exporting Countries (OPEC) provided US$ 30 million aid
from 1979 to 1989. Communist countries provided US$ 273 million in bilateral aid
from 1970 to 1988. From 1981 until 1988, Japan was the premier source of bilateral
official development assistance (ODA) for Nepal, accounting for more than one-third
of all funds. The second largest donor during that period was the former West
Germany.
2 The Aid Group is now known as Nepal Development Forum and 23 countries and many international agencies represented Nepal Development Forum 2000 held in France. In recent years, it has been held in Nepal also.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
72
As can be seen from Table 3.2, since the 1980s, among the bilateral donors, Japan has
been the largest donor, followed by Germany, United States and United Kingdom.
These four countries still account for over 60 per cent in the share of total bilateral
aid. Until the mid 1960s the United States was the largest donor. US aid increased
from US$ 11.42 million in the 1960s to over US$ 22 million in 2000-02. German aid
increased from US$ 0.61 million in the 1960s to over US$ 31 million in 2000-02; aid
from the United Kingdom rose to almost US$ 31 million in 2000-02 from less than a
million dollar in the 1960s. More significantly, Japan’s aid increased from US$ 0.07
million in the 1960s to over US$ 90 million in 2000-02. Denmark, Switzerland,
Norway and Netherlands have also become major bilateral donors to Nepal.
In the case of multilateral donors, the ADB, IDA, UNDP and UNICEF are the major
donors. Except for the UNDP, the contributions of these donors were not very
significant in the 1960s. Together they provided US$ 1.35 million, and the UNDP
alone contributed US$ 1.2 million. From the 1970s, however, multilateral aid
increased. On average the ADB increased its aid from US$ 4.25 million in the 1970s
to over US$ 66 million in the 1990s. IDA aid also increased from US$ 6.91 million in
the 1970s to over US$ 54 million in the 1990s. Throughout the 1990s, aid from
multilateral donors increased substantially and accounted for around 40 per cent of
total aid during 1990-2000.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
73
Table 3.2: Nepal’s average bilateral and multilateral aid, 1960-2002 (US$ million) Major donors 1960-69 1970-79 1980-89 1990-99 2000-02 1. Japan 2. German 3. United Kingdom 4. Denmark 5. United States 6. Switzerland 7. Norway 8. Canada 9. Australia 10. Finland 11. Netherlands 12. Sweden 13. France 14. Belgium 15. Austria 16. Italy 17. New Zealand 18. Arab countries 19. Korea A. Total bilateral (including others)
0.07 0.61 0.84 0.00 11.42 0.28 0.03 0.01 0.21 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13.11
6.17 6.96 7.82 0.51 9.54 2.61 0.33 2.05 0.74 0.02 0.90 0.07 0.00 0.36 0.08 0.01 0.31 3.35 0.00 38.89
49.07 23.71 16.96 3.79 17.00 11.17 3.09 8.67 2.04 5.83 3.62 0.15 6.61 0.64 0.93 1.05 0.13 3.24 0.00 156.02
94.90 26.56 25.53 18.73 17.59 13.71 7.65 4.66 4.25 9.49 7.75 1.09 8.60 0.45 2.21 0.32 0.35 1.88 1.60 246.93
90.92 31.41 31.02 25.45 22.92 12.81 11.17 4.21 4.02 5.27 8.81 6.15 0.18 0.67 1.47 0.22 0.47 7.79 1.80 270.31
1. ADB 2. IDA 3. UNDP 4. WFP 5. UNICEF 6. UNTA 7. UNHCR 8. OTHER UN 9. UNFPA 10. Arab Agencies 11. IFAD B. Total multilateral (including others) Total A + B
0.00 0.19 1.22 0.17 0.34 0.49 0.05 0.11 0.00 0.00 0.00 0.89 14.00
4.25 6.91 4.65 2.96 1.29 0.86 0.06 1.15 1.72 4.15 0.00 24.51 63.40
36.13 51.80 13.67 7.28 5.16 1.89 0.08 3.01 1.99 1.35 4.92 131.66 287.68
66.10 54.26 10.24 7.31 6.77 3.52 4.78 2.44 3.50 1.76 1.61 161.44 408.37
41.58 26.15 7.71 6.99 4.32 4.00 4.65 3.39 3.55 1.91 0.97 112.71 383.02
Notes: (a) Since OECD did not include India and China, aid from them could not be reported here.
However, the significance of aid from India and China is discussed separately later in the chapter. (b) IMF assistance is not regarded as aid. It is primarily given for budget and balance of payments support. Thus, assistance from the IMF is not included in the list. However, many bilateral and multilateral aid agencies make their aid contingent upon fulfilment of IMF’s conditionality.
Source: OECD/IDS online database
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
74
According to the OECD (2004), among the top 10 donors of gross ODA (Official
Development Assistance) to Nepal for 2002-03 were Japan (US$ 87 million), IDA
(World Bank) (US$ 68 million), Germany (US$ 49 million), United Kingdom (US$
45 million), US (US$ 35 million), Denmark (US$ 33 million), ADB (US$ 31 million),
Norway (US$ 17 million), European Commission (EC) (US$ 15 million) and
Switzerland (US$ 14 million).
3.3.1 Japan’s aid
When the Japanese embassy in Nepal was established in 1968, Japan started
providing loans and grants to Nepal. Average Japanese aid was less than 1 per cent of
total bilateral aid in the 1960s, and it increased to almost 35 per cent in the 1980s.
Since the early 1980s, it has become the largest bilateral donor to Nepal. Japanese aid
stood at about US$ 60 million in 2003. Of total Japanese aid to Nepal, grant
assistance represents 58 per cent, loans 24 per cent and technical cooperation 18 per
cent, as at 28 April 2003 (see Japanese embassy, 2003).
Table 3.3: Japan’s share of total bilateral aid, 1960-2002 Year 1960-69 1970-79 1980-89 1990-99 1960-00 2002 Average share (%)of total bilateral aid 0.62 14.97 34.99 38.04 22.84 26.66 Source: OECD/IDS online database The sectoral distribution of total grants aid from Japan as at April 28, 2003 shows that
the agricultural sector received the highest amount, accounting for 23 per cent. The
second highest share of grants (19 per cent) went to the social sector, which includes
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
75
education (8 per cent), health (3 per cent), safe drinking water (7 per cent) and other
social services (1 per cent). The remaining grant aid went to the infrastructure sector
(16 per cent), debt relief (12 per cent), the energy sector (8 per cent), communication
(8 per cent), food aid (4 per cent), disaster mitigation (4 per cent), civil aviation (3 per
cent) and other non-project sectors (3 per cent) (see Japanese embassy, 2003).
Japanese loan aid was provided mainly for projects. The highest share of loan aid as at
April 28, 2003 went to the Udaipur Cement Plant Project, accounting for 29 per cent.
The second highest share was received by the Kaligandaki “A” Hydroelectricity
Project (26 per cent). Among other projects, the Kulekhani No. 2 Hydropower Station
Project received 19 per cent of Japanese loans, the Kulekhani Disaster Prevention
Project, 10 per cent and Kulekhani Hydroelectric Project 6 per cent.3
3.3.2 India’s aid
India has been providing development assistance to Nepal for over 50 years. It was
the second largest donor after the United States until the 1965. India became the
largest donor in 1966 and remained so until 1980-81.
Table 3.4: India’s share of total bilateral aid, 1960-1990 Year 1960-64 1965-69 1970-74 1975-79 1980-84 1985-90 Average share (%) of total bilateral aid 20.35 50.35 42.63 26.31 21.98 13.23 Source: Khadka (1997)
3 The percentages represent accumulated total loans as at 28 April 2003. See www.np.emb-japan.go.jp
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
76
Table 3.4 shows that India’s aid increased substantially during the late 1960s. It
increased from 20 per cent of total bilateral aid in the first half of the 1960s to over 50
per cent of total bilateral aid in the late 1960s. In particular, in 1968 and 1969 it
reached over 60 per cent of total bilateral aid. However, after the late 1970s, India’s
average share decreased and by the late 1980s, it stood at 13 per cent of total bilateral
aid.
In the early days, Indian assistance was given more for infrastructure projects, such as
roads, railways and airports.4 India spent over 56 per cent of its total aid at this time
building roads and airports. Table 3.5 shows road projects that were built during
1953-85 with Indian aid.
Table 3.5: India’s aid for road projects, 1953-90 Name of the project Length (km) Year constructed Tribhuvan Raj path 116 1953-59 Siddhartha Raj marg 200 1965-72 Dakshinkali Road 19 1969 Mahendra Raj marg (eastern section) 300 1969-75 Kathmandu–Godawari Road 16 1973-75 Kathmandu–Trisuli Road 69 1972-75 Hanumannagr–Fatehpur Road 28.2 1975-77 Hanumannagar–Rajbiraj Road 13.5 1983 Mahendra Raj marg (Butwal–Kohalpur) 310 1984-86 Kohalpur–Mahakali Road 200 1986-92 Source: Various issues of HMG/N
More recently, Indian assistance has been extended to other sectors such as education,
health, agriculture and power. Thus, the amount of aid has increased substantially
over the years. It increased from an average of Rs. 150 million in the mid 1980s to Rs.
4 Nepal’s only railway, the Janakpur–Jayanagar line, was built with Indian aid.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
77
750 million in 1999-00. However, these figures exclude the supply of subsidised
commodities such as rice, sugar, cement and fertiliser, and the refund of
petrochemical excise duty levied on items exported from India.5
3.3.4 China’s aid
Nepal’s diplomatic relationship with the People’s Republic of China was established
in 1955, further strengthening the age-old bilateral relationship between the two
countries. The first and second agreements between China and Nepal on economic aid
were signed in 1956 and 1960 respectively. Since then China has been providing
grants of financial and technical assistance to Nepal.
Table 3.6: China’s share of total bilateral aid, 1960-90 Year 1960-64 1965-69 1970-74 1975-79 1980-84 1985-90 Average share (%) of total bilateral aid 5.5 15.2 16.91 15.11 8.43 4.2 Source: Khadka (1997)
China’s first assistance was to support Nepal’s Five Year Plan (1956-60) with a sum
of US$ 12.6 million. China’s aid increased from just 5.5 per cent of total bilateral aid
in the first half of the 1960s to 15 per cent in the second half of 1960s. It further
increased to almost 17 per cent by the mid 1970s. However, China’s importance has
declined considerably and its share in total bilateral aid stood at about 4 per cent by
the late 1980s.
5 See http://www.south-asia.com/embassy-india/indnepal.htm.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
78
The Chinese aid-financed projects are mainly in transport and industry. However,
China also provides aid to other sectors such as hydropower and irrigation, public
facilities, health, education and sports.6 Table 3.7 presents the list of Chinese aid
funded road projects.
Table 3.7: China’s aid for road projects, 1963-90 Name of the projects Length (km) Year constructed Arniko Highway 104 1963-67 Arniko Highway maintenance 13 1968-70 Prithivi Highway (Kathmandu–Pokhara Road) 174 1965-67 Kathmandu–Bhaktapur Road 13 1969-71 Gorkha–Narayanghat Road 60 1976-82 Kathmandu Trolley Bus 14 1973-75 Kathmandu ring Road 27 1974-77 Pokhara–Mustang Road 73 1987-90 Source: Various issues of HMG/N
China has constructed many important highways, such as the Prithivi highway, which
links Kathmandu and Pokhara, Nepal’s only tourist centre, apart from Kathmandu. As
a result, this highway opened up significant economic opportunity for ordinary
people. In addition, China helped build the ring road around Kathmandu, the trolley
bus system, and the Kathmandu to Bhaktapur road.
China also provided financial assistance to establish a number of industries –
industries that had great significance during the period when Nepal pursued import
substitution policies. During 1965-86 Chinese aid helped to establish the Bansbari
Leather and Shoe Factory, the Harishiddi Brick and Tile Factory, the Hetauda Cotton
6 Embassy of China in Nepal, www.chinaembassey.org.np
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
79
Textile Mills, the Bhaktapur Brick and Tile Factory, the Bhrikuti Paper Mills, the
Lumbini Sugar Factory and the Leather Globes and the Apron Manufacturing Unit.
One important difference between India and China’s aid is that China provided
assistance not only for road projects, but also for the promotion of consumer goods in
Nepal. India, on the other hand, helped build infrastructure in areas where they had
more strategic interests. India’s aid never involved promoting trade in Nepal, as that
would affect Indian exports (Khadka, 1997).
3.3.4 The World Bank, the IMF and the Asian Development Bank in Nepal
The World Bank
Nepal became a member of the World Bank on 6 September 1961. While the Bank’s
office was opened in 1971 in Kathmandu, its operations began in 1969. Its first credit
was provided to a telecommunications project from the International Development
Association (IDA). Since then, the World Bank has approved 79 credits, amounting
total of around US$ 1.6 billion. Active credits totalled US$ 341 million as at April
2004. The World Bank has been providing funds for the development of
infrastructure, telecommunications, education, Structural Adjustment Programs, and
poverty reduction programs and projects. Recently approved active projects are listed
in Table 3.8. These projects have prioritised financial sector restructuring and power
development followed by the education and health sectors.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
80
Table 3.8: Active projects financed by the World Bank (IBRD and IDA),
1999-2004
Name of the projects Credit (US$
million) Approved date Nepal health sector program project 50 09/09/2004 Education for all project 50 08/07/2004 Poverty alleviation fund project 15 01/06/2004 Second rural water supply and sanitation project 25.3 01/06/2004 Financial sector restructuring project 75.5 09/03/2004 Community school support project 5 30/6/2003 Nepal power development project 75.6 22/05/2003 Financial sector technical assistance project 16 19/12/2002 Nepal telecommunications sector reform project 22.56 11/12/2001 Road maintenance and development 54.5 23/11/1999 Total credit (1999-2004) 389.46 Source: World Bank, 2004
In 1964, the World Bank financed a transport survey to help prepare for a five-year
transport sector investment plan. Since 1970, the bank has funded six road projects in
Nepal and the building of suspension bridges in various parts of the country (Table
3.9). These projects have generated economic opportunities in some of Nepal’s
poorest regions. They improved the quality of transportation between Kathmandu and
the rest of the country, as well as strengthening the maintenance capabilities of the
road department.
Table 3.9: Roads and suspension bridges financed by the World Bank, (1970-2003)
Road bridges Length (m) Pedestrian suspension bridges Length (m)
Dhobi Khola 45 Kabeli (Phidim) 70 Bishnumati (Balaju) 60 Tamor (Taplejung) 100 Amlekhgung No. 1 62 Kali Gandaki (Purtighat) 80 Amlekhgung No. 2 92 Kali Gandaki (Ranighat) 153 Parwanipur 36 Ulli Khola (Gulmi) 100 Source: NRB, 2003
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
81
The World Bank has been involved in the development of telecommunications in
Nepal since November 1969. A more modern and reliable long-distance network has
been established, helping to bring telecommunication services to rural areas. A
satellite earth station funded by the World Bank has significantly improved the quality
of international telephone services and enabled the introduction of modern services
such as facsimile and data transmissions.
The World Bank has also provided finance for education projects. These have
developed the educational sector in many respects, their major achievements being
institutional development, staff training, building construction, the introduction of
computers and equipments, curriculum and textbook development, and the
introduction of new education programs.
Table 3.10: Some educational projects financed by the World Bank and others,
(1977-2003)
Name of the projects Duration
Credit (US$ million) Co-financer
Institute of Engineering development project 1977-85 4.7 UK Western region campus project 1979-87 12 ILO Primary education 1984-92 8.6 Agricultural manpower project 1985-94 10.9 Engineering education project 1989-99 10 Canada and Switzerland Higher education project 1994-01 17 Earthquake rehabilitation project 1989-96 23
Basic and primary education project 1992-98 30.3 DANIDA, Norway, Finland and European Commission
Basic and primary education project 1999-03 12.5 DANIDA, Norway, Finland and European Commission
Total credit (1977-2003) 129 Source: NRB, 2003
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
82
In the 1980s, the World Bank supported the implementation of the Structural
Adjustment Program. Nepal’s weak institutional capacities, poor governance and
other various problems in the banking, trade and agricultural sectors were identified
as major impediments for economic development. The World Bank’s first SAP was
launched in 1986 with US$ 50 million of credit, for the purpose of implementing
policy reforms. The SAP gave emphasis to sound macroeconomic management,
effective management of public finances, support for the agricultural and light
manufacturing sectors, liberalisation of trade, and reform of public enterprises.
A second structural adjustment was disbursed in 1989 with US$ 60 million credit.
The main aim of this credit was to consolidate and reinforce the earlier one, and also
to revamp the tax system, rationalise the management of development spending,
restructure the two main state-owned commercial banks (Nepal Bank Limited and
Rastriya Banijya Bank) and open up the financial sector, improve the distribution of
fertiliser, and make irrigation more effective. Both the first and second SAPs
programs have had a remarkable impact on the liberalisation of the trade regime and
the financial sector (already discussed in chapter 2).
Recently, the World Bank has begun to focus more on supporting Nepal’s Poverty
Reduction Strategy Paper (PRSP). In November 2003, it approved the Poverty
Reduction Strategy Credit (PRSC) worth US$ 70 million. The credit is intended to
implement measures to revive growth, improve service delivery, improve governance
and promote social inclusion. It also contributes to maintaining a sound
macroeconomic framework and protecting high priority programs by filling part of
Nepal’s financing gap.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
83
It is believed that Nepal’s PRSP will be more effective through sustainable economic
growth. To stimulate broad based economic growth, the World Bank’s assistance
focuses on removing bottlenecks to growth such as the excessive role of the state and
the lack of adequate infrastructure. According to a report of the World Bank (2003),
its recent assistance to Nepal has focused on strengthening the quality of public
expenditure, the soundness of the financial system, and the investment climate. Also,
the World Bank has been supporting infrastructure projects that help promote
demand-driven irrigation schemes managed by local water user groups, and water
supply schemes, which reduce the time women spend collecting water. (In some parts
of the Nepal, it still takes four to five hours to collect drinking water.)
The International Monetary Fund (IMF)
Nepal became a member of the IMF on 30 September 1961. Details of the latest
financial loans from the IMF are presented in Table 3.10. The Structural Adjustment
Facility (SAF) and Stand-By Arrangement (SBA) were implemented during the 1980s
in conjunction with the World Bank’s Structural Adjustment Programs. These
programs have made significant contributions to economic and trade liberalisation in
Nepal. Based on Nepal’s progress and the government’s commitment to further
reforms, in November 2003 the IMF approved approximately US$ 72 million over
three years to establish the Poverty Reduction and Growth Facility (PRGF).
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
84
Table 3.11: IMF financial arrangements for Nepal, 1985-2003 Program Approved date Expiration
date Amount approved (SDR million)
Amount drawn (SDR million)
PRGF 19 Nov 2003 18 Nov 2006 49.91 7.13 PRGF 5 Oct 1992 4 Oct 1995 33.57 16.79 SAF 14 Oct 1987 13 Oct 1990 26.11 26.11 Stand-By 23 Dec 1985 22 Apr 1987 18.65 18.65 Source: IMF, 2003b
Asian Development Bank (ADB) Nepal was one of the 31 founding members of the ADB, which was established in
1966. The ADB lends to Nepal on highly concessional terms of interest (1.5 per cent
per annum, with loan repayments typically due over 32 years with 8-year grace
periods), from its soft-lending window, the Asian Development Fund (ADF). The first
loan of US$ 6 million was for air transport development, in 1969. Since then, ADB
loans have been increasing to Nepal. They grew by an average of US$ 80 million in
the 1990s. Cumulative ADB lending to Nepal as at 31 December 2003 was about US$
2 billion.7
7 See on www.adb.org/documents/fact_sheets/NEP.asp.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
85
Table 3.12: ADB sectoral distribution of cumulative lending as at 31 Dec 2003 Sector Loan (numbers) Amount (US$ millions) % of total loan Agriculture and Natural resources
52 808.5 38.4
Energy 14 432.4 20.5 Social infrastructure
19 410.4 19.5
Transport and communication
13 270.7 12.9
Industry and non-fuel minerals
5 75.1 3.6
Others 5 100.6 4.8 Finance 1 7.3 0.3 Total 109 2,105.0 100.00 Source: ADB, 2004
Table 3.12 shows that the agricultural sector received a significant share of ADB
loans, accounting for almost 40 per cent of all ADB lending to the country. Over time,
the pattern of ADB lending has changed. While the primary focus was on agriculture
and physical infrastructure up until the 1980s, lending for social infrastructure has
increased considerably in recent years. In the social infrastructure sector, the ADB
financed projects in primary and secondary education, rural water supply and
sanitation, gender and development, and urban management.
3.4 Sectoral distribution of aid
Figure 3.5 shows the sectoral distribution of foreign aid between 1974-83. The
transport and communication including power received the largest share of aid (65 per
cent) in the fiscal year 1974-75, and on average these three sectors received over 50
per cent of total aid during 1974-83. The agriculture sector received the second
highest share of aid followed by the social sector (including rural development). Thus,
until the early 1980s, more amount of aid was used to finance infrastructure. Although
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
86
aid financing increased from around 20 per cent in 1979-80 to almost 29 per cent in
1982-83 in the agriculture sector, the transportation, communication and power
remained main target of aid financing throughout the period.
Figure 3.5: Sectoral distribution of aid as percentage of total aid, 1974-83
0
20
40
60
80
1974 1975 1976 1977 1978 1979 1980 1981 1982
Agriculture
Industry and commerce
Trans, power & communication
Social services
Note: social services (including rural development) Source: Poudyal (1988)
The same trend continued in the 1980s. Among the four sectors, transport, power and
communication received the largest amount of aid, followed by the agriculture and
social sectors (Figure 3.5A). Industry and commerce received the least amount.
However, from 1998 to 2000, a relatively higher amount of aid was allocated to the
social services sector.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
87
Figure 3.5A: Sectoral distribution of aid as percentage of total aid, 1984-1999
0
10
20
30
40
50
60
7019
84
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Agriculture
Industry and commerce
Trans, pow er & communication
Social services
Note: due to two difference sources of data, we have presented this Figure separately. Source: CBS, 1991 and 2001
The agricultural sector, providing livelihood to the majority of Nepalese, has been
receiving the second highest amount of aid after the transport, power and
communication sector. In fact, in 1993 it superseded the transport, power and
communication sector. However, its share declined steadily since then, and is now
less than that of the social sector. Thus, there is a clear shift away from agriculture to
the social sector in aid allocation; given the importance and also the backwardness of
agriculture, this may seem a tough choice. Still, the continued dominance of the
transportation, power and communication sector may be linked to the prevalence of
widespread corruption among government officials (see, for example, Knack, 2001;
Mauro, 1995; Tanzi, 1998).
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
88
3.5 Types of aid
3.5.1 Project and program aid
Throughout the 1970s, almost all aid activities in Nepal were linked to projects, such
as financing infrastructure developments in the communication, health, education,
agricultural and rural sectors. By the late 1970s and early 1980s, the modality of aid
disbursement, especially from the World Bank, moved more towards program aid
designed to support policy reforms. Among various reasons for this shift, it was
believed that program aid would be quicker to disburse. Furthermore, it was
recognised that, contrary to expectations, project aid could not prevent fungibility of
aid. The movement towards program aid brought the World Bank and the IMF much
closer operationally. As seen in the previous section, the World Bank provided two
Structural Adjustment Programs followed by the IMF’s SAF and SBA. Nonetheless,
project aid still dominates in Nepal.
3.5.2 Technical cooperation/assistance
Technical cooperation encompasses all kind of assistance to improve the level of
knowledge, skills and technical capabilities of the recipient country. Although the
World Bank uses the terms technical cooperation and technical assistance
interchangeably, the OECD uses separate and distinct definitions. Technical
cooperation (or freestanding technical cooperation) includes activities financed by
donor countries to augment the level of knowledge, skills and productive aptitudes of
the population of developing countries. Technical assistance (or investment-related
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
89
technical cooperation) includes financing the design and/or implementation of project
or programs aimed at increasing the physical capital stock of a recipient country.
Figure 3.6: Technical cooperation as percentage of total aid, 1966-2002
0
20
40
60
80
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
Technicalcooperation % oftotal aid
Source: OECD/IDS online database
As can be seen from Figure 3.6, of the total foreign aid received, technical
cooperation in Nepal accounts for about 35 per cent on average. It was about 70 per
cent in 1969 and now stands at around 30 per cent. Technical assistance can reduce
technological gaps in developing countries by supplying well-trained foreign
personnel who bring new skills, ideas and equipment. These foreign experts may
work together with local people or may provide training to them, transferring those
skills and areas of knowledge required for long-term development.
However, many researchers and agencies have expressed doubts about the
merits of technical cooperation (see, for example, Buyck, 1991; Berg, 1993).
Technical cooperation has been found to be supply driven, with insufficient emphasis
given to the training of local people. Foreign experts get higher salaries and better
facilities than local staff. Recipient countries are often required to hire experts from
donor countries even when local experts are easily available and at a relatively lower
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
90
pay. Furthermore, technical cooperation is provided through loans instead of grants,
and thus creates debt burdens for developing countries (HMG/N, 2002).
3.5.3 Humanitarian and emergency aid
Humanitarian or emergency aid is provided during unfavourable circumstances such
as natural or man-made disasters. The purpose of humanitarian aid is more to save
lives than to achieve economic growth. It can consist of donations of food and other
commodities and services intended solely to help save people in situations of high
risk.
Figure 3.7: Emergency aid as percentage of total aid, 1995-2002
00.5
11.5
22.5
33.5
44.5
1995 1996 1997 1998 1999 2000 2001 2002
Emergency aid % of totalaid
Note: Earlier data for emergency aid are not available. Source: OECD/IDS online database
Compared to some African countries, Nepal has received limited amounts of
humanitarian aid, although almost every year it faces natural disasters such as floods
and landslides. However, since 1999, the proportion of humanitarian aid has
increased. As can be seen from Figure 3.7, emergency aid rose to over 4 per cent of
total aid in 2002 from less than 1 per cent in the late 1990s. This is due mainly to
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
91
dislocations caused by increased Maoist violence, and natural disasters such as floods
and landslides.
3.5.4 Food aid
Figure 3.8: Food aid as percentage of total aid, 1975-2001
0
2
4
6
8
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Food aid % of total aid
Source: OECD/IDS online database
Food aid was less than 1 per cent of GDP in Nepal during the entire 1975-2001
period. The share of food aid in total aid increased from less than 2 per cent in the late
1970s to over 6 per cent in the early 1980s. It then decreased to less than 1 per cent in
the early 1990s and remained at below 2 per cent for the rest of the period (Figure
3.8).
3.6 Rationale and use of aid
The rationale for foreign aid is found primarily in the two-gap model (reviewed in the
next chapter). That is, aid finances savings–investment and export–import (foreign
exchange) gaps. Any financing gap can be financed by borrowing from domestic
and/or foreign sources. These sources could be non-official (commercial) and/or
official (foreign aid). Commercial sources involve short-term borrowings and foreign
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
92
direct investment. For most developing countries, including Nepal, commercial
sources do not play a major role. Hence, for them foreign aid remains the main source
of financing savings–investment and foreign exchange gaps.
3.6.1 Savings–investment gap
With an average savings/GDP ratio of less than 12 per cent during 1970-2002, it can
be said that Nepal is a low saving country. Its savings rate increased from 10 per cent
in the 1980s to 13 per cent in the 1990s. On the other hand, its average
investment/GDP ratio was 16.6 per cent during 1970-2002. This increased from 17.6
per cent during 1980-90 to 20.2 per cent during 1990-2002. Thus, there is a gap
between savings and investment.
Figure 3.9: Aid and savings–investment gap (GAP) as percentage of GDP, 1970-2002
-12
-8
-4
0
4
8
12
16
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
GAP (SR-IR)AR
Source: IMF/IFS and OECD/IDS online databases
The gap has been widening over the years. In the late 1970s the savings–investment
gap stood at less than 4 per cent of GDP. In the 1980s, it rose to more than 7 per cent
of GDP (see Figure 3.9). During the same period, aid as a percentage of GDP was
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
93
high enough to fill the gap. On average, aid as percentage of GDP was over 8 per cent
during 1970-2002. Hence, the savings–investment gap was almost fully financed by
foreign aid; there were very limited private capital inflows in any form. However, the
aid financing need has declined since the early 1990s with an increase in remittance
income from Nepalese working abroad (Khatiwada, 2003).
3.6.2 Foreign exchange gap
Similarly, we find a very close association between aid/GDP and trade account
deficit/GDP ratios (Figure 3.10). The trade account deficit as a percentage of GDP
increased from less than 4 per cent in the 1970s to over 10 per cent on average in the
late 1980s to 1990s. During the same time frame, aid also increased, from less than 4
per cent of GDP in the 1970s to over 10 per cent in the late 1980s. Since the late
1990s, as foreign aid has declined Nepal has maintained its current account balance
with the overseas workers’ remittances.
Figure 3.10: Aid and trade balance as percentage of GDP, 1970-2002
-16
-12
-8
-4
0
4
8
12
16
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Aid as % of GDPTrade balance as % of GDP
Source: IMF/IFS and OECD/IDS online databases
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
94
3.6.3 Government budget deficit
It is generally believed that the savings–investment gap is a result of government
budget deficit. Aid is a major source of financing the budget deficit. Figure 3.11
shows aid and budget deficit trends as percentages of GDP. Until the early 1970s,
average budget deficit was about 1 per cent of GDP. As budget deficit continued to
increase to an average of 9 per cent of GDP in the mid 1980s to the early 1990s,
average aid as a percentage of GDP also increased in the same period to almost 10 per
cent (Figure 3.11). Since the late 1990s, the average budget deficit was maintained at
below 7 per cent of GDP; but the average aid flow was slightly over 7 per cent of
GDP. This difference could be due to statistical factors (they are taken from different
sources). There are other possible reasons too. For example, some aid (especially
emergency aid) may be distributed directly without being recorded in the annual
budget (that is, discretionary off-budget spending). This kind of spending also raises
the possibility of lack of accountability and misuse.
Figure 3.11: Aid and budget deficit as percentage of GDP, 1970-2002
-10
-5
0
5
10
15
20
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Aid as % of GDPBudget deficit as % of GDP
Source: IMF/IFS and OECD/IDS online databases
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
95
In sum, all three indicators – savings–investment gap, foreign exchange gap and
government budget deficit – support the two-gap model. In other words, aid to Nepal
is needed mainly to finance the savings–investment and/or foreign exchange gaps.
Since government budget deficit is the main source of the gaps, there is a close
association between government budget deficit and aid inflows. Foreign aid has been
an important source of funds for government development expenditure. Aid
contributed 55.7 and 56.3 per cent of development expenditure under the Eighth Plan
(1992-93 to 1996-97) and Ninth Plan (1997-98 to 2001-02) respectively (see Paudyal,
2003). Thus, on average, over 50 per cent of development expenditure is financed
through foreign aid in Nepal.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
96
3.7 Micro issues of foreign aid
3.7.1 Aid conditionality and country ownership
Conditionality plays an important role in aid effectiveness. During the 1980s and
1990s conditional lending and aid grants in exchange for policy reform and structural
adjustment significantly increased, due largely to the approach of the World Bank and
the IMF. While the approach changed the traditional aid-financed investment towards
a strategy of aid-induced economic reforms, it also ensured that aid inflows are used
for the intended purpose and hence for the benefit of recipient countries. Despite the
mixed results and many criticisms of aid conditionality, access to aid has been made
contingent upon the adoption of appropriate policy framework through the imposition
of conditionality.8 Critics of conditionality based aid often point out that recipient
countries usually lack commitment to implement imposed policy reforms. They may
agree to reforms at the time of financial difficulties when they seek donor assistance;
but as soon as the situation improves with the disbursement of aid, many of the
reforms are either reversed or delayed (see, for example, Darzen, 2002 and Boughton,
2003). The Nepal Development Forum meeting held in Paris in April 2000 pointed
out the lack of country ownership as one of the main reasons for the slow
implementation of reforms (Foreign Aid Policy 2002).
In addition to the lack of country ownership, the number of reforms needed to fulfil
the conditionality within the set time frame is often found beyond a country’s
8 See Sachs (1997), Leandro et al. (1999), and Stiglitz (2002) for more discussion about the effectiveness of the World Bank and the IMF programs. For the effectiveness of conditionality, Killick (1997) noted, “ in the general case, conditionality is not an effective means of improving economic policies in recipient countries” (1997: 493).
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
97
administrative and institutional capacity. For example, conditionality includes
macroeconomic reforms (e.g., reducing budget deficits, devaluation, reducing
domestic subsided credit expansion), and other structural conditions such as freeing
controlled prices, reducing trade barriers and privatisation of public enterprises. All
together there are 18 reforms to be implemented within 3 to 4 months (mid November
2004-mid January 2005). See appendix 3.1 for details.
More importantly, these conditions create a sequencing problem for the efficient
implementation. If appropriate sequencing is not considered, conditions may
contradict each other and the expected benefits from the reforms may not flow. For
example, the Asian financial crisis has revealed that regulatory mechanism should
have been strengthened before liberalising the financial sector. Thus, as argued by
Boughton (2003), well-sequenced fewer conditions are more likely to succeed in
achieving their objectives.
Although conditionality induced policy reforms may yield benefits in the long-run,
they often have short-term costs due to the problems mentioned above. For example,
in Nepal increasing the price of petroleum products, dropping subsidies in fertiliser,
privatising public enterprises and increasing VAT rates had adverse effects on
agriculture, employment and business confidence. As a result, conditionality induced
policy reforms faced political resistance, which added fuel to political instability, and
in turn economic instability. The government has been forced to slow down the pace
of privatisation due to political pressure as it caused widespread unemployment.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
98
Nepal also had to deal with political unrest following the rise of prices of petroleum
products, increase in VAT rates and removal of subsidies.9
One of the visible weaknesses of these Structural Adjustment Programs in Nepal is
that they failed to have a significant impact on poverty reduction. In other words,
policy reforms did not promote investment in the agriculture sector. Increased
agricultural investment is needed to improve agricultural growth and productivity,
which play a crucial role in poverty reduction.
3.7.2 Fungibility of aid
If donor and recipient policy preferences differ substantially, aid finance is more
likely to be converted to fungible resources (see the literature review in the next
chapter). When aid is fungible, it tends to increase government spending on projects
not intended by donors. As the World Bank noted, “If aid financing is fungible, the
benefits of an aid-financed project are only loosely connected with the actual benefits
of aid financing” (1998: 60). In the case of Nepal, the World Bank (2000) in its Public
Expenditure Review noted that Nepal’s development budget tends to be over-
programmed because foreign aid is easily available to finance over 50 per cent of
development expenditure. Due to political reasons, the government often approves
projects that are generally less important in terms of socio-economic return. In the
majority of cases as discussed in section 3.4, capital-intensive projects are financed by
foreign aid, which do not contribute significantly to employment generation and
9 See IMF (2003) for an assessment of the pace of reforms. IMF (2003) noted that the pace of reform and implementation were slow because of Nepal’s political instability. The Nepal Development Forum meeting held in Paris in April 2000 also pointed out the lack of country ownership.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
99
poverty reduction. On the other hand, capital-intensive projects are generally believed
to encourage corruption through tendering and procurement processes. Furthermore,
if a significant portion of aid goes to finance non-traded sector, then aid may retard
economic growth in recipient countries. Yano and Nugent (1999) found evidence of
this in Nepal.
3.7.3 Coordination between donors and recipients
Aid effectiveness also depends on cooperation and coordination among donors,
between donors and recipient government departments, and among government
departments. For example, Nepal receives aid from more than 20 bilateral and 11
multilateral donors (see Table 3.2). Each donor has its own strategy and priority for
the development of Nepal, which may contradict the stance of other donors. If there is
no mutual understanding between donors about the needs of Nepal, it may result in a
resource gap in some priority sectors. On the other hand, there could be a glut of aid
projects in some sectors.
Similarly, the lack of coordination among different government departments also
reduces the effectiveness of aid. Thus, aid resources can be wastefully used. Nepal’s
Foreign Aid Policy 2002 pointed out, “aid coordination has become a burdensome
and cumbersome task” (2002: 6). Time-consuming procedures involved in
channelling aid from one department to another may make some donors move their
aid package somewhere else, and it may also lead to delays in the disbursement of aid
in subsequent years.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
100
Donor competition in hiring staff from government departments for project
management also creates problems. As Knack has suggested, “Foreign aid can also
weaken the state bureaucracies of recipient governments. This can occur most directly
by siphoning away scarce talent from the civil service, as donor organisations often
hire away the most skilled public officials at salaries many times greater than those
offered by the recipient-nation government” (2001: 313).
3.7.4 Tied aid
Aid may be tied through use of formal and informal restrictions. If a donor’s motive is
to promote home exports, tying aid may distort the economy of the recipient country
(Hjertholm and White, 2000). Generally, under tied aid, more capital-intensive goods
and services and technically advanced products are imported, which may not be
appropriate for the recipient country. Under tied aid recipient countries cannot take
advantage of competition from international markets to obtain the most suitable
sources of supply. In some cases, overseas technicians or experts take back almost all
of the given aid money. Furthermore, aid financed projects employ foreign
technology without making use of local technical knowledge. Recipient countries
cannot afford to maintain such projects in the long-run; they thus become financial
burdens.
3.7.5 Absorptive capacity
Aid effectiveness also depends on the absorptive capacity of recipient countries.
Donors should have good information about whether a recipient country is able to use
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
101
aid to generate economic growth and in turn reduce poverty. Knack (2001) found that
a higher level of aid erodes the quality of governance, which is measured by indices
of bureaucratic quality, corruption and the rule of law. When foreign aid started
pouring into Nepal after 1951, its absorptive capacity was so poor that it was unable
to direct aid finances effectively. It was entirely dependent on donors’ perceptions and
thus it had almost no control over foreign aid (Stiller and Yadav, 1979). Since 1951,
Nepal improved its absorptive capacity but not as much as is necessary. It still lacks a
quality institutional framework and efficient service delivery. Its weak institutions and
inappropriate policies have been the main obstacles to its ability to absorb aid
effectively. As is the case in other developing countries, Nepal does not have an
appropriate and effective mechanism to evaluate foreign technology and so in some
projects it has had to depend entirely on foreign technology and experts.
3.7.6 Foreign aid policy
Due to a lack of coherent foreign aid policy, for over 50 years Nepal failed to address
the above microeconomic issues of aid effectiveness. Until very recently, Nepal did
not have a government department designated to undertake regular supervision,
coordination and evaluation of aid financed projects. The cost of incoherent policy
can be very high; Nepal has already paid this cost being an aid dependent country. Up
until recently, aid to Nepal was always donor driven; it was always based on donor
motives and perceptions. For the first time, Nepal is counteracting this tendency
through the new policy framework called Foreign Aid Policy 2002.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
102
The policy highlights the various aid issues facing Nepal. It discusses the significance,
problems and prospects of aid to Nepal. It reviews past performance and current
problems associated with the national and donor perspectives. It introduces new
guidelines, strategies and policies for better aid utilisation. It appeals to donors to
develop mutual understanding about aid effectiveness, to appreciate Nepal’s particular
constraints such as widespread poverty, high rate of population growth, and
geography (land locked, mountainous terrain).
Foreign Aid Policy 2002 recognises that Nepal has failed to maximise the benefits of
past foreign assistance. Despite an increasing level of aid, its overall economic
performance has not improved. The lack of institutional capacity, appropriate
planning and management, timely supervision and evaluation of projects and
programs impede its development efforts. More importantly, Nepal’s absorptive
capacity remains weak. Differences persist between national needs and donors’
priorities, and projects and programs are largely donor driven. The difficulties in
matching donors’ perceptions with Nepal’s particular needs has perhaps reduced the
effectiveness of aid. A further problem has been that many aid inflows have not been
recorded in the government budget. Foreign Aid Policy 2002 addresses this by
highlighting the importance of efficient and effective accountability in the use of
foreign resources.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
103
3.8 Foreign debt burden
A substantial part of foreign aid goes to servicing foreign debt. As can be seen from
Figure 3.12, Nepal’s external debt burden has been increasing. Foreign debt rose from
about 2-3 per cent of GDP in the early 1970s to nearly 60 per cent of GDP in the late
1990s.
Figure 3.12: Foreign debt as percentage of GDP, 1970-2001
010203040506070
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
Foreign debt as percentageof GDP
Source: IMF/IFS online database
To maintain debt servicing, a high growth rate of exports is essential for borrower
countries. If exports grow faster than debt, a borrowing country does not have to fully
depend on grant aid and further capital inflows to service its debts. In the case of
Nepal, due to the narrow base and direction of exports (items are limited to garments,
woollen carpets and the like, going to India, United States and Germany and a few
other countries), export earning capacity is very weak and low.
The actual burden of foreign debt can be seen by considering debt service payments
(loan repayments together with interest) as a ratio of total exports of goods and
services. While Nepal’s debt service payment, as a ratio of total export of goods and
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
104
services, was less than 1 per cent until the late 1970s, it increased to 10 per cent in
1990, but declined to 6 per cent on average throughout the 1990s, remaining the same
in 2001. On the other hand, the total external debt/total export ratio rose from 63 per
cent in 1979-80 to 395 per cent in 1990-91, and stood at 207 per cent in 2001 (Bhatta,
2003).
The increasing burden of debt service has been hampering development efforts in
Nepal, mainly by curtailing investment in social services and infrastructure. Since the
mid 1990s, the annual average external debt service alone consumed nearly 13 per
cent of government revenue, which was almost more than 14 per cent of regular
expenditure, and about 8 per cent of the total government expenditure (Bhatta, 2003).
3.9 Concluding remarks
This chapter has provided a comprehensive overview of aid flows to Nepal. Nepal
receives aid from more than 20 bilateral and 11 multilateral donors. Among the
bilateral donors Japan has been the largest donor followed by Germany, United
Kingdom and USA. The ADB and IDA (World Bank) have been major multilateral
donors to Nepal. Foreign aid has played a significant role in meeting the savings-
investment gaps and financing the government’s development expenditure. Foreign
aid has also been crucial for alleviating Nepal’s foreign exchange constraint. Thus,
much of the achievements of Nepal during the last three decades in socio-economic
development can be attributed to donor assistance. Some of the salient features of
foreign aid to Nepal during 1960-2002 can be summarised as follows:
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
105
• Average aid/GDP ratio increased from almost 2 per cent in the 1960s to
around 10 per cent in the 1990s.
• Average share of bilateral aid in total aid decreased from almost 97 per cent in
the 1960s to 60 per cent in the 1990s.
• Average share of grants aid in total aid decreased from almost 100 per cent in
the 1960s to around 67 per cent in the 1990s.
• Average aid/government total expenditure ratio increased from around 30 per
cent in the 1960s to almost 80 per cent in the late 1980s and remained around
40 per cent in the 1990s.
• Average aid/revenue ratio increased from less then 80 per cent in the 1960s to
over 100 per cent throughout the 1980s and 1990s; but it decreased to around
62 per cent in 2001.
• A larger proportion of aid has been used to build infrastructure, which is
generally regarded as non-tradeable. However, infrastructure assists the
tradeable sector.
• Nepal’s savings-investment and foreign exchange gaps has been fully financed
by foreign aid
Having discussed the role of aid in Nepal, next we analyse econometrically the impact
of aid on the Nepalese economy in chapter 6, 7 and 8.
Chapter 3: Foreign Aid to Nepal: An Historical Perspective
106
Appendix 3.1: Reform conditions imposed by the IMF under the PRGF arrangements Prior action for first review (1) Implements VRS (voluntary retirement scheme) at the Rastriya Banijya Bank (RBB) (Phase II) Structural performance criteria (1) Implement time-bound action plan to improve custom administration (timing- Nov. 15, 2004 and Jan. 15, 2005) (2) Fully operationalise the large tax payer office in the Inland Revenue Department (timing- Nov. 15, 2004 and Jan. 15, 2005) (3) Implement new framework for monetary operations, including a liquidity monitoring framework (timing-Nov. 15, 2004) Financial sector reforms (1) Finalise audit of Nepal Rastra Bank’s (NRB) 2003/04 accounts by an international auditor (timing-Jan.15, 2005) (2) Strengthen the NRB (provide for compulsory retirement scheme in NRB employee rules and regulations) (timing-Nov.15, 2004) Public sector reform (1) Finalise audit of Nepal Oil Corporation (NOC) 2003/04 accounts by international auditor (timing- Feb. 15, 2005) (2) Implement automatic pricing mechanism for oil products (timing-Dec. 31, 2004) Structural benchmarks (1) Cabinet approval of Fiscal Transparency Ordinance (timing- Jan. 15, 2005) (2) Amend BFI ordinance including for consistency with other legislation (timing-Feb. 15, 2005) (3) Cabinet approval of Asset Management Companies Ordinance (timing-Jan. 15, 2005) (4) Strengthen the NRB (revise human resource policies) (timing-Nov. 15, 2004) (5) Prepare a time bound action plan to strength Financial Management and Internal Audit Department of NRB (timing-Nov. 15, 2004) (6) Implement restructuring plans for Agricultural Development Bank (ADBN) and Nepal Industrial Development Corporation (NIDC) (timing- Nov. 15, 2004 and Jan. 15, 2005) (7) Adopt Petroleum Products Sale and Distribution Ordinance (timing-Feb. 15, 2005) (8) Complete liquidation/privatisation of five SOEs (timing- Nov. 15, 2004 and Jan. 15, 2005) (9) Cabinet approval of amended Civil Service Ordinance (timing-Nov. 15, 2004) (10) NRB to reconcile accounting data with program monitoring data (Quarterly test date) Notes: (a) See further IMF (2004) for the Quantitative Performance Criteria and Indicative Targets
(b) The World Bank also imposes conditions separately under PRSP. See World Bank (2003b)
Chapter 4
Review of the Literature
“In the broadest sense… most aid does indeed ‘work’. It succeeds in achieving its developmental objectives… contributing positively to the recipient countries’ economic performance, and not substituting for activities which would have occurred anyway. That is not to say that aid works in every count. Its performance varies by country and by sector. On the criterion of relieving poverty, even the aid which achieves its objectives cannot be considered fully satisfactory… [T]he relief of poverty depends both on aid and on the policies of the recipient countries – a collaboration in which aid is definitely the junior partner. And there is a substantial fraction of aid which does not work… Further, bilateral donors often have political and commercial motives for aid, which can interfere with developmental objectives. When these motives predominate, the results can be harmful to growth and to the poor”(Cassen and Associates, 1994: 7).
4.1 Introduction
From World War II to date, the main goal of most developing countries has been to
achieve rapid economic growth. Foreign aid has provided a major source of finance
for developing countries trying to achieve this goal. For example, in some countries
aid as a share of government revenue has been more than 50 per cent (Sevensson,
1997). However, many of them have failed to improve their condition. There have
been extensive studies of the impact of aid on economic growth, and the findings
remain mixed.
Many researchers have attributed the failure of aid financed development to the lack
of good policy environment and poor governance. This has led donors to devise
conditional lending, known as program aid. Program aid is given to support the
recipient government’s budget on the condition that the government carry out
“growth-promoting” policy reforms and improve governance.1 Aid is disbursed in
1 Growth promoting policies are generally regarded as market friendly and less state intervention.
Chapter 4: Review of the Literature 108
tranches upon “satisfactory” policy reforms. However, many other researchers believe
that the very conditionality is the cause of aid failure. They argue that reform agenda
lacks country ownership as they are imposed by the donors. As a result, they face
political resistance. Moreover, the sequence and pace of reforms may not suit a
particular country’s condition. Reviewing the merits of conditional lending, Easterly
(2003: 38) has expressed doubts about the effectiveness of selectivity in aid
allocation. He has characterised the imposition of conditions as “no more than a
wistful hope, rather than a policy with consequences” in circumstances where “a
nation will selectively receive aid if it is a ‘good performer’ – unless it is a bad
performer, in which case it will receive aid from the ‘bad performer’ fund.” Easterly
(2003) has also argued that donors are as much responsible for the past failure of aid
as recipients. According to him, donors are judged by the amount of money spent and
hence are driven by the desire to “move money”.2 This creates potential moral hazard
and incentive problems for both donors and recipients. He has, therefore, emphasised
the need for independent evaluations of aid-funded projects as recommended by the
Meltzer Commission (2000).
However, in this survey, we cover two aspects of the literature. First, we review the
main body of literature concerning aid effectiveness in terms of economic growth, and
related to this, the impact of aid on savings and investment. Second, since aid is
channeled through the government and government’s fiscal position has implications
for domestic savings and investment, we survey the studies that have examined the
impact of aid on government revenue and expenditure.
2 According to Easterly, Judith Tendler observation as far back in 1975 that “A donor organisation’s sense of mission … relates not necessarily to economic development but to the commitment of resources, the moving of money…” remains valid even today.
Chapter 4: Review of the Literature 109
4.2 Aid, economic growth, savings and investment
The first formal argument in favour of foreign aid was given by Rosenstein-Rodan
(1961). He argued that aid was required to change countries from economic
stagnation to self-sustaining economic growth. He believed that each dollar of foreign
resources in the form of aid would result in an increase of one dollar in total savings
and hence investment. McKinnon (1964) calls this the “classical view”.3 Rosenstein-
Rodan extensively investigated the use of capital inflow and its requirements in
underdeveloped countries. Aid should be continued, he believed, until
underdeveloped countries could mobilise a level of capital formation sufficient for
self-sustaining growth. However, he argued that foreign capital inflow should be
within the limit of absorptive capacity of the developing countries.
Chenery and his associates (Chenery and Bruno, 1962; Adelman and Chenery, 1966;
Chenery and Strout, 1966) stressed that many goods have strategic importance in
efficient industrial growth but cannot be produced domestically in the early stages of
development. According to them, foreign aid can have a large favourable impact on
growth rate when such bottleneck is binding.4 McKinnon (1964) calls this the
“modern view”.5
Chenery and his associates identified three phases of development, and, based on an
extended Harrod–Domar growth model, argued that the stage of growth determines
3 Johnson (1958) held a similar view that foreign investment directly adds to domestic savings and hence lifts the investment rate. 4 A similar view was held by Manne (1963). 5 McKinnon (1964) constructed a growth model of the Harrod-Domar type to illustrate the ideas of Chenery and his associates. In particular, a general framework is given for evaluating the “pay-off” in terms of economic growth of foreign transfers under different values of savings and export parameters.
Chapter 4: Review of the Literature 110
the size of the existing savings–investment gap. During the first phase, due to the
shortage of financial resources, investment levels are below the rate required to
achieve targeted growth. Aid can be used to fill the gap between available savings and
investment required to meet the targeted growth.
During the second phase, a trade gap appears, as export earnings are insufficient to
finance required imports of capital equipment and raw materials. Hence, foreign aid is
needed to finance imports. During the third phase, although the savings–investment
gap would disappear, due to structural rigidities the foreign exchange gap would
continue requiring aid to finance imports. Because of aid’s role in filling the savings–
investment and exports–imports gaps, the model developed by Chenery and his
associates has come to be known as the two-gap model.6
The two-gap model has been tested by a number of economists and policy makers
because of its path-breaking nature. For example, Rahman (1968) used the same
cross-sectional data that Chenery and Strout used for 31 less developed countries in
1962, and then ran a least squares regression of the savings ratio on the ratio of capital
inflows to GNP. Rahman found support for Haavelmo’s (1963) hypothesis that in a
developing country domestic savings is not only a function of national income but is
6 The idea of the two-gap model was first developed by Chenery and Bruno (1962) in the context of Israel. Adelman and Chenery (1966) applied the idea to Greece. Then Chenery and Strout (1966) formally developed the two-gap model to link aid to economic growth at different stages of development. They used data from 31 developing countries to identify their stages of development and to determine their needs for foreign assistance. The model was illustrated by using the example of Pakistan’s transition. The two-gap model was criticised on the grounds that it ignores the substitution possibilities between imports of consumption and investment goods, and between domestic savings and foreign exchange. The critics argue that developing countries should be able to transform surplus domestic resources into export production to earn foreign exchange. But as Thirlwall (1983: 295) has noted, “If it were that easy, the question might well be posed, why do most developing countries suffer from chronic balance of payments deficits over long periods despite vast reserves of unemployed resources?”
Chapter 4: Review of the Literature 111 also related inversely to the inflow of foreign capital. Thus, domestic savings may fall
if capital inflow is very large. These results appeared to challenge the assumption of
the models of Chenery and his associates that foreign capital is used only for
augmenting investment and not as a substitute for domestic savings.
Griffin (1970) also found evidence that contradicted the two-gap model. He argued
that aid was a substitute for savings, and hence a large part of foreign capital was used
to increase consumption rather than investment. Griffin raised the issue of fungibility
of aid. He argued that the government might increase public consumption with
increased foreign capital inflows by changing the composition of its expenditure. At
the same time, the easy availability of foreign aid might discourage the government
from taking steps to mobilise domestic resources. He further claimed that foreign
capital inflows financed the capital-intensive projects. This increased the capital-
output ratio in the economy. Based on an ordinary least squares (OLS) regression
analysis of data from 32 underdeveloped countries for the period 1962-64, Griffin
concluded that aid did not contribute to economic growth; instead aid was associated
with a drop in savings.
As in the case of his first study, in a second study with Enos, Griffin found a
significant negative association between aid and growth. Griffin and Enos (1970)
argued that instead of contributing to growth, aid could lower growth because it was
substantially motivated by the politics of donors. Their regression analysis of data
from 15 African and Asian countries for the period 1962-64 showed that there was no
close association between the amount of aid received and the rate of growth of GNP.
In the same study Griffin and Enos even found that average economic growth was
Chapter 4: Review of the Literature 112
inversely related to the ratio of foreign aid to GNP in 12 Latin American countries for
the period 1957-64. They further found that an extra dollar of aid was associated with
a rise in consumption of about 75 cents, and a rise in investment of only about 25
cents. They concluded that while aid could lower savings, it might also retard long-
run economic growth by distorting the composition of investment.7 However, Griffin
and Enos were aware of the limitations of their studies due to methodological and data
problems, some of which were later highlighted by their critics.8
Kennedy and Thirlwall (1971) rejected the claim made by Griffin (1970), and Griffin
and Enos (1970) that foreign aid reduces domestic savings, and increases
consumption rather than investment. Commenting on Griffin (1970), they noted, “…..
a reduction in domestic saving is not a necessary concomitant of increased capital
imports, and even if it was this would not be a sufficient condition for rejecting capital
imports if consumption is a desirable or productive activity” (1971: 137). The
government might divert foreign assistance to public consumption expenditure such
as on education and health, which may have high positive return. They argued that
over all capital-output ratio might fall even though some particular capital-intensive
projects were financed by foreign capital. According to them, the negative regression
7 Yano and Nugent (1999) found that aid financed over expansion of non-traded sector may cause growth immiseration. This study will be reviewed later in this chapter. 8 Weisskopf (1972) examined the relationship between foreign capital inflows and domestic savings for a sample of 44 underdeveloped countries, using time-series data for the post-war period (at least seven years). Weisskopf hypothesised that the level of domestic savings would be behaviourally related to the level of net foreign capital inflows. Weisskopf’s conclusion was consistent with those of Rahman (1968) and Griffin and Enos (1970), which both found that the impact of foreign capital inflows on domestic savings in underdeveloped countries was significantly negative. Voivodas (1973), in a simplified version of the two-gap model, found no significant relationship between the inflows of foreign capital and the rate of growth of GDP. Voivodas used pooled data for 22 developing countries. Critiques attributed his result to two violations of the underlying assumption of the two-gap model. The first was the spill-over effect of foreign capital inflows on domestic consumption, ignored by the two-gap model. The second was the assumption of a fixed capital–output ratio.
Chapter 4: Review of the Literature 113 result between foreign capital and domestic savings implies that foreign assistance is
given on the basis of recipient’s low savings.
In line with Kennedy and Thirlwall (1971), Stewart (1971) also criticised Griffin’s
views of foreign aid and domestic savings. She argued that in developing countries
while some forms of consumption expenditure (e.g., on health and education) may
increase growth, some forms of investment expenditure (e.g., in luxury goods
industries) might have a little impact on development. Thus, for the negative
relationship between domestic savings and foreign capital inflows, she noted, “the
regressions Griffin quotes show the relationship between current account of the
balance of payments and domestic savings and cannot be interpreted as a guide to the
impact of long term capital on domestic savings”(1971: 141). She argued that Griffin
had wrongly hypothesised that current account deficit (matched by capital flows in the
form of aid) caused lower savings. Rather the correct causality should be from low
savings to higher current account deficits and hence higher aid.
Eshag (1971), too, pointed out some internal inconsistencies in Griffin’s model. For
example, according to Eshag, Griffin’s results are due to implicit assumption of full
employment of resources and their flexible uses. In this framework, savings is the
only constraint on investment. Eshag wondered how consumption could rise if aid did
not increase income or output. According to him, this could happen if aid was in the
form of consumption goods, distributed free of charge like “dole”.
Papanek (1972) criticised Griffin’s view that aid leads to increased consumption
instead of domestic savings. Papanek acknowledged that so-called “revisionist”
Chapter 4: Review of the Literature 114 contributions were useful in challenging overly optimistic views of the positive
benefits of foreign capital inflows. He also pointed out that as long as the effect of an
additional unit of foreign resources on investment is less than one, its effect on
savings would appear to be negative.
Papanek further argued that the negative statistical relationship between savings and
foreign inflows could be partly attributed to an accounting convention and might not
be a behavioural relationship. For example, if food aid is distributed to the poor,
domestic savings and investment may not be affected by the given food aid. However,
the accounting system could show a decline in savings because poor people consumed
in excess of their income. Thus, Papanek argued that developing countries with lower
economic growth and mass poverty are likely to receive a higher proportion of aid
that might increase consumption rather than investment. In addition, he noted, “as
long as both savings and foreign inflows are substantially affected by third factors
[such as natural disaster], the negative correlation between the two found in many
studies sheds little or no light on their causal relationship”(1972: 950).
In many studies, researchers simply ignored the different components of foreign
resources and used aggregate amount to investigate the relationship between foreign
aid and domestic savings. This might be a source of misleading conclusions.
Therefore, Papanek (1973) disaggregated all capital inflows into three components:
foreign aid, foreign private investment and all other inflows, in his cross-country
regression analyses of 34 countries in the 1950s and 51 countries in the 1960s. He
found that all inflows had a statistically significant positive effect on growth, but more
importantly, aid affects growth significantly more than any other factors.
Chapter 4: Review of the Literature 115 Newlyn (1973) attempted to reconcile the findings of Papanek and those of Rahman
and Griffin and Enos. He argued that “only if consumption grants are inappropriately
treated as capital items will the confusion cited by Papanek arise”. He added: “[T]he
confusion would be due to inappropriate specification of capital inflows rather than to
any characteristics inherent in the accounting convention in relation to behaviour”
(1973: 867). Newlyn further demonstrated that while negative values between 0 and 1
of regression parameters would normally mean a reduction in the dependent variable,
in this case national resources used for investment to promote growth, no such
implication could be drawn in the aid–savings context. Only if the negative parameter
value exceeds unity can it be concluded that aid leads to an absolute reduction in the
total amount of resources being used for investment.
Stoneman (1975) was critical of studies by both the “revisionists” and their critiques
for failing to distinguish between two main effects of foreign transfers. They are (a)
the balance of payments effect, and (b) the structural change effect. The former refers
to higher investment and consumption made possible by higher imports with the help
of foreign inflows. The later refers to the influence of foreign inflows on exports,
capital-output ratio and income distribution. Stoneman used cross section data from
188 countries between the period 1955 and 1970 and applied OLS method to test his
model. He assumed that economic growth depended on gross domestic investment,
net inflow of direct investment, net inflow of foreign aid and other foreign long-term
flows, and the stock of foreign direct investment. Stoneman found support for the
positive relationship between foreign aid and economic growth. However, he was
aware of the possibility of a non-linear relationship between foreign transfers and
economic growth, and concluded that “… we can offer no opinion on the possibility
Chapter 4: Review of the Literature 116
that there is an initially favorable impact of foreign investment on growth, say up to
twenty percent of GNP, after which further domination has a negative effect”
(Stoneman, 1975: 18).9
Over Jr. (1975) was critical of Griffin and Enos’ use of OLS technique and believed
that their work suffered from serious simultaneity bias. Therefore, he replicated
Griffin and Enos’ study by using the same data set; but instead of OLS, Over Jr. used
2SLS. In the system of equations, aid was first taken as a function of investment
levels (or savings); then savings was taken as a function of the fitted aid values from
the first equation. Based on his findings, Over Jr. rejected the claims of Griffin and
Enos (as well as of Weisskopf) and concluded, “…aid complements growth – and
even elicits an additional matching increase in the domestic savings rate” (Over Jr.,
1975: 755).
Gupta (1975) in a cross-country analysis of 40 developing countries attempted to re-
examine the debate between the revisionist (mainly of Rahman, Griffin, Enos) and
orthodox (e.g., Papanek) views on the savings-aid and growth-aid relationships by
taking the direct and indirect effects of foreign aid. Following the critiques of the
revisionists, the savings rate was assumed to depend, among other variables, on per
capita GDP, growth and foreign capital inflows. The indirect effect of foreign inflows
on savings rate was modeled by assuming that foreign inflows affect growth
positively which, in turn, affects savings. He claimed that the sign of the total (direct
plus indirect) affect cannot be determined a priori.
9 Later studies, to be reviewed, explicitly modelled the possibility of a non-linear relation and estimated the optimal aid-GNP ratio.
Chapter 4: Review of the Literature 117 Thus, Gupta (1975) is the first known study to model the simultaneity between
savings and growth where both are affected by foreign inflows. As Over Jr. (1975),
Gupta used 2SLS, and the estimates revealed that foreign inflows affect savings rate
negatively (the direct effect), but growth rate positively (the indirect effect). The total
effect of foreign capital on savings rate was found to be negative. This result may
appear puzzling: if foreign inflows affect savings (and hence investment rate)
negatively then growth should be affected negatively as well. However, Gupta’s
findings can be justified if foreign inflows do not completely crowd out (offset)
domestic savings, and hence there would still be a net increase in total investible
resources. This is exactly what Newlyn (1973) said when he was trying to reconcile
the two different views on foreign aid.
Following Papanek (1973), Gupta also disaggregated foreign inflows into three
different components: foreign aid, foreign private investment and other foreign
inflows (e.g., short-term borrowings). He found the same results as in the model with
aggregate foreign inflows. That is, all the disaggregated components affect savings
negatively, but growth positively. In contrast to Papanek’s findings, Gupta also found
that the effect of aid was the least among the three components.
Thus, it seems that the earlier studies (1960s and 1970s) do not show a consensus on
the positive effects of aid. Contrary to the optimistic view, a number of studies found
that aid and other inflows reduced domestic savings and helped increase consumption.
Others argue (e.g. Stewart, Thirlwall and Papanek) that it is possible for aid to
associate negatively with savings. This happens as aid is given on the basis of needs
determined by low per capita income and low savings. Additionally, food aid, which
Chapter 4: Review of the Literature 118
is supposed to increase consumption, could be negatively related to savings.10 So too
could emergency relief aid designed to help with shocks and disasters. These types of
aid are not intended to maximise growth. Hence, any careful study of aid
effectiveness should distinguish between different types of aid. Any aid-growth study
must also recognise that the impact of aid on growth may take a longer period to be
detected econometrically.
Mosley (1980) performed a two-stage least squares regression (2SLS) with a sample
of 83 less developed countries for the period 1969-77. The model and methodology of
this study is very similar to Gupta (1975). In the model, level of development was
assumed to depend on savings, aid and other foreign capital inflows. Aid, in turn, was
assumed to depend on level of development. Thus, he hypothesised that aid
influenced and was influenced by a country’s level of development. Mosley (1980) is
the first study to recognise that the impact of aid might take some time to be noticed,
and hence used lagged response of GNP to aid. Mosley found a significant negative
correlation between aid and GNP per capita. However, when he divided samples into
30 poorest countries and 53 middle-income countries, he found a different result. In
the poorest country group, Mosley found that aid was positively correlated to growth,
if aid was lagged five years; but in the case of middle-income countries, he found that
aid was negatively correlated to growth.
Gupta and Islam (1983) used a sample of 52 developing countries for the periods of
1950-60 and 1965-73. The sample countries were divided into three different income
10 Some argued that even food aid might disrupt domestic production and distribution, making a country more dependent on aid than before (Linear, 1985).
Chapter 4: Review of the Literature 119
groups (based on 1973 per capita income) and three geographic regions (Asia, Africa
and Latin America). As in Gupta (1975), Gupta and Islam analysed direct and indirect
impacts of foreign capital inflows with a wide variety of social and structural
variables. They specified and estimated a simultaneous equations model in which the
savings rate and the growth rate affect each other, and both are affected by foreign
inflows. They also decomposed the aggregate foreign capital into three components:
foreign aid, foreign private investment and other inflows. While they found a positive
relationship between foreign aid and economic growth, they concluded that domestic
savings played a more important role in augmenting growth.
Dowling and Hiemenz (1983) found a significant and positive relationship between
aid and economic growth. Their study was based on a sample of 52 developing
countries over the period 1968-79. They further divided the total sample into high-
growth (31) and low-growth countries (21). They used an extended version of the
model applied by Papanek (1973) and Mosley (1980). The differences were that they
added four policy variables designed to express different aspects of government
policy in each country. Thus, Dowling and Hiemenz pioneered the study that
examines the role of policy environment in aid effectiveness.11
These policy variables were: (1) degree of openness of the economy (expressed by
exports plus imports, both net of oil as a proportion of GDP); (2) the role of
government in domestic resources mobilisation (measured by central government tax
revenue as percentage of GDP); (3) the share of public sector in economic activities
11 In later studies, Boone (1996) and Burnside and Dollar (1997) concluded that aid does not work in an environment of “bad” policies. This has been used to justify aid disbursement based on policy reforms. Boone and Burnside-Dollar studies will be reviewed later in the chapter.
Chapter 4: Review of the Literature 120
(measured by total government expenditure in GDP); and (4) a measure of financial
repression (M2/GDP). They found that, especially in the high-growth countries, some
of these policies have positively influenced the aid–growth relationship. In particular,
liberal trade and financial policies improved overall growth performance in the case
of high-growth countries. In the case of slow-growth countries, only liberal trade
policies played an important role in explaining income growth with improvements in
government tax revenue. The share of government expenditure in GDP was not found
to have a significant impact on growth in either group of countries.
The Intergovernmental Task Force commissioned a study by Cassen and Associates
(1986) to assess the impact of aid.12 Cassen and Associates found that aid could work
positively in recipient countries. They qualified this by arguing that if appropriate aid
was provided in a satisfactory policy context and if all other components of growth
were in place, then the statistical relationship between aid and growth would be
positive. In other words, aid did not work in every country; rather its performance
varied by country and sector. They further argued that the effectiveness of aid
depended on different components and sources of aid. In particular, they found that
bilateral aid was more politically and commercially motivated than multilateral aid,
and hence could have some harmful effect on growth.
Cassen and Associates also mentioned the importance of coordination and
management. For example, misunderstanding can often exist between official
agencies and non-government organisations. As a result, their work does not
12 This task force was the initiative of the donor countries, and the World Bank acted as the secretariat. Cassen and Associate updated their work in 1994, and their conclusions remain more or less the same as their 1986 study.
Chapter 4: Review of the Literature 121
contribute to any coherent set of activities; nor do they coherently complement
development activities undertaken within the country. Cassen and Associates reported
a proliferation of aid-funded projects, initiated here and there in an almost haphazard
way.
This creates what they described as “aid-overload”, that is, aid flows beyond the
administrative and management capacity of the recipient. This strains the recipient
government’s ability to supply counterpart funding, leading to delays in the
disbursement of aid funds and implementation of projects. In other words, aid fails
when it is provided beyond the absorptive capacity – a point noted earlier by
Stoneman (1975). Studies, for example, by Hadjimichael et al. and Durbarry et al., to
be reviewed later, identified optimal aid to GDP ratio at which diminishing returns to
aid applied in the economy.
Mosley et al. (1987) conducted multiple linear regression analyses for three time-
periods between 1960 and 1980. The equation to be tested was derived by assuming a
welfare function of the government as in Heller (1975).13 The equation suggests that
the effectiveness of aid is determined by three parameters of the government welfare
function. They are: (a) weight attached to deviation of government investment from
desired level, (b) weight attached to deviation of borrowing from desired level and (c)
the extent to which desired government investment expenditure rises as private
investment diminishes. The effectiveness of aid is also assumed to depend on (d) the
share of aid allocated to recurrent budget, (e) the extent of aid to which aid crowds out
13 The Heller type models will be reviewed later in this chapter.
Chapter 4: Review of the Literature 122 private sector investment, (f) ratio of changes in output to changes in private capital
stock and (g) ratio of changes in output to changes in government capital stock.
In the cross-country data in the 1970s, they found very little correlation between the
growth of GNP and aid-GNP ratio. They hypothesised that this could be due partly to
non-aid influences on growth and party to inter-country differences in the way aid
was used. Since their primary concern was the inter-country differences in aid use
and its effect on aid effectiveness, they have divided the sample into four categories:
(a) low aid-low growth, (b) high aid-low growth, (c) high aid-high growth and (d) low
aid-high growth. They used the cut off points of over 5 per cent aid/GNP ratio and
over 4 per cent GNP growth to define a high aid and high growth country. They found
that the only two variables that had significant impact on growth in the 1970s were
savings rate and export growth. When they controlled their sample for these two
variables, the general finding was that “the rate of return on capital is higher and the
share of aid inflows allocated to the development budget are, on average, higher in
‘high aid, high growth’ countries than in ‘high aid, low growth’ countries, whereas the
impact of aid inflows on private-sector capital investment is about the same in each
group”.
Mosley et al. then investigated aid effectiveness over time with a system of three
equations. In the first equation, growth was assumed to depend on aid, other financial
flows, savings, growth of literacy rate and export growth. In the second equation aid
was a function of initial per capita GNP, initial mortality rate, growth, OPEC and
Arab League dummies. The third equation assumed that mortality rate was a function
of aid, initial per capita GNP and growth. Thus, the model incorporated the ideas of
Chapter 4: Review of the Literature 123
Papanek and Stewart that aid is given on the basis of needs, and the interdependence
of aid, savings, growth and level of development. The main conclusion of Mosley et
al. study is negative. That is, they did not find any significant correlation between aid
and growth.14 Among the possible reasons for this negative findings they identified
two reasons – (a) aid diversion to non-productive uses and (b) negative price effects to
the private sector (aid crowding out).
In another study, Mosley (1987) employed OLS and 2SLS using data from 1960 to
1984 for 67 developing countries. He found that there appeared to be no statistically
significant correlation in any postwar period, either negative or positive, between
inflows of development aid and the growth rate of GNP in developing countries when
other causal influences on growth were taken into account. He referred to the
micro/macro paradox, whereby most of micro project studies on aid effectiveness
found positive results, whereas macro studies did not find any evidence of positive
effects of aid. Mosley noted three points in relation to the micro/macro paradox. First,
there were inaccurate measurements in both micro and macro studies. Second,
fungibility of aid within the public sector could reduce the effectiveness of aid. Third,
is the possibility of crowding out of the private sector by aid-financed activities, as
they compete for skilled manpower. According to him, all these factors need to be
taken into account when examining the issue of aid effectiveness.
Bowles (1987) is the first known study to econometrically examine the issue of
causality between aid and savings. He used time-series data for 20 less developing
14 In a similar subsequent study, Mosley et al. (1992) found that countries progressed in a counter-clockwise manner from low aid-low growth to low aid-high growth phase.
Chapter 4: Review of the Literature 124
countries from 1960-81 and employed the Granger causality test to examine the
causal relationship between foreign aid and domestic savings. In half of the sample
countries, Bowles found no causal relationship between aid and savings, and in the
other half, the direction of causality was mixed. In three cases changes in savings
were shown to cause changes in aid, in five cases the converse, and for the remaining
two there was bi-directional causality.
Rana (1987) performed a study of 14 Asian countries using both time-series and
pooled cross-section data for the period 1965-82. Following Gupta (1975) and Gupta
and Islam (1983), Rana used simultaneous equations techniques. In his model, there
were two endogenous variables (growth rate of GDP and gross domestic saving as a
percentage of GDP) and five exogenous variables (foreign aid as a percentage of
GDP; foreign capital investment including long-term borrowing as a percentage of
GDP; change in exports as a percentage of GDP; change in labour force; per capita
GDP). In contrast to Gupta and Gupta-Islam, Rana found that foreign capital made a
positive contribution to the growth of these Asian countries, and in general higher aid
flows were associated with more productive investment.15
Levy (1988) conducted a study of 22 sub-Saharan African countries whose population
was over one million. In a pooled cross-section of time-series data, the study covered
a period of 14 years from 1968 to 1982, with two sub-periods before and after 1973.
The post 1974 data represented a period when domestic investment exceeded
domestic savings by more than the amount in the previous period. That is, the
15 A later study by Rana with Dowling (Rana and Dowling, 1988), found similar results that foreign capital flows made a positive contribution to the growth of Asian developing countries.
Chapter 4: Review of the Literature 125 savings-investment gap in the post 1974 period was higher than the pre 1974 period.
The results in both sub-periods (1968-73 and 1974-82) and for the 15 years (1968-82)
period as a whole showed that aid was positively and significantly correlated with
investment and economic growth. In the first sub-period, the estimates indicated that
an additional dollar of foreign aid raised domestic investment by 0.92 dollars with a
standard error of 0.278. In the later period, the response of investment to aid was at
least as high as in the initial period. For the entire period, an additional dollar of aid
was found to be associated with an increase in investment by 1.08 dollars with a
standard error of 0.244.
Levy also found statistically significant and positive relationship between aid and
economic growth (in both their level and changes). The results were not found to be
sensitive to stages of development proxied by per capita income, nor to simultaneous
estimation bias.
Snyder (1990) revisited the aid-savings debate sparked by Griffin and Enos in the
1970s. Following the comments on Griffin and Enos by Stewart, Thirlwall and others
that the negative aid-savings relationship could be due to some omitted variables,
Snyder included per capita income as an additional variable in his study of 50 low-and
middle-income countries. He found that although savings correlated negatively and
significantly with aid, the relationship lost significance when per capita income was
included in the OLS regression. He also found significant negative relationship
between aid and per capita income, implying that poorer a country, higher is the aid
flows. Thus, Snyder’s findings lend support to the traditional views as opposed to
pessimistic views of Griffin and Enos. However, he noted that the coefficient of aid in
Chapter 4: Review of the Literature 126 the regression, although small and statistically not significant, was consistently found
to be negative. Thus, he concluded that there could be some moderate tendency
toward aid switching (to consumption or unproductive use), but not to the extent as
claimed by Griffin and Enos.
Snyder also replicated Gupta’s 1975 study by including per capita income in the
model for 28 countries, which were common in both studies, to account for the
difference in their results. The coefficient of aid was found to be significant and
negative as in Gupta’s original study even after including per capita income.
However, when an additional 22, mainly poor and low-income countries, which
received substantial aid were added to the sample, the estimated coefficient of aid
became small and non-significant in the presence of per capita income. Snyder
believed that Gupta’s findings of strong negative aid-savings relationship could be
due to sample composition, which included a very few low income countries or sub-
Saharan African countries, but contained several middle income European countries,
oil exporters and other nations that are not typically aid recipients.
Snyder’s findings are broadly consistent with those of Bowles (1987) who did not
find any causality (in Granger sense) in half of his sample of 20 countries. As
highlighted earlier, in remaining countries the causality was mixed.
Killick (1991) also analysed aid inflows to sub-Saharan Africa and found that aid had
been less effective in promoting economic development than it was in other regions.
For aid ineffectiveness, Killick emphasised these four factors: (1) the recipient
country’s policy environment; (2) its limited absorptive capacity, (3) an unfavorable
Chapter 4: Review of the Literature 127 world economic environment, partly due to donor policies; (4) weaknesses in donor
agencies.
Killick argued that the policies of a recipient country had a decisive influence on the
effectiveness of program, sectoral and project aid. For example, policy mistakes
contributed to a decline in export market shares and in savings and investment. Aid
effectiveness also depends on a country’s absorptive capacity – that is, whether a
country is capable of utilising additional aid to productive use (this depends on
available domestic resources such as skilled manpower, quality of institutions and
recurrent costs of project. Furthermore, donors’ own policies (for example, promotion
of commercial objectives and foreign policy) may be an obstacle for the effectiveness
of aid. Thus, in many ways, Killick’s conclusions are similar to those of Cassen and
Associates (1986).
Islam (1992) estimated the foreign aid and economic growth relationship in
Bangladesh by using annual time-series data for the period 1972-88. Total aid was
decomposed into grants and loans as a proportion of GDP to estimate the effect of
each on growth rate. Again aid was disaggregated into three components: food aid,
commodity aid and project aid. Islam’s results indicated that foreign capital could
play a positive role in the process of economic development. However, not all
components of aid were equally important. Loans and food aid appeared to have a
stronger influence on economic growth than commodity and project aid. Islam also
found that domestic resources contributed more strongly to growth than aggregated
foreign resources.
Chapter 4: Review of the Literature 128 Brewster and Yeboah (1994) conducted a study of 14 highly aid-dependent countries
in which both aid growth and aid/GNP ratios were greater than 6.7 per cent. They
used data from 1969 to 1987 and applied simple descriptive statistical techniques. The
results for 9 out of 11 aid-favoured countries showed negative savings growth over a
period of nearly two decades. They concluded therefore that aid had not been
contributing to growth and savings in desirable directions in the countries under
study. They suggested that the ineffectiveness of aid could be due to adverse terms of
trade, poor returns on investment and low labour productivity. That is, the adverse
effects of these factors could outweigh any positive benefits of aid.
Hadjimichael et al. (1995) examined the impact of macroeconomic policies,
exogenous factors and structural reforms on growth, savings and investment in sub-
Saharan Africa. They used 31 countries from the region for the period 1987-92.
Specific policy variables such as government investment, the public budget deficit
and inflation were taken into the analysis. Although the concepts of ‘absorptive
capacity constraint’ and aid ‘overload’were recognised by early studies (e.g. Chenery
and his associates, and Cassen and Associates), which may cause the returns to aid to
decline after a certain point, Hadjimichael et al. is the first study to examine the
possibility of a non-linear aid–growth relationship. Thus, a squared aid term was
included in the regression to capture possible non-linear aid–growth relationship.
They found that aid was subject to diminishing returns due to recipient countries’
absorptive capacity. The contribution of aid to GDP growth declines if aid/GDP ratio
exceeds 25 per cent.
Chapter 4: Review of the Literature 129 Walle and Timothy (1996) investigated effectiveness of aid from seven donor
countries (United States, United Kingdom, Japan, Canada, Denmark and Sweden) to
seven African countries (Botswana, Burkina Faso, Ghana, Kenya, Senegal, Tanzania
and Zambia). Walle and Timothy argued that despite some progress in human welfare
indicators, in most African countries aid did not contribute to fostering economic
growth and poverty alleviation. Due to political instability and civil conflict, progress
has been reversed in some countries. From 1980 to 1993 the rate of economic growth
was found to be negative in these African countries. In addition, similar to Cassen and
Associates and Killick’s observations, Walle and Timothy found that the lack of a
government’s own management capabilities contributed to the poor performance of
aid. Other weaknesses were lack of country ownership, poor coordination with
donors, and inability to cover recurrent costs.
Boone (1996) used five-year and decade average data for 96 countries from the period
1971-90 to analyse the importance of political regimes to aid effectiveness. He found
that while aid increased consumption, higher consumption did not benefit the poor.
Boone also claimed that aid had an insignificant impact on improvements in basic
measures of human development such as infant mortality, primary schooling ratios
and life expectancy. Since there was no significant relationship between aid and these
measures, Boone argued that aid inflows primarily benefited a wealthy political elite.
He further claimed that aid increased the size of government but did not significantly
increase investment. Finally, Boone found that the impact of aid did not vary
Chapter 4: Review of the Literature 130
according to whether recipient governments were liberal democratic or highly
repressive.16
Bowen (1998) used a sample of 67 less developed countries for the period of 1970-88.
Models were specified to allow for direct and indirect effects of aid on growth. He
modeled the direct and indirect effects by following a methodology, known as
“Expansion Methodology” where a basic model linking aid to growth was extended
by taking into account of aid’s influence on the constant and coefficients of other
variables. Bowen found that aid was not significantly associated with economic
growth directly; instead aid was found to have substituted domestic savings.
Khan (1999) performed an aid/GDP Ganger causality test using data from Pakistan
and found a negative and significant association between aid and economic growth.
The study was based on data from 1972-93. Khan attributed the negative aid–growth
relationship to the lack of cooperation between donors and recipients.
In some studies, for example, Yano and Nugent (1999), the effectiveness of aid was
judged according to a country’s ability to promote tradable sector and its contribution
to the expansion of the export market. Yano and Nugent estimated a model of the
“transfer paradox” for a small open economy with non-traded goods. They considered
the welfare effect of development aid and demonstrated that a transfer paradox can
occur in a small country in the presence of non-traded goods.17 They used time-series
16 Boone found the same in his earlier 1994 study, which attracted the attention of the influential The Economist magazine. The findings were summarised by the Economist (Dec. 10, 1994) as aid is “down the rat hole”. 17 Aid is a transfer from developed countries to developing countries in order to enhance the welfare of the recipient. However, paradoxically, welfare can decline if aid is used for the non-traded sector.
Chapter 4: Review of the Literature 131 data for 44 aid dependent countries for the period 1970-90, and showed that if aid
went to finance the expansion of non-traded (and/or import-competing sectors), a
transfer paradox might arise and net welfare might decline.
Yano and Nugent concluded: “[T]he expansion of the non-traded goods sector can
change the domestic price of the non-traded good in such a way that the otherwise
beneficial effect of aid may be offset” (1999: 432). They argued that “under certain
conditions, the over-expansion can more than offset the beneficial effect thereby
giving rise to the transfer paradox even in a small country” (1999: 432). They found
evidence of the immiserisation effect of aid in Congo, Uganda, Bangladesh and
Nepal. That is, aid may lead to slower or negative economic growth depending on its
sectoral distribution. As reviewed earlier, Levy (1988) alluded to the importance of
aid to accelerate structural change and the growth of tradable sector.
However, after re-examination of the Yano-Nugent (1999) model, Choi (2004)
pointed out “the expansion of the non-traded goods sector is necessary and sufficient
proof that the capital transfer is welfare improving and no transfer paradox
occur”(2004: 250). He argued that during the Marshall Plan, a significant portion of
aid was also used to purchase medicine to combat tuberculosis, build railroads and
water system in French North Africa, and this could not be welfare reducing. Based
on the Marshall Plan examples, he further argued that the expansion of non-traded
sector (such as infrastructure) was essential for the eventual expansion of the tradable
sector.
Chapter 4: Review of the Literature 132 Corruption could be a major reason for the ineffectiveness of aid in many developing
countries. Many argue that aid can increase political instability; a corrupt and an
inefficient government may survive with the support of aid. For example, Rodrik
(1996) suggests that aid can help a bad government to survive. Knack (2000) points
out that higher aid levels erode the quality of governance in a number of ways. They
encourage rent seeking and other forms of corruption, they fuel conflict over control
of aid, and more importantly, they allow the hiring of the most skilled people in the
donor’s organisation at high rates, which disadvantages the local organisations and
government.
Following Boone (1996), some later studies attempted to examine the effect of
corruption by incorporating various indices of governance. One important study in
this area is Burnside and Dollar.
The Burnside and Dollar and related studies
The study by Burnside and Dollar (BD) (1997, 2000) became very influential for
donors across the world, particularly because of its introduction of economic policy
and governance variables in the aid–growth equation. In addition, BD included
several institutional and political variables such as assassinations, ethnic
fractionalisation and institutional quality.18 In many ways, BD’s studies shared the
conclusions of Boone (1994, 1996) and created a pessimistic view about aid.19 Hence
BD’s work resulted in a wave of aid effectiveness studies, considerably different from
18 Burnside and Dollar (2000) is almost identical to their 1997 study. The study was slightly modified by breaking down the original sample into middle-and low-income countries. Their study created a heated debate on the issue of aid effectiveness among both academics and policy makers. 19 As with the study by Boone, Burnside-Dollar study was reviewed in The Economist under the title, “Making Aid Work” (The Economist, Nov. 14, 1998).
Chapter 4: Review of the Literature 133 the traditional aid effectiveness studies. The BD study (along with that of Boone)
generated as much academic controversies in the late 1990s as the GE (Griffin and
Enos) study along with Weisskopf did in the 1970s.
BD’s study was based on a panel of 56 countries and six four-year time periods, from
1970-73 to 1990-93. They constructed a policy index variable from measures of
budget surplus, inflation and openness to interact with foreign aid. They also used a
measure of institutional quality to capture security of property rights and efficiency of
the government bureaucracy. They ran a number of regressions in which growth rates
in recipient countries depend on initial per capita national income, aid, and indices
representing policies and institutions.
BD argued that the growth process is directly dependent on the quality of economic
policy and institutions. They found that in a good policy environment foreign aid had
a positive effect on growth. They further found that bilateral aid was influenced by
donor interest variables and strongly positively correlated with government
consumption, while multilateral aid was largely a function of income level, population
and good policy.
The World Bank (1998) extended the BD study. It used a general equilibrium-growth
model to examine the endogeneity and non-linear effects of aid, and the impact of aid
on economic policies and institutional environments in recipient countries. The World
Bank also addressed the issue of aid fungibility. Its empirical analysis revealed that
aid helps stimulate economic growth and reduce poverty but only when strong
institutions and good economic management exist in recipient countries. In other
Chapter 4: Review of the Literature 134 words, aid leads to faster economic growth, poverty reduction and achievements in
many social indicators in developing countries with sound economic management, but
is less effective where there are weak institutions and policies. The World Bank’s
studies generated further interest in aid-effectiveness, initially sparked by BD.
Durbarry et al. (1998) used both panel (four periods with six-year averages) and
cross-section data techniques for 58 developing countries for the period 1970-93 to
investigate the aid–growth relationship. They employed an augmented Fischer–
Easterly type growth model in which macroeconomic and policy variables are
allowed to affect long-run growth rates. For possible non-linearity in the aid–growth
relationship, they included a quadratic term of the aid/GDP ratio in the regression.
They argued that the possibility of non-linearity in the aid–growth relationship should
be recognised from the outset. Durbarry et al. concluded that foreign aid inflows had a
beneficial effect on developing countries with stable macroeconomic policy
environment. However, according to them, it does not imply that aid affects growth
negatively in the absence of good policy. They noted that the inclusion of policy
variables provides a more fully specified model, but aid–growth effects are not
dependent on it as claimed by BD. They further argued that while a low amount of aid
did not generate faster growth, very high aid/GDP ratios (over 40-45 per cent) were
also associated with slower growth. This gives an indication that the optimum
aid/GDP ratio is around 40-45 per cent.
Guillaumont and Chauvet (2001) examined the effect of aid using pooled data for two
12-year periods – 1970-81 and 1982-93 for 66 developing countries. They argued that
the macroeconomic effectiveness of aid crucially depended on external and climatic
Chapter 4: Review of the Literature 135 factors rather than on the economic policy environment. They found that aid was
effective in that it accelerated growth in vulnerable countries. They therefore
concluded that the worse the environment, the greater the need for aid and the higher
its potential for productivity. Their model was estimated using the two-stage least
squares technique incorporating an aid to GDP ratio, an aid–policy interaction term
(similar to the one used by BD, 1997, 2000), and an interaction term between aid and
a composite external environment indicator. The results revealed that the variables
that combined aid with the policy environment indicator was not statistically
significant, while the variables that combined aid with the external environment
indicator had a statistically significant (and positive) impact on growth. The finding
does not, in other words, support BD’s claim that aid effectiveness depends on a good
policy environment.
Dalgaard and Hansen (2001) also empirically investigated the aid–growth results of
the BD model. They used the same data set used by BD to reassess aid effectiveness,
and found that the BD results were crucially data-dependent. When five observations
were excluded from the samples (Gambia, 1986-89, 1990-93; Guyana, 1990-93; and
Nicaragua, 1986-89, 1990-93), the results changed because these observations had a
very big influence on the coefficient to the aid–policy interaction term. They also
showed that by deleting other combinations of observation the opposite outcome
could be produced, that is, aid stimulated growth irrespective of the policy
environment. However, they found support for the BD hypothesis that the aid–growth
relationship is non-linear and there is diminishing returns to aid.
Chapter 4: Review of the Literature 136 Collier and Dehn (2001) included shocks in the aid–growth relationship to analyse aid
effectiveness, and the shocks were measured by an index of export prices. They used
the BD data set and found that “negative shocks have substantial adverse effects on
output, which even over a period of four years or less are around twice as large as the
direct loss of export income” (2001: 10). They further discovered that once these
shocks were included, the BD result became robust to choice of sample. Thus, with
the inclusion of shocks in the BD model, Collier and Dehn found that the shocks were
highly significant. On the other hand, they claimed that the adverse effects of negative
shocks on growth could be mitigated through offsetting increases in aid.
Collier and Dollar (2002) re-examined the core BD results with an extended data set
from 59 developing countries and took four-year averages for the period 1974-97.
They found support for BD that aid works in a good policy environment. They also
concurred with the findings of the World Bank’s Assessing Aid that donors were not
successful in inducing lasting reforms in recipient countries. Hence, Collier and
Dollar concluded that aid should be directed to countries, which already have good
policy environment and better governance. That is, aid should be selective.
In addition, Collier and Dollar estimated the allocation of aid that would maximise the
reduction of poverty. They argued that to maximise poverty reduction, aid should be
allocated to countries that have a high level of poverty combined with a good policy
environment. That is, donors can affect growth through their allocation of aid, and
growth in turn will lead to poverty reduction only where there is a good policy
environment. Collier and Dollar argued that the actual allocation of aid was different
Chapter 4: Review of the Literature 137
than that of poverty-efficient allocation, and claimed that with a poverty-efficient
allocation, aid productivity would be almost double.
Dalgaard et al. (2002) addressed various issues of aid effectiveness. They examined
cross-country correlations between aid, savings and growth, and demonstrated why
plots of cross-country averages were distorted by identification problems and
heterogeneity biases. They stated that “once these problems are taken into account,
cross-plots of aid versus growth and savings support the panel data regression results
of a positive impact of aid on growth” (2002: 2). Dalgaard et al. also investigated the
impact of geographic circumstances on aid effectiveness.20 They estimated the model
using data from 1974-77 to 1990-93 of a panel of 54 countries. They found that in the
BD type growth equation, aid was much more effective in countries outside of the
geographical tropics. When Dalgaard et al. investigated the results of the BD (1997)
model, they found that aid was effective even in bad policy environments but aid had
diminishing impact on growth. They argued that in the BD model, the interaction
between aid and policy was ambiguous. Their findings are consistent with the studies
by Dalgaard and Hansen (2001) and Guillaumont and Chauvet (2001) as they also
found the interaction between aid and policy index to be statistically insignificant.
Easterly et al. (2003) re-assessed the relationship between aid, policy and growth as
modeled by BD (2000), extending data from 1993 to 1997. They added extra
countries and observations to the BD data set, but used the same methodology to re-
examine aid effectiveness in the context of good policy. The aid–policy interaction
term was found not only insignificant but also appeared with different signs. Thus,
20 Bloom and Sachs (1998) found that growth rates across the countries are affected by their geography.
Chapter 4: Review of the Literature 138 according to them, aid effectiveness does not depend on policy environment as
claimed by BD.
In fact, there is no general agreement about the identification of exactly which
policies are crucial. If the three policies emphasised by the BD model were actually
robust determinants of the return on aid, this would be a major breakthrough. From
this perspective, the findings of the BD model do not stand up to scrutiny. Easterly
(2003) points out that without further testing and research for the validity of the
conclusion, the general findings have been passed on via the media, and then cited by
international agencies claiming that an increase in foreign aid is justified for those
countries having good policies and governance.21 As Easterly states, “a regression
result was passed from one source to the next without questions about the robustness
or broader applicability of the result” (2003: 25). Thus, he cast doubts about the
wisdom behind the policy recommendations that aid should be allocated selectively to
those countries with good policy.22
Hansen and Tarp (HT) Survey of aid effectiveness studies
Hansen and Tarp (2000) examined and summarised empirical cross-country studies of
aid effectiveness going back to the 1960s, and concluded that aid contributed
positively to economic performance. They surveyed 131 cross-country regressions
from 29 different studies, which they categorised into “three generations”. The first-
21 International aid agencies such as the British Department for International Development, the Canadian International Development Agency and many others have been influenced by the BD findings and conditioned aid on policy reforms. 22 Easterly (2003: 38) has characterised the imposition of conditions as “no more than a wistful hope, rather than a policy with consequences” in circumstances where “a nation will selectively receive aid if it is a ‘good performer’ – unless it is a bad performer, in which case it will receive aid from the ‘bad performer’ fund.”
Chapter 4: Review of the Literature 139 generation studies used the Harrod–Domar growth model and the two-gap model. In
39 first-generation regressions, aid was assumed to be an exogenous net increment to
the capital stock of the recipient country, and hence it was not treated as a component
of national income adding to both consumption and investment. From the first-
generation studies they found that aid led to an increase in total savings. Thus, given
the underlying Harrod–Domar model, the implication is that aid spurs growth.
In the second-generation empirical work, Hansen and Tarp focused on the relationship
between aid and growth via investment. Moreover, in these studies different financing
components of investment such as domestic savings, aid and other foreign capital
inflows were separated. In 18 cross-country studies, a positive relationship was found
between aid and investment, implying that aid made a positive contribution to growth.
They found in 17 studies that there was a significant positive impact of aid on
investment, while only one study showed an insignificant effect. A second strand of
the second-generation literature investigated the relationship between aid and growth
in reduced-form equations. In 72 regressions, 40 showed a positive impact of aid on
growth, 1 a negative impact and 31 an insignificant effect.
The third-generation studies were primarily focused on four more recent studies
(Hadjimichael et al., 1995; Durbarry et al., 1998; Hansen and Tarp, 1999; and BD,
1997). These studies used large number of sample countries with panel type data from
over a number of years. They also included measures of economic policy and the
institutional environment in reduced-form growth regressions, along with traditional
macroeconomic variables. Finally, they addressed the endogeneity of aid and
explicitly treated the aid–growth relationship as non-linear.
Chapter 4: Review of the Literature 140 These empirical works suggest that aid increases savings and investments and that
there is a positive relationship between aid and growth. Hansen and Tarp’s survey
reveals that in each generation of studies, those claiming a negative aid–growth or
negative aid–savings relationship are clearly in the minority. They conclude,
We find a consistent pattern of results. Aid increases aggregate savings; aid
increases investment; and there is a positive relationship between aid and
growth….The positive aid—growth link is a robust result from all three
generations of work. (Hansen and Tarp, 2000: 122).
Post HT Survey
The World Bank (2001) conducted a study of 10 African countries. The study
demonstrates the effects of a range of African policy experiences. Despite large
amounts of aid going to these countries, not all have been able to reap the benefits.
Among the 10 countries surveyed, Ghana and Uganda have been most successful in
achieving sustained good policy and economic outcomes. According to the study,
based on reforms undertaken in the 1980s and 1990s, Ethiopia, Mali and Tanzania
have been mixed reformers, and Congo and Nigeria non-reformers. The study further
shows that a large amount of aid with bad policy environment could further delay
reforms. The cases of Ghana and Uganda indicate that donors should concentrate on
technical assistance and other “soft support” and on policy dialogues in the pre-reform
period. Thus, this study reinforced the conclusion of BD and conditionality based
lending.
Gounder (2001) used time-series data for the period 1968-96 to estimate the aid–
growth relationship in Fiji. While the model was based on a neoclassical production
Chapter 4: Review of the Literature 141 function, it was estimated using ARDL approach to cointegration. The aid data were
disaggregated into various forms such as bilateral, multilateral, technical cooperation,
grants and loans aid. The results showed that foreign aid contributed significantly to
Fiji’s economic growth. However, not all forms of aid had the same effects. Bilateral,
grants and technical cooperation grants contributed more significantly to growth than
any other forms of aid.
Using the same methodology and data from 1975 to 1997, Gounder (2003) found a
positive and significant relationship between aid and growth in Solomon Islands. She
also performed Granger causality tests, which showed bidirectional causality between
aid and economic growth in Solomon Islands.
Hansen and Tarp (2001) analysed the aid–growth relationship by comparing the latest
studies of cross-country aid–growth regressions where the relationship was modeled
as non-linear. They used two different data sets: from 1974 to 1993 for 56 countries,
and 1960 to 1987 for 45 countries. Hansen and Tarp took into account country-
specific effects and aid endogeneity. They justified the introduction of country-
specific effects in the regressions by arguing that diversity among developing
countries in terms of their natural endowments and cultural and socio-economic
characteristics should be a major concern in cross-country comparison of aid
effectiveness.
Hansen and Tarp argued that in the models estimated by Hadjimichael et al. (1995),
Durbarry et al. (1998) and Lensink and White (1999), the aid variables were included
as uncentred regressors. As a result, the estimated coefficient of the aid variable was a
Chapter 4: Review of the Literature 142 measure of the partial effect of aid on growth evaluated at no (zero) aid. Thus, they
noted, “we have chosen to center the aid variable around the sample mean, so the
estimated aid coefficient is the marginal effect of aid on growth evaluated at the
mean, 0.061” (2001: 552). When endogeneity of aid and country-specific effects are
taken into account, the empirical findings show that aid increases the growth rate,
which is not conditional on the policy index as claimed by BD (1997, 2000).
However, Hansen and Tarp found that there were decreasing returns to aid. They did
not identify the optimal aid/GDP ratio beyond which the decreasing returns will set in.
A possible reason for the ineffectiveness of foreign aid could be the negative effect of
high aid inflows on the absorptive capacity of a recipient country. Lensink and White
(2001) empirically examined the Aid–Laffer curve with respect to growth to show
that high aid inflows have negative effects. In the regression analysis, pooled cross-
section time-series data were employed, taking period averages calculated from three
five-year periods (1975-79, 1980-84 and 1985-89) and one three-year period, in 111
countries. They found aid/GNP ratio of about 50 per cent as the turning point at which
aid starts to have a negative effect on growth. This is considerably higher than the
findings of Hadjimichael et al.(1995) and Durbarry et al. (1998).
Hasan (2002) examined the aid–savings relationship, using cointegration and Ganger
causality techniques. The study used a sample of 27 developing countries for the
period 1960-98. The causality results showed that causal direction and lag vary
markedly across countries. In more than half of the countries studied, Hasan found no
causal relationship between aid inflows and domestic savings. In the remaining
Chapter 4: Review of the Literature 143 countries the direction and pattern of causality were mixed. Thus, Hasan’s findings
are similar to those of Bowles (1987), reviewed earlier.
Mavrotas (2002) used disaggregated aid data to examine aid effectiveness in India.
Aid was disaggregated into project, program and technical assistance for the period
1970-92, and the cointegration technique was applied for the estimation procedure.
The findings suggest that in the case of India, the composition of aid seems matter for
the effectiveness of aid, given their different impacts on the economy. Mavrotas
concluded that both program aid and project assistance had a negative influence on
growth in India. However, a study by Dawson and Tiffin (1999) found that aid neither
promoted nor adversely affected economic growth in India. Using annual data from
1961-92, Dawson and Tiffin found that ODA (Official Development Assistance) was
stationary while GDP had a unit root. Thus, in their interpretation the long-run
relationship between aid and growth could not exist.
Instead of estimating the impact of aggregate aid, White and Dijkstra (2003)
attempted to estimate the effectiveness of program aid, mostly from Sweden. They
also conducted eight country case studies (Bangladesh, Cape Verde, Mozambique,
Nicaragua, Tanzania, Uganda, Vietnam and Zambia). They examined the impact of
donor–recipient policy dialogue on the pace of reforms and the impact of program
funds on imports and balance of payments.
As an estimation method, they employed quantitative techniques (to assess fund
impacts) and a qualitative approach (to assess policy dialogue). They also performed a
counterfactual analysis of balance of payments, assuming that the exchange rate
Chapter 4: Review of the Literature 144 would be depreciated to increase exports (for example, 15 per cent), there would have
been no increase in reserve, and a different scenario for debt service (debt service paid
actual, no or low percentage paid, and paid in-between) in the absence of aid. They
concluded that program aid had been useful to achieve macroeconomic stabilisation
through financing the budget deficit and supporting the exchange rate to avoid
devaluation.
Islam (2003) examined the relationship between foreign aid and economic growth
under different political regimes. The model was based on the neoclassical production
function, and aid was assumed to augment technological progress. Islam used the
generalised least squares (GLS) method for the estimation procedure. The data were
for a sample of 21 sub-Saharan and 11 Asian countries for the period 1968-92, and the
countries were separated into two types of authoritarian regimes, tinpot and
totalitarian. Tinpot regimes are defined as focusing on personal consumption and
avoiding unnecessary spending on repression; they are thus considered a weak form
of dictatorship. Totalitarian regimes are those that entertain maximum power and use
highly repressive measures to stay in power but at the same time make an effort to
promote economic growth.
When the model was tested on sub-samples of tinpot and totalitarian countries
separately, the results indicated that the effect varies substantially across regime
types. The coefficient of aid was found positively significant for totalitarian countries
but negative and statistically insignificant for tinpots. The results further showed that
tinpot regimes involved more corruption than totalitarian regimes. Further, weak
forms of dictatorship (that is, tinpots) did not implement policy reforms, possibly
Chapter 4: Review of the Literature 145 because of the pressure of special interest groups, whereas strong dictatorships
implemented policy reforms relatively easily. Thus, aid was found to be effective in
stimulating growth in totalitarian countries but ineffective in tinpot countries.
Chatterjee and Turnovsky (2005) developed a theoretical model through which
foreign aid affects macroeconomic performance. They decomposed total aid into tied
and untied aid and found that the long-run impact of a tied aid program depends
crucially on the elasticity of substitution in production. Thus, they noted that tied aid
is more effective in economies with a low degree of substitution between factors of
production. They further stressed, “tied aid generates dynamic adjustments, as public
capital is accumulated in the recipient economy. Its effect on the long-run growth rate,
and the extent to which this is beneficial, depends on the elasticity of substitution in
production, as well as co-financing arrangements, if any, imposed on the recipient
economy, and how its government chooses to react to the additional flow of
resources”(2005: 39).
Aid and Poverty
In recent years, the basic objective of foreign aid has been replaced by the objective of
poverty reduction in recipient countries. In the past few decades a bulk of research has
shed new light on role and effectiveness of aid in reducing poverty in developing
countries. Most donors are therefore changing their focus to pro-poor based economic
growth with the aim of poverty reduction. In other words, the effectiveness of foreign
aid is being analysed from a different perspective, focusing on aid’s capacity to
reduce poverty that has been the principal target for aid donors as well as many
developing countries.
Chapter 4: Review of the Literature 146 Mosley et al. (2004) based on cross-country evidence found a significant relationship
between pro-poor public expenditure and poverty reduction. The GMM and 3SLS
techniques were applied to data from 34 countries for the period 1980-2000. They
used a pro-poor public expenditure index to investigate the effect of aid on poverty
rather than on economic growth. They developed a range of methodologies for
devising one overall measure of pro-poor public expenditure. They considered public
expenditure on the basics of health care, primary education, water and sanitation, rural
roads and agricultural extension service as pro-poor. In addition to pro-poor
expenditure, they also used measures of inequality and corruption, which also
influenced the poverty leverage of foreign aid. They found that aid that went to pro-
poor public expenditure had a longer lasting impact on poverty.
Their findings are consistent with those of Collier and Dollar (2001, 2002). Mosley et
al. concluded: “[W]e feel that inter-country reallocations of aid could increase such
poverty impact. Among the criteria that could form the basis for such reallocations,
we find corruption, inequality and the composition of public expenditure to be
particularly strongly associated with aid effectiveness” (2004: 235).
Gomanee et al. (2005) found that aid improves welfare indicators measured by infant
mortality and Human Development Index (HDI). According to them, aid might have
direct (by increasing incomes or access to social services) and indirect (through an
effect on growth) effects on welfare. They used a panel of four four-year and one five-
year period averages data from 1980 to 2000 for 104 countries. When they divided the
sample into low-income and middle-income countries, they found greater impact of
aid on improving welfare in low-income than middle-income countries. However, in
Chapter 4: Review of the Literature 147 contrast to Mosley et al. (2004), they did not find any strong support that aid impacts
welfare through pro-public expenditure (PPE).23 Thus, based on the results, they
concluded, “although aid increases PPE in low-income countries, the efficacy of PPE
in increasing welfare is quite low while significant amount of aid to social sectors are
independent of government spending” (2005: 364)
Studies of aid effectiveness in Nepal
Although Nepal is an aid-dependent country, only few attempts have been made so far
to address the issue of aid effectiveness in Nepal in empirical terms. Mihaly (1965)
and Stiller and Yadav (1979) were early studies that addressed the issue of foreign aid
in Nepal. They claimed that aid had not been used effectively due to the lack of
administrative capacity and political instability. During 1951-59, ten different
cabinets were formed because of weak leadership and lack of strong political will.
Based on descriptive analyses, these authors argued that policy makers had a poor
understanding of the role of aid in the Nepalese economy, and the country therefore
suffered from poor absorptive capacity. Almost four decades later, Mihaly (2002)
maintained that aid has not been effective in Nepal, due mainly to lack of
administrative capacity and political will. In addition, Mihaly (2002) argued that
Nepal’s aid was greatly influenced by the strategic interests of donors. Thus, Mihaly
noted: “[A]n offer of aid can appear to manifest the donor’s political support for the
recipient – as did the Chinese cash grant to Nepal in 1956. And a facility financed by
aid can be of strategic value to the donor – as are the Indian and Chinese-built roads
in Nepal” (2002: 218).
23 They constructed PPE index estimating government expenditure on education, health and sanitation.
Chapter 4: Review of the Literature 148 Poudyal (1988) using data from 1964 to 1982 performed regression analyses between
foreign aid and economic growth, and aid and domestic savings. He found that aid
had a significant positive effect on the level of GDP. He also estimated the model
using five years lag of aid. For the one and two years lag, the coefficients were found
smaller and negative. But for the four and five years lag, the coefficient were positive
and larger. Thus, he claimed that the long running aid funded projects did not
contribute to the economy in the short-run. The negative short-run relationship
between aid and growth was attributed to the use of domestic resources (as a part of
recipient contribution) to support these long running foreign financed projects.
However, he did not find statistically consistent results between aid and domestic
savings. Paudyal strongly believed that foreign aid contributed positively to the
development of Nepal. It was only possible through aid to build major projects and
physical infrastructure, which would not have been built due mainly to resources
constraints.
Dhakal et al. (1996) tested causality in the Granger sense between foreign aid and
economic growth in eight countries, including Nepal, for the period 1970-90. The
other countries in the sample were India, Pakistan, Thailand, Botswana, Kenya,
Malawi and Tanzania. The empirical results showed that foreign aid did not cause
economic growth in Nepal. Of the possible reasons, they identified political
corruption as causing a significant diversion of aid, from importing capital goods to
consumption goods. Singh (1996) also expressed almost similar views about the
effectiveness of aid in Nepal. He found that despite a significant amount of foreign
aid, Nepal did not achieve any impressive economic progress during the three decades
(1950-1980). Based on a descriptive analysis, Singh concluded that a small group of
Chapter 4: Review of the Literature 149 people (e.g. top level bureaucrats, ruling politicians, real state owners, researcher,
contractors and designers) benefited from aid in Nepal.
Khadka (1996) conducted a descriptive analysis of the role of foreign aid in Nepal’s
economy during 1961-90 by examining some macroeconomic indicators. Khadka
concluded that despite Nepal’s heavy dependence on foreign aid, the role of aid in
improving the level of incomes, savings and investment had not been significant. He
further noted that while a huge amount of aid was invested in the agriculture sector,
Nepal went from being a net exporter to a net importer of food grains. Thus,
according to Khadka, political and institutional factors might be highly important for
aid effectiveness in Nepal. However, in another study, using a simple regression
analysis for the period 1960-90, Khadka (1997) found that aid had a positive impact
on the growth of GDP. In this study, he used only bilateral disbursements for aid data
and excluded multilateral disbursements, and hence one only gets a partial picture.
In line with Mihaly (1965, 2002), Stiller and Yadav (1979), Singh (1996) and Dhakal
et al. (1996), Panday (2001) noted that Nepal failed to use foreign aid effectively. As
a result, Nepal suffered from under development and inequalities. He argued that
policy makers are governed by the demands of the aid system without due attention to
country ownership. Although exogenous influences are unavoidable in policy-making
process, the influence of endogenous actors (politician) and process in policy-making
is very weak in Nepal. For example, he noted, “aid provides not just financial
wherewithal but political legitimacy for the government. Senior political leaders
lobby with the donors, not their government or political colleagues, for projects that
are of interest to them or their constituencies” (Pandey, 2001:180). Thus, he believed
Chapter 4: Review of the Literature 150 that poor governance, and lack of strong political leadership without any vision
completely ruined the country.
4.2.1 Summary
Based on the above survey, we can summarise the following main points about aid-
savings-growth relationships:
• The findings are mixed: some found negative and others found positive
relationships between aid and savings, and aid and growth.
• Majority of studies are cross-country analyses.
• Among the single country analyses only a few used the cointegration
technique. Therefore,
o the possibility of spurious relationship is high in the earlier analyses;
o they were also unable to detect long-run relationship between aid and
savings and/or growth.
• More importantly, there are very few studies that involved Nepal. None of
these studies:
o applied cointegration technique;
o disaggregated aid by types and source;
o included policy variables.
A summary of past studies is presented in Table 4.1.
Chapter 4: Review of the Literature 151 Table 4.1: Summary of aid-growth and aid-savings empirical analyses Study Sample Methodology Findings Comments Rosenstein-Rodan (1961)
Almost all aid recipient countries
Descriptive Aid contributes to self-sustaining economic growth
First formal economic argument for aid
Chenery and Bruno (1962)
Israel (1950-59) Estimates based on input-output model and different assumptions about various parameters.
Aid plays dual role to boost investment and foreign exchange resources.
Linked aid to economic growth within an extended Harrod-Domar growth model that incorporates savings and foreign exchange constraints
Adelman and Chenery (1966)
Greece (1950-61)
OLS, 2SLS, Limited Information
Foreign aid contributed to GNP growth
First econometric estimation of an extended Horrod-Domar growth model
Chenery and Strout (1966)
31 underdeveloped countries, (1957-62)
OLS Positive relationship between aid and growth and justified aid for two reasons: to fill the savings– investment gap and the foreign exchange gap
This remains a major model but its assumptions of constant capital output ratio and non-substitution between savings and foreign exchange have been questioned
Chapter 4: Review of the Literature 152 Rahman (1968)
The same data set used by Chenery and Strout
OLS Negative relationship between aid and domestic savings
Has attracted criticism on the ground that there might be other factors for the negative relationship
Griffin and Enos (1970)
15 African and Asian countries (1962-64) and 12 Latin American countries (1957-64)
OLS Negative relationship between aid and savings; aid retards long-run economic growth
This is an extension of Rahman, and suffers from the same shortcomings
Weisskopf (1972)
44 underdeveloped countries
OLS with time-series data for at least seven years post–World War II periods
Impact of foreign capital inflows on domestic savings was found significantly negative
The model ignored continued effects of factors left behind by the war.
Voivodas (1973)
22 underdeveloped countries, 1956-68)
OLS with pooled data
No significant relationship between capital inflows and GDP growth
Focused only on spill-over effects on consumption of foreign aid without including feedback effects
Papanek (1973)
34 underdeveloped countries in the 1950s and 51 countries in the 1960s
OLS Significant positive effect of aid on growth
The findings are still relevant as the study separates different components of aid
Stoneman (1975)
188 developing countries, five years period between 1955 and 1970
OLS Found positive relationship between aid and growth
Aid effects negatively after certain point (beyond 20 per cent of GNP)
Chapter 4: Review of the Literature 153 Over (1975) Same data set
used by Griffin and Enos (1970)
2SLS Aid contributed to growth
First study to analyse simultaniety between aid and savings
Gupta (1975) 40 developing countries
2SLS Total effects of aid on savings were found negative
First study that incorporated feedback between savings and growth
Mosley (1980) 83 less developed countries (1969-77)
2SLS Negative correlation between aid and GNP per capita
First study to recognise lag response of GNP to aid
Dowling and Hiemenz (1983)
52 developing countries, (1962-79) in three-year periods
OLS, added four policy variables in the model
Significant and positive relationship between aid and growth
First study to use policy variables
Gupta and Islam (1983)
52 developing countries (1950-60) and (1965-73)
2SLS Foreign capital made significant contribution to growth
Examined aid effectiveness in countries at different income levels and in different regions
Cassen and Associates (1986)
Extensive qualitative evaluation of aid effectiveness
Discussion based on practical experiences
Aid effectiveness depends on various factors
Very useful and important assessment that highlighted a number of issues for aid effectiveness
Mosley et al. (1987)
81 developing countries (1960-80)
Fiscal response model and extended model of Griffin (1970) and Papanek (1973), OLS and 3SLS
Aid had no significant relationship with GNP growth
Added extra explanatory variables in the Papanek model
Chapter 4: Review of the Literature 154 Mosley (1987) 67 developing
countries (1960-84)
OLS, 2SLS No significant relationship (either positive or negative) between aid and GNP growth
Highlighted the micro/macro paradox in aid-effectiveness findings
Bowles (1987) 20 less developed countries (1960-81)
Bivariate Granger causality test
Found no causal relationship between aid and savings in 10 of 20 surveyed countries
First study to econometrically test aid-savings causality
Rana (1987) 14 Asian countries (1962-82)
Both time-series and cross-section data, OLS, ILS
Positive contribution of aid to growth
Similar to Gupta (1975), but different findings
Rana and Dowling (1988)
9 developing Asian countries, 1965-82
ILS Foreign aid partially contributed to economic growth
Similar findings with that of Rana (1987)
Levy (1988) Sub-Saharan African countries (1968-82)
Pooled cross-section of time-series data, OLS
Aid was positively correlated with investment and economic growth
Divided sample in two sub-periods based on saving-investment gap
Snyder (1990)
50 low- and middle-income countries (1960s, 1970s and 1980s)
Panel data set, OLS
Found positive relationship between aid and savings when per capita income is included in the model.
Also acknowledge that there could be some aid diversion to consumption, but not to the extent as argued by Griffin-Enos
Killick (1991)
Sub-Saharan African countries (1960s-87)
Comparative analysis with other developing countries
Aid effectiveness depended on absorptive capacity and policy environment of recipient
Recognised donors’ policy weaknesses. Thus, similar findings as Cassen and Associates
Chapter 4: Review of the Literature 155 Islam (1992) Bangladesh,
(1972-88) OLS Loans and
food aid affected growth positively more than other forms of aid
Disaggregated aid into food, commodity and project aid as in Papanek (1973)
Hadjimichael et al. (1995)
31 sub-Saharan African countries, (1987-92)
They included some policy variables in the model with aid square term
Aid had a positive impact on growth
Included policy variables and aid square term first time to represent non-linear relationship in the model
Boone (1996) 96 countries (1971-90)
Five-year and decade-average data, OLS
Found no significant relationship between aid, growth and investment
This study attracted much attention due to its pessimistic views of aid
Bowen (1998) 67 less developed countries (1970-88)
2SLS Aid was not associated directly with growth and it had a negative effect on saving rate
Investigated direct and indirect effects of aid using expansion methodology
Burnside and Dollar (1997)
Panel of 56 countries with six four-year time periods, from 1970-73 to 1990-93
OLS and 2SLS Aid had a positive impact on growth only in a good policy environment
Has attracted wide criticisms on methodological and data ground. But has become influential among donors
World Bank (1998
Extensive investigation into aid effectiveness in various countries
Based on a number of background other papers
Aid effectiveness depended on the recipient’s economic policy and institutional environment
Consistent with BD, which focused more on policy environment for the effectiveness of aid
Chapter 4: Review of the Literature 156 Durbarry et al. (1998)
58 developing countries (1970-93)
OLS and GLS Aid–growth effects were not dependent on policy variables
A very high aid/GDP ratios (over 40-45 per cent) create aid over-load
Khan (1999) Pakistan (1972-93)
Bivariate Granger causality test
Found a negative and significant association between aid and economic growth
Political instability might be a major reason
Yano and Nugent (1999)
44 aid-dependent countries, (1970-90)
A model of transfer paradox
Aid could lower welfare if aid was used in non-traded goods sector
However, critics pointed out that non-traded sector such as infrastructure is crucial for development
Hansen and Tarp (2000)
131 cross-country regressions from 29 different studies
A survey of three generations of studies and re-examination of aid-growth relationship
Aid increased savings and investment and positively affected growth
A comprehensive study that clarified the aid–growth relationship
Gounder (2001)
Fiji (1968-96) Aggregate and disaggregated forms of aid, ARDL approach to cointegration
Aid contributed to growth
Used cointegration technique for time-series data
Hansen and Tarp (2001)
56 developing countries, (1974-93)
OLS and GMM
Aid stimulated growth, which was not conditional on policy index established by BD
Took into account country-specific effects; found more convincing results
Chapter 4: Review of the Literature 157 Guillamont and Chauvet (2001)
66 developing countries
Two pooled 12-year periods (1970-81) and (1982-93), OLS and 2SLS
Aid was found to be effective to accelerate growth in more vulnerable countries.
The results were not consistent with BD findings that aid only works in a good policy environment
Dalgaard and Hansen (2001)
The same data set used by BD
Deleted some observations to get different outcomes of BD model
BD model was found to be data-dependent, and hence aid stimulated growth irrespective of the policy environment
Provided further evidence that BD findings were misleading and data dependent
Lensink and White (2001)
111 countries, (1975-89)
Pooled cross-section time-series data, average three five-year periods and one three-years period, 2SLS
After a certain level of aid inflows, aid started to have negative effects
Findings stressed the absorptive capacity of recipient countries
World Bank (2001)
10 African countries (1980s and 1990s)
Comparison of policy experiences between countries
Some countries have been successful in reforming and achieving economic growth
Supports BD’s emphasis on conditionality based lending
Collier and Dollar (2002
59 developing countries (1974-97) on four-year averages
OLS, headcount poverty-gap and square poverty-gap
With a poverty efficient allocation the productivity of aid would be double
Policy implications were unrealistic because if aid was allocated according to mass poverty, all aid would have gone to India and China
Chapter 4: Review of the Literature 158 Hasan (2002) 27 developing
countries, (1960-98)
Cointegration and Granger causality test
For more than half of 27 countries, there was no relationship between aid and domestic savings
The cointegration test was valid only for two countries
Dalgaard et al. (2002)
54 countries, from 1974-77 to 1990-93)
Investigated BD model in a bad policy environment
Aid was found to be effective even in a bad policy environment
Used geographical variables in the model
Easterly et al. (2003)
BD model, data extended from 1993 to 1997
Same methodology used by BD
Aid did not promote growth in a good policy environment
Demonstrates the danger of findings from simplistic research that can form the basis of aid policy of donors
White and Dijkstra (2003)
8 developing country case studies
Qualitative (policy dialogue) and quantitative (counterfactual analysis) of Swedish program aid
The program aid had been successful in maintaining macroeconomic stabilisation, financing the budget deficit and supporting the exchange rate
One can extend further research on aid effectiveness through counterfactual analysis
Islam (2003) 21 sub-Saharan and 11 Asian countries, (1968-92)
GLS Aid had a negative and significant effect on growth
Shows that aid effectiveness depends on types of political regime – tinpots and authoritarian
Chapter 4: Review of the Literature 159 Gounder (2003)
Solomon Island (1975-97)
ARDL and Granger causality
Found a significant and positive relationship between aid and growth.
Aid and growth relationship further confirmed by the bidirectional causality between them
Mosley et al. (2004)
Data set is a pooled sample of 34 countries (1980-00)
GMM, 3SLS Found a significant relationship between poverty reduction and pro-poor public expenditure
Highlighted the importance of aid allocation to pro-poor sectors
Gomanee et al. (2005)
A panel of four four-year and one five-year period for104 countries (1980-00)
OLS Aid contributed to welfare directly and indirectly through growth
Welfare enhancing role of aid does not necessarily depend on pro-poor public expenditure as claimed by Mosley et al. (2004)
Chapter 4: Review of the Literature 160 Studies of aid effectiveness in Nepal
Stiller and Yadav (1979)
Nepal (1951-76)
Descriptive analysis
Aid did not contribute to economic development
Lack of leadership and poor administrative quality were responsible for the ineffectiveness of aid
Paudyal (1988)
Nepal (1964-82)
OLS Aid had a positive and significant relationship with economic growth
This is the first known econometric study of aid- growth relationship in Nepal
Singh (1996) Nepal (1950-80)
Descriptive analysis
Small group of people benefited from aid and created severe income distribution problem
Hypothesis not tested econometrically
Dhakal et al. (1996)
8 countries from Asia and Africa (1970-90)
Bivariate Granger causality test
Except for two countries, foreign aid significantly caused economic growth
Negative relationship between aid and growth in Nepal.
Khadka (1996)
Nepal (1961-90)
Descriptive analysis
Aid did not contribute to economic growth and savings in Nepal
Aid might be helping to improve social indicators
Khadka (1997)
Nepal (1960-90)
OLS Aid had a positive relationship with growth
No explanation for why the results are different from the previous descriptive analysis
Mihaly (1965, 2002)
Nepal (1950-00)
Descriptive analysis
Aid is not effective in Nepal
Aid effectiveness did not improve in three decades
Chapter 4: Review of the Literature 161 4.3 Aid and fiscal behaviour
Many recent studies have analysed the public sector’s fiscal response to aid in
developing countries. This is an important development since most aid goes to the
public sector. Since public-sector budget deficit/surplus has direct implications for
total domestic savings and the current account position, understanding the public
sector’s response to aid is a pre-requisite to understanding macroeconomic impact of
aid. Fiscal response involves identifying how aid funds are allocated between various
expenditure categories and how this ultimately affects levels of public expenditure
and revenue. There are two broad approaches in the literature that address the fiscal
response to aid and aid fungibility. One approach follows the seminal work of Heller
(1975); the other follows the framework of McGuire (1978). The Heller type models
examine government expenditure and revenue behaviour. The McGuire type studies
focus mainly on the issue of fungibility, that is, the use of aid in sectors (or projects)
not in line with the donor’s intended purpose. They also examine aid’s impact on
revenue.
4.3.1 Heller type studies of fiscal response
Heller (1975) examined aid and fiscal behaviour through an econometric model of the
public sector. A cross-section time-series data set was used for 11 African countries
for the period 1960-70. The econometric model developed by Heller has since been
used and tested by a number of researchers in estimating fiscal behaviour of aid.
In the model, Heller postulated that policy makers’ utility depends on the attainment
of target expenditures. Policy makers attempt to minimise loss by minimising
Chapter 4: Review of the Literature 162 deviations of actual expenditure from target levels subject to a budget constraint given
by domestic revenue and aid. In particular, policy makers consider the following
activities: (a) alternative uses of public resources, for example, expenditures for
economic growth, for provision of current social and economic services, and for the
maintenance of political order and stability; (b) the distribution of total output
between the private and public sectors; (c) alternative modes of domestic financing
such as borrowing and taxation; (d) alternative types of external assistance, that is,
grants and loans.
The utility function of policy makers can be expressed as
)1.4..(..................................................].........,;,,),(,[ 21 AABGGTYIFU scg −=
where Ig = public investment expenditure for development purposes, Y-T =
disposable income in the private sector, Gc = civil consumption in the public sector,
Gs = socio-economic consumption in the public sector, B = flow of public borrowing
from domestic sources, A1 = total foreign grants to the public sector from all sources,
and A2 = total foreign loans to the public sector from all sources.
Heller further assumed that a welfare-maximising government attempts to minimise
the following quadratic loss function:
)2.4.(..........)(2/)()(2/)()(2/
)()(2/)()(2/)(
2*10
*987
26
52*
4*
32
210
***
***
BBBBGGGGGG
GGTTTTIIIIL
sssscc
ccgggg
−−−−−−−+−
−−+−−−−−−−+=
ααααα
αααααα
subject to a budget constraint:
Chapter 4: Review of the Literature 163
)3.4........(........................................)1()1()1( 23121 APAPTPBI g −+−+−+=
)4.4(......................................................................23121 APAPTPGG cs ++=+
where a starred variable indicates a target level for each variable. 1-P1, 1-P2 and 1-P3
are the proportions of tax, foreign grants and loans respectively spent on public
investment for development purpose.
The target variables were derived through estimation. For the final estimation
procedure, generalised least square (GLS) and two-stage least squares (2SLS) were
used. The findings showed that aid increased public investment but reduced domestic
taxes and borrowing. Grants were found to be more pro-consumption biased whereas
loans were found to be pro-investment. Tax increases were used more for public
consumption than public investment.
Gang and Khan (1991) used the Heller model to examine the relationship between
foreign aid and the fiscal behaviour of the Indian government. They employed non-
linear three-stage least squares (3SLS) for the estimation procedure and used times-
series data from 1961 to 1984. Gang and Khan used time-series data for a single
country, and employed non-linear three-stage least squares for the whole system.
They claimed that their procedure of combining single equation and 2SLS estimation
was an improvement on the earlier study of Heller. The results showed that grants,
loans and multilateral aid had no significant effect on government consumption. More
importantly, bilateral aid induced the transfer of domestic public resources from non-
investment to investment for development purposes. They argued that this might
happen for two reasons. First, bilateral aid was closely monitored by donors. Second,
Chapter 4: Review of the Literature 164 tied aid imposed conditions to add certain resources into the same project (That is,
they needed counter financing by recipients). On the other hand, domestic tax revenue
was used to finance both civil and socio-economic consumption. Furthermore, an
increase in government consumption would be financed through increased tax
revenue but not through foreign aid.
White (1994) criticised the Gang and Khan study on a number of theoretical and
methodological grounds. White expressed doubts about the estimated target variables,
as there was no guarantee that the resulting estimated targets would be consistent with
constrained equations. White pointed out “It therefore appears that Gang and Khan’s
results are derived from the way in which the target series are estimated: as such the
results can tell us nothing about the Indian government’s fiscal response to aid
inflows” (1994: 160). In addition, White argued that Gang and Khan focused more on
partial results, ignoring reduced-form equations and hence suppressing the model’s
implicit dynamic elements. According to White, Gang and Khan produced misleading
interpretations because of these two factors.
Khan and Hoshino (1992) extended the coverage of Gang and Khan to five South and
South East Asian countries (India, Pakistan, Bangladesh, Sri Lanka and Malaysia).
The time-series data were used for India from 1955 to 1976, Malaysia from 1968 to
1976, Pakistan from 1955 to 1970, Sri Lanka from 1955 to 1976 and Bangladesh from
1972 to 1976. Due to the insufficient time-series data, they regressed the model for
pooled time-series cross-section data. The results showed that aid had impacts on both
the expenditure and the revenue sides of the recipient government’s budget.
Chapter 4: Review of the Literature 165 On the consumption side, aid was seen as an increase in income, and due to the
positive income elasticity, public consumption also increased but the marginal
propensity to consume of foreign aid was less than one. Loans were found to be more
important than grants for public investment. On the other hand, grants reduced the tax
burden while loans increased it. However, McGillivray (1994) pointed out that the
study only showed partial effects and ignored feedback effects. That is, Khan and
Hoshino did not estimate the reduced-form equation to obtain total (direct and
indirect) effects and suffered from the same problem as Gang and Khan.
Ahmed (1996) analysed the impact of aid on the public sector in four developing
countries (India, Pakistan, Bangladesh and Philippines) from the 1960s to the early
1990s. He included in his model the expected income feedback effects into the target
equations. This made his empirical work different from the earlier work by Heller
(1975), Gang and Khan (1991) and Khan and Hoshino (1992). Unlike the earlier
studies, he assumed that borrowing was used to finance both current consumption and
investment. Aid was also assumed to be endogenous in the model. He found that the
overall impact of aid on public sector investment, consumption, domestic borrowing
and taxation varied between countries. Generally, while aid led to an increase in both
public investment and consumption expenditure, it reduced taxation and domestic
borrowing.
Franco-Rodriguez et al. (1998) examined the impact of aid on public sector fiscal
behaviour for Pakistan using data from the period 1956-95. They analysed how aid
revenue affected the government’s fiscal behaviour with respect to tax, borrowing and
expenditure decisions. In a Heller (1975) type model, they allowed domestic
Chapter 4: Review of the Literature 166 borrowing in addition to aid and tax revenue, for the purposes of financing both
capital and recurrent expenditures, and aid was assumed to be endogenous. In
addition, they replaced constraints (equations 4.3 and 4.4 above) on public sector
fiscal behaviour in the Heller model with the following:
BPAPTPI g )1()1()1( 321 −+−+−=
BPAPTPGG ndd 321 ++≤+
where Gd and Gnd are development and non-development expenditure respectively.
The rationale for an inequality constraint is “that there are external constraints, which
limit the manner in which the public sector in developing countries allocates revenue”
(Franco-Rodriguez et al. 1998: 1244). The results of their study showed that only half
of aid went to government consumption, and aid had a slightly positive impact on
public investment and a negative impact on tax efforts.
McGillivray (2000) investigated public sector behaviour in Pakistan using 1956-95
time-series data. The study is similar to the fiscal response model devised by Franco-
Rodriguez et al. (1998). While McGillivray allowed domestic borrowing to finance
both recurrent and capital expenditure in the model, the constraint equation was not
replaced by inequality. McGillivray found that both public investment and
consumption expenditure were positively associated with aid, and aid (both grants aid
and loans aid) had no impact on taxation and non-tax revenue. Grants aid did not have
any impact on public consumption expenditure, but loans aid was positively related
with both socio-economic and civil consumption expenditure.
Chapter 4: Review of the Literature 167 Franco-Rodriguez (2000) analysed the impact of foreign assistance to Costa Rica
using the same framework of fiscal response models as in Franco-Rodriguez et al.
(1998). The data covered the period 1971-94. While aid was endogenised on the
assumption that recipient governments had some control over the amount of aid that
was actually disbursed, borrowing was allowed to finance both development and
recurrent expenditure. The use of inequality in the budget constraint established the
maximum percentage of each revenue category that could be directed to public
consumption. When the model was applied for Costa Rica, it showed a very small
impact of aid inflows on public sector fiscal behaviour.
McGillivray (2002) used the model of Franco-Rodriguez et al. (1998) and time-series
data from 1960 to 1997 to examine the interaction between aid, structural adjustment
and the public sector fiscal behaviour in the Philippines. This study is similar to the
earlier study of Pakistan, but aid was disaggregated into multilateral and bilateral aid.
The results showed that there was a degree of fiscal indiscipline with respect to the
allocation of borrowing and multilateral aid. McGillivray found that almost all
multilateral aid had been allocated to consumption expenditure, and hence, the
multilateral aid to the Philippines had been highly fungible. Similarly, the majority of
bilateral aid had been allocated to public consumption and almost 100 per cent of
borrowing had been allocated to the consumption budget in the Philippines.
McGillivray and Ouattara (2003) investigated the impact of foreign aid on public
sector fiscal behaviour using time-series data for the period 1975-99 for Cote d’Ivoire.
They used the same model developed by Franco-Rodriguez et al. (1998) but in
addition to grants aid and loans aid, foreign debt service was included in the model.
Chapter 4: Review of the Literature 168 Like most fiscal response studies, target variables were approximated, as data on these
variables could not be obtained directly. These targets were estimated as a long-run
relationship, if it was possible to find a cointegrating regression between the target
variables and some explanatory variables. On the other hand, when it was not possible
to establish such a cointegrating relationship, the targets were approximated using
autoregressive techniques. The structural equations were estimated using the non-
linear three-stage least squares technique. McGillivray and Ouattara found that a large
portion of aid to Cote d’Ivoire was used for debt servicing, and aid did not appear to
induce reduction in borrowings. Furthermore, most borrowings were used to finance
government expenditure on both investment and consumption.
4.3.2 McGuire type studies of aid fungibility
Aid is said to be fungible if a recipient country uses aid for its own purposes rather
than those intended by the donors. McGuire type studies investigate whether spending
on sectors to which aid is directed actually increases by the amount of the given aid.
A graphical analysis of the McGuire model is presented in Figure 4.1 for a better
understanding of the aid fungibility problem. McGuire (1978) studied the fiscal
effects of federal grants and subsidies to local governments in the US.24 Usually such
grants or subsidies are given for nominated use by the receiving government. They
may also come with the condition of matching funds from the recipient. Therefore,
the budget constraint of the recipient changes depending on the nature of grants. If the
grant (=BB’) is given without any restrictions, the budget constraint of the recipient
24 As noted by McGuire, the model is applicable to numerous other domestic or foreign grant programs (McGuire, 1978: 26).
Chapter 4: Review of the Literature 169 will shift outward from BB to B’B’. If the grant is conditional on matching funds
(=B’B”) for use in a particular sector then the budget constraint will move from BB to
BB”. Finally, if the grant (=BB’=BB*) is conditional only on its use (but no matching
fund) then the budget constraint will shift outward from BB to BB*B’, allowing an
increase in expenditure only on nominated sector.
Figure 4.1: A graphical presentation of McGuire model
B’ B B* B B’ B” Subsidised goods Source: McGuire, 1978
According to McGuire, the actual post-grant budget constraint may differ from the
above as determined by legal conditions of the grant document. This can happen when
the recipient government’s utility function differs from that of the donor government.
There are a variety of ways the recipient government can transform a conditional
grant into fungible resources. Thus, McGuire used an unknown portion, φ, of the
grants to estimate fungibility, and assumed that the grant recipient was always at an
Chapter 4: Review of the Literature 170
optimal point without taking into account grant conditionality. Given the pre-grant
budget constraint, if the recipient can treat a portion (0 ≤ φ ≤ 1) of the conditional
grant as if it were a pure revenue supplement, then the grant is fungible. If φ = 1, and
the post-grant optimal choice is an interior solution, grant is fully fungible. When φ =
0, grant is not fungible.
One of the well-known studies of aid fungibility was conducted by Pack and Pack
(1990) for Indonesia. Although they did not explicitly recognise McGuire’s work,
their model is very similar to his framework. They assumed that government faces a
budget constraint and possesses community indifference curves depicting the choice
for different public goods to be provided to citizens. Foreign aid was treated as a
budgetary supplement.25 That is, revenue plus aid must equal total development and
current expenditure. There was no provision for internal borrowing since the fiscal
policy showed roughly balanced budgets during the investigation period of two
decades.
From the constrained optimisation solution, Pack and Pack (1990) derived three
equations for estimation in order to explore fungibility of aid and the effects of aid on
revenue raising efforts. The first equation was for non-development current
expenditure,
)5.4..(......................................................................).........,( ttt AIDGDPfCE =
25 This is in line with the way Indonesia used to treat foreign aid before the changes brought about by the economic crisis of the late 1990s. Foreign aid was regarded as revenue in the government budget.
Chapter 4: Review of the Literature 171
= per capita non-development current expenditure in year t, GDPwhere CEt t = per
capita gross domestic product, and AID = all categorical per capita development aid. t
The second equation was for development expenditure,
)6.4(..................................................).........,,,( ,,, TIMEOAIDAIDGDPgD tjtitti =
where Di,t = current expenditure per capita category i in year t, AIDi,t = foreign aid
per capita designated for expenditure category i, OAIDj,t = all other categorical aid to
sectors other than i (all categorical total aid minus designated aid), and TIME = year,
included to capture the possibility that development expenditure may benefit from
scale economies or learning by doing.
The third equation was for government revenue,
)7.4(......................................................................).........,,( tttt AIDoilNonOilhR −=
where R is revenue (excluding foreign aid), which is a function of oil and non-oil
gross product and aid.
The equations were estimated using a Seemingly Unrelated Regression (SUR)
technique for the period 1966-86. The estimated results showed that foreign aid did
not displace development expenditure, instead it stimulated total public expenditure.
Pack and Pack (1990) further found that most categorical aid was spent on the
purposes intended by donors. More importantly, their findings revealed that aid did
not lead to a reduction in domestic revenue.
Chapter 4: Review of the Literature 172 Pack and Pack (1993) conducted a similar type of analysis for the Dominican
Republic for the period 1968-86. In the model, as noted earlier, they assumed that
government possessed a community indifference curve and was faced by a budget
line. They estimated their model simultaneously using the SUR approach. The
findings in the case of the Dominican Republic are different from those found in
Indonesia. Foreign aid in the Dominican Republic was found to be fungible and is
consistent with the negative perception of aid that aid use diverges from its intended
purpose.
Khilji and Zampelli (1991) applied the McGuire framework to study the fungibility of
US aid to Pakistan for the period 1960-86. They used the Full Information Maximum-
Likelihood estimation technique, and found that US assistance, whether military or
non-military, was fully transformed into fungible resources, with an impact on
spending less significant than expected. An additional dollar was treated the same in
the budget regardless of its source.
Feyzioglu et al. (1996) used annual data from 1971 to 1990 for 14 developing
countries. They examined the effects of foreign aid on aggregate as well as various
other components of public spending. They explicitly postulated a variant of the
McGuire (1978) model, but contrary to McGuire allowed the aid recipient to be at a
sub-optimal level. In the spirit of Pack and Pack (1990), the recipient government
buys S public goods, {g1, g2…. gs}, in the market to provide to its citizens. It pays for
these goods by the fungible portion of foreign assistance and all other resources, R
(domestic and foreign), that it has at its disposal. A portion of the earmarked aid is
fungible if it can be treated as a revenue supplement.
Chapter 4: Review of the Literature 173
Feyzioglu et al. found that “a dollar given in official development assistance to
developing countries does not lead to a tax relief effect, instead it causes government
spending to increase by a dollar. Of this increase in government spending, roughly
three-quarters is spent on current expenditure and the remaining quarter on capital
expenditure” (Feyzioglu et al. 1996: 27). Hence, they claimed that the results were not
consistent with the earlier findings that foreign aid was spent entirely on consumption
and not on investment.
Following the same approach, Feyzioglu et al. (1998) analysed the relationship
between foreign aid and public spending for two different samples, 14 and 38
developing countries. They used a panel data set with annual time-series observations
from 1971 to 1990. In the first sample of 14 developing countries, they found that aid
was not fungible at the aggregate level and there was no associated tax relief.26
However, in the case of a larger sample of 38 countries they found that aid was
fungible and part of the funds were used for tax reduction. The results further
indicated that aid was fungible in three out of five sectors examined. Governments
that received earmarked concessionary loans for agriculture, education and energy
reduced their own resources going to these sectors and used them elsewhere.
Moreover, only loans to the transport and communication sectors were fully spent on
the purposes intended by donors.
26 In the sample of 14 developing countries, a new measure of public investment that incorporated investment by all levels of government as well as public enterprises was used. For the second sample, that of 38 countries, they selected a country that had at least 35 per cent of the annual observation for each of the variables used in regression.
Chapter 4: Review of the Literature 174 Swaroop et al. (2000) estimated the impact of foreign aid on the central government’s
development and non-development spending in India. They used annual time-series
data from 1970 to 1995. They also used a panel database over the period of 1980-
1992 for 16 major states in India to analyse the inter-governmental fiscal link. The
study was based on the same underlying theoretical model as Feyzioglu et al. (1998),
and they used ordinary least squares and two-stage least squares regression for the
estimation procedure. To analyse aid fungibility, they made an attempt to demonstrate
two aspects of aid fungibility, one at the federal level and the other at the inter-
governmental level. They showed that the central government converted most foreign
funds, including those earmarked for state governments, into fungible funds and spent
on those activities that would have been undertaken anyway. However, foreign aid did
not influence the internally determined pattern of resource allocation in India.
4.3.3 Other major studies of fiscal behaviour
Gupta et al. (2003) examined the revenue response to inflows of foreign aid in 107
countries during 1970-2000. In the model, they decomposed foreign aid into loans and
grants, and investigated whether the impact of aid on the revenue effort depended on
the composition of aid. They modelled cross-country variation in tax shares as a
function of grants and loans flows in percentage of GDP, controlling for the structure
of the economy (agriculture value-added and industry value-added in percentage of
GDP), openness (the sum of exports and imports in percentage of GDP), and the level
of economic development (real income per capita). The results indicated that
concessional loans were generally associated with higher domestic revenue
mobilisation, while grants had the opposite effect. They argued that the relationship
Chapter 4: Review of the Literature 175 between loans and tax efforts could be influenced by the fact that loans had to be
repaid. Thus, it had a positive effect on the domestic revenue effort. The results also
indicated that foreign aid was non-linearly related to domestic revenue and its impact
was influenced by the level of corruption.
Bulir and Lane (2002) analysed the impact of aid volatility on fiscal behaviour. They
argued that the positive impact of aid was undermined in some cases by the volatility
and unpredictability of aid. Aid is significantly more volatile than domestic fiscal
revenue, and the volatility of aid grows with the degree of aid dependence (see also
Bulir and Hamann, 2001). There has been a perception that aid commitments are a
weak basis for spending plans, particularly when aid is a large component of the
budget. In this case, projected fiscal deficits including committed aid will tend to
overstate the strength of fiscal position. As a policy implication, Bulir and Lane
argued that if aid is volatile or unpredictable, recipient countries have to pursue a
flexible fiscal framework in which tax and spending plans can be adjusted in response
to aid receipts.
McGillivray and Morrissey (2001) critically evaluated the findings of the impact of
aid on public sector fiscal behaviour. In particular, they focused on two important
issues in the earlier findings. First, aid leads to an increase in the total expenditure of
the recipient country by more than the value of the aid inflows, and second, aid
reduces tax revenue. They argued that “ the unintended outcomes resulted from mis-
perceptions or illusions regarding either the real or nominal value of the aid inflows,
or the way in which the aid was to be used” (2001:132).
Chapter 4: Review of the Literature 176 According to McGillivray and Morrissey, the problem of aid fungibility is misleading
since the relevant issue is how aid affects fiscal behaviour and how spending plans are
implemented. They further argued that even in the presence of conditions for
fungibility, spending on the items donors want to support would not necessarily
increase by less than the value of the aid. In an earlier study, McGillivray and
Morrissey (2000) examined the concept of fungibility. They held that if donors and
recipients simply have different preferences in terms of allocation of public
expenditure, fungibility emerges easily; likewise in a case where there may be no
intended fungibility yet spending on the items targeted by donor could decrease.
Nevertheless, their conclusions were consistent with findings that aid was associated
with reductions in tax and other recurrent revenue.
4.3.4 Summary
We have presented a review of studies that address the impact of aid on government
fiscal behaviour. The survey reveals that the aid impact on fiscal behaviour varies
across countries. In some, aid did not lead to a reduction in revenue raising efforts and
aid was not diverted to unproductive uses. However, studies also found that aid was
diverted away from its intended purpose. Some studies found that aid had a positive
impact on public investment but negative impact on tax efforts; others found very
small impacts of aid on public sector fiscal behaviour.
More importantly, none of these studies used cointegration, and analysed impulse
response function to examine the time profile and adjustment of aid, revenue and
expenditure when shock hit any of them.
Chapter 4: Review of the Literature 177 There has been no study of fiscal response to aid in Nepal. A summary of past studies
is presented in Table 4.2.
Chapter 4: Review of the Literature 178 Table 4.2: Summary of empirical studies of aid and fiscal behaviour Study Sample Methodology Findings Comments Heller (1975)
11 African countries (1960-70)
Used cross- section time-series data, and GLS and 2SLS
Aid increased investment but reduced taxes and borrowings
Seminal work on fiscal response model and used government’s utility maximisation framework
Pack and Pack (1990)
Indonesia, (1970-90)
Time-series data and used SUR
Aid did not lead to a reduction in domestic revenue efforts, but stimulated total public expenditure
Model derived from “median voter model”. Focused more on aid fungibility rather than fiscal impact
Khilji and Zampelli (1991)
Pakistan (1960-86)
Time-series data and used FIML technique
Aid was found to be fully fungible
McGuire type model. Examined only the US aid
Gang and Khan (1991)
India (1961-84)
Used time-series data and estimated full system of simultaneous equation with 3SLS procedure
Grants, loans and multilateral aid had no significant effect on government consumption
Heller type model. Due to misspecification of model there exist problems in the interpretation of results
Khan and Hoshino (1992)
5 South and South East Asian countries (1956-76)
Pooled time-series and cross- section data, non-linear 3SLS
Loans were found more positive for investment than grants, and while grants reduced tax burdens, loans increased it
Extension of Heller model. Failed to show total effects (direct and indirect) and thus ignored feedback effects
Chapter 4: Review of the Literature 179 Pack and Pack (1993)
Dominican Republic (1968-86)
Time-series data and used SUR
Found a divergence of aid away from its intended purpose
Model derived from “median voter model”. The results are different from their findings for Indonesia. Thus, fungibility depends on country specific factors
Ahmed (1996) 4 South Asian countries (1960-90)
Pooled time-series and cross- section data. 3SLS
While aid led to increases of both public consumption and investment, it reduced taxation and domestic borrowing
Heller type model. Used feedback effects in estimation of target variables
Feyzioglu et al. (1996)
14 developing countries (1971-90)
Panel data, a model of aid fungibility, OLS, and GMM
Foreign aid was spent on both government consumption and investment
McGuire (1978) type model. Not conclusive about the effectiveness of aid
Feyzioglu et al. (1998)
14 and 38 developing countries (1971-90)
Panel data, OLS and GMM
Aid was not fungible at the aggregate level in a sample of 14 countries but aid was found to be fungible in 38 countries
McGuire (1978) type model. Aid was found to be more fungible in agriculture, education and energy sector
Chapter 4: Review of the Literature 180 Franco-Rodriguez et al. (1998)
Pakistan (1956-95)
Time-series data, non-linear 3SLS
Slightly positive impact on public investment and negative impact on tax effort
Extended the Heller model by allowing borrowing on both capital and consumption expenditure and treating aid as an endogenous variable
Swaroop et al. (2000)
India (1970-95)
Time-series data, and used OLS and 2SLS
Foreign aid did not influence the internally determined pattern of resource allocation
McGuire (1978) type model. Aid fungibility investigated in both federal and state levels
Franco-Rodriguez (2000)
Costa Rica (1971-94)
Time-series data, non-linear 3SLS
A very small impact of aid inflows on public sector fiscal behaviour
Heller type model. Not conclusive result; it could be due to inappropriate target variables and country specific factors
McGillivray (2000)
Pakistan (1956-95)
Time-series data, non-linear 3SLS
Aid associated positively with both public investment and consumption expenditure and aid had no impact on taxation
Heller type model. Disaggregated aid into grants and loan aid, but aid was not endogenised in the model
Chapter 4: Review of the Literature 181 McGillivray (2002)
Philippines (1960-97)
Time-series data, non-linear 3SLS
Almost all multilateral aid has been allocated to consumption expenditure and almost 100 per cent domestic borrowing allocated to the consumption budget
Heller type model. Ambiguous results as he found multilateral aid was also allocated to consumption
McGillivray and Ouattara (2003)
Cote d’Ivoire (1975-99)
Time-series data and applied fiscal response model as a maximising utility framework, non-linear 3SLS
Large portion of aid is used for debt servicing and it does not induce a reduction in borrowing; also borrowing is used for both investment and consumption
Heller type model. The findings suggest that borrowing should be allowed for both capital and consumption expenditure in the model
Chapter 4: Review of the Literature 182 4.4 Concluding remarks
During the 1960s, a number of studies empirically analysed the effects of foreign aid
on savings, investment and growth. Early advocates of development aid argued that
an increase in aid was necessary to boost investment, which in turn would help
achieve high economic growth. They highlighted that the required increase of aid was
only temporary as after some point in time a process of self-sustaining growth would
begin. Thus, aid was needed to help speed up the transition process to a self-
sustaining growth. The theoretical framework adopted by early advocates of aid was
an extension of the Harrod-Domar growth model, which came to be known as “two-
gap” model.
In the 1970s, the two-gap model was criticised on a number of grounds such as its
assumption of constant capital-output ratio and non-substitutability between domestic
and foreign resources. Several empirical studies found that aid affected savings
negatively, which in turn retarded economic growth. These studies also revealed that
an increased flow of aid primarily led to an increase in consumption rather than
investment. However, these studies came under severe criticisms on both
methodological and data grounds. Subsequent studies, which took account of some of
these criticisms found mixed results with regard to aid-savings-growth relationships.
Studies in the 1980s examined the aid-savings-growth relationships using more
complex models. They analysed the impact of policy environment, the possibility of
aid over-load (or the impact of a lack of absorptive capacity). There emerged some
consensus that the impact of aid may decline after certain levels of aid and policy
Chapter 4: Review of the Literature 183 environment are likely to affect aid effectiveness. There was also recognition of
limited contribution of aid as economic development depends on host of other factors.
A new trend in aid effectiveness studies emerged since the early 1990s. These studies
examined the fiscal behaviour in the presence of aid. As in the case of aid-savings-
growth studies, no firm consensus on the impact of aid on government revenue and
expenditure (both level and structure) has been found.
Since the late 1990s, the aid effectiveness debate shifted its focus to the conditional
policy environment of aid recipient countries. However, many observers feel uneasy
about conditional lending and fear that it may lead to less aid to countries, which need
aid the most.
Chapter 5
Methodology and Data
“Until not so long ago econometricians analysed time-series data in a way that was quite different from the methods employed by time-series analysts…Neither group paid much attention to the other until the appearance of two types of disquieting … studies. The first set of studies claimed that forecasts using the econometricians’ methodology were inferior to those made using the time-series analysts’ approach; the second type claimed that economic data in fact are not stationary, and this could lead to serious problems with traditional statistics … These revelations caused econometricians to look very hard at what they were doing, leading to extensive research activity … that has markedly changed and improved the way in which econometricians analyse time-series data” (Kennedy, 1992: 247).
5.1 Introduction
Past studies of aid effectiveness were mostly based on cross-country data; only few
studies used time-series data from individual countries. It is generally believed that
single country times-series analysis is more useful, as it can capture country-specific
features that may not be found in a cross-country analysis. Note though that time-
series data may produce spurious relations if the variables under study are linked to
common factors. If the variables follow a time trend (that is, their means and
variances are not constant over time), they are said to be nonstationary. Two
nonstationary variables may be found related, while in fact they are not, simply
because of the common nature of their time trends. Thus, according to Engle and
Granger (1987), the direct application of ordinary least squares or generalised least
squares to nonstationary data produces regression results that are misspecified or
spurious in nature. These regressions tend to produce performance statistics that are
inflated, such as high R2, F and t-statistic, which often lead researchers to commit
Type I errors (Granger and Newbold, 1974).1
1 Type I error means the null hypothesis is rejected when it should not have been.
Chapter 5: Methodology and Data
185
It is therefore important to test the nature of the time-series data. Most
macroeconomic time-series data are found to be nonstationary or integrated of order
1, denoted by I(1). That is, they can be made stationary by differencing the series
once.2 Earlier researchers who performed single-country analysis used first difference
of the time-series data to avoid spurious regression. However, this creates the problem
of losing long-run information on the variables.
To deal with this, researchers are increasingly using cointegration and the error
correction mechanism (ECM) to estimate time-series relationships. In general a linear
combination of I(1) series is integrated of order 1. However, there exists a special case
where the linear combination of I(1) can be I(0) or stationary. In that case, the series
are said to be cointegrated.
It must also be remembered that the effect of aid on economic growth in any one year
is likely to be lagged and longer term. So, it is important to search for long-run
relationships between aid and growth whatever the mechanism by which aid exerts its
influence on economic performance. Cointegration allows us to test for the presence
of a non-spurious long-run equilibrium relationship between the variables under study
in a multivariate setting with and without a time trend. Both cointegration and the
error correction mechanism investigate long-run linkages and short-run dynamics
among the variables.
2 If a time-series has to be differenced d times, it is integrated of order d or I(d). If d = 0, the resulting I(0) process represents a stationary time-series.
Chapter 5: Methodology and Data
186 Our empirical estimation is composed of three steps. As a prerequisite, we first test
the stationarity/nonstationarity of the time-series data, that is, we test for the presence
of a unit root or I(1) for each variable. Second, we test for the number of cointegrating
vectors in the model. Third, we estimate and test for the long-run dynamic
relationship using the vector error correction model (VECM). In addition, we also
perform bivariate and multivariate Granger causality tests, if the variables are not
cointegrated. Finally, we analyse the impulse response function to simulate the
response of relevant variable to changes in aid, and vice versa if necessary. In this
chapter, we explain each of these in greater detail.
5.2 Unit root tests
Before testing for cointegration, a unit root test is required to ensure that the variables
under study are nonstationary I(1). The cointegration test is only applicable if the
variables are of the same order I(1). Thus, we employ two types of unit root tests, the
Augmented Dickey–Fuller (ADF) (Dickey and Fuller, 1979, 1981) and the Phillips–
Perron (PP) tests (Phillips and Perron, 1988), with a constant as well as a
deterministic trend. Using a constant and a trend in unit root tests has been standard
process because of the nature of time-series data.
For the ADF test, we estimate the following equation (5.1),
)1.5........(........................................11
1121 tit
n
iitt YYtY εαββ +Δ+∂++=Δ −=− ∑
Chapter 5: Methodology and Data
187 where Yt is the relevant time-series, t is the time or trend variable, Δ is a first-
difference operator, and ε1t is an error term. This equation can also be estimated
without including a time trend. However, the ADF test does not adequately
distinguish between nonstationary series and stationary series that have a high degree
of autoregression. In the case of a structural break in the series, the ADF test may also
incorrectly indicate that the series contains a unit root (Culver and Papell, 1997).
We therefore perform the PP test, which provides more robust estimates when the
series have serial correlation and time-dependent heteroscedsticity and there is a
structural break. For the PP test we estimate the following equation,
)2.5........(........................................)2/( 21
1221 tit
m
iitt YYTtY εαββ +Δ+∂+−+=Δ −=− ∑
In both equations (5.1) and (5.2), Δ is the first-difference operator and ε1t and ε2t are
covariance stationary random error terms. T is the number of observations. The lag
length n in equation (5.1) is determined by the Akaike’s Information Criteria (Akaike,
1973) to ensure serially uncorrelated residuals, and the lag length m in equation (5.2)
is determined as per Newey-West’s (Newley and West, 1987) suggestions.
The null hypothesis of nonstationarity is tested using the t-statistic with critical values
calculated by MacKinnon (1991). We test the null hypothesis that ∂1 and ∂2 are zero
against the hypothesis that ∂1 and ∂2 are less than zero. The null hypothesis that the
variables are nonstationary time-series is rejected if ∂1 and ∂2 are less than zero and
statistically significant. These tests are carried out for all variables by replacing Yt’s
Chapter 5: Methodology and Data
188 with the variables under study in both equations (5.1) (the ADF tests) and (5.2) (the
PP test).
5.3 Test for cointegration
To understand a cointegrating relationship between variables, let us consider two
time-series, Yt and Xt, which are both nonstationary or I(1). Let us suppose that Yt
and Xt share the same stochastic trend; thus they may be tied together in the long run.
If Y t and Xt are I(1), and if the associated error term (a particular linear combination
of the variables) follows I(0), then the variables are said to be cointegrated. In other
words, two variables will be cointegrated if they have a long-run or equilibrium
relationship between them. We discuss here two approaches to the cointegration test:
the Engle–Granger (1987) approach and Johansen’s Maximum Likelihood Test
approach (Johansen, 1988 and Johansen and Juselius, 1990).
5.3.1 The Engle–Granger (1987) approach
This approach is generally used in the bivariate situation. One can test for
cointegration among the variables using the ADF or PP unit root tests on the residuals
(εt) estimated from the cointegrating regression between Yt and Xt (equation 5.3). Let
us assume that we have the following equation:
)3.5(....................21 ttt XY εϕϕ ++=
Chapter 5: Methodology and Data
189 To examine whether εt is I(0) or I(1), we should obtain the values of the error term
from the OLS estimates of equation (5.3) and perform unit root tests using the ADF
and PP procedures by replacing Yt with εt in equations (5.1) and (5.2) as mentioned
earlier. According to the Engle and Granger approach, if the error term is a stationary
process or I(0), then cointegration exists. In other words, although individually two
variables are nonstationary, if residuals are found to be stationary the regression is a
cointegration regression. The approach is called static because it ignores any dynamic
adjustments that may be present in a complete model.
5.3.2 Johansen’s approach
The Engel and Granger two-step approach cannot identify the number of
cointegrating vectors. Also, if the number of variables is more than two, the Engel and
Granger approach cannot estimate the parameters efficiently. Therefore, we use
Johansen’s method, first proposed by Johansen (1988), and Johansen and Juselius
(1990). The Johansen approach is capable of determining the number of cointegrating
vectors for any given number of nonstationary series of the same order.
Before applying the Johansen’s approach, one should first determine the lag length or
order of the vector autoregression (VAR). It is a key element in the specification of
the VAR, which forms the basis of inference for the cointegrating rank. Generally, the
lag length is chosen on the basis that the equation should pass all the diagnostic tests.
The most commonly used criteria are the Akaike Information Criterion (AIC) and
Schwarz Bayesian Criterion (SBC). These are given as
Chapter 5: Methodology and Data
190
)4.5(..................................................)/2(),(ln mTprAIC +Ω= &
)5.5......(........................................)/(ln),(ln mTTprSBC +Ω= &
where Tpr tt /),( /εε &&& =Ω , m is the number of freely estimated parameters in a VAR
model of lag = p and cointegrating rank = r, and tε& is a residual vector in the
restricted rank VAR, ln is the natural log and T is the number of observations. When
using AIC or SBC based on the estimated standard errors in equation (5.4) or (5.5)
respectively, the model with the lowest value for the AIC or SBC is chosen (see
Pesaran and Pesaran, 2003). The dominant practice is to choose lag length (p) using
one and or both of the information criteria plus the requirements that there should be
no evidence of serial correlation. One then uses the Johansen procedure to determine
the cointegrating rank.
Johansen (1988) and Johansen and Juselius (1990) formulate the process for
determining the cointegrating rank as follows. Consider an unrestricted VAR model
up to k lags in which the process Xt for given values of X-k+1,……X0, can be defined
as
)6.5......(....................).............2,1(,...........11 TtXXX tktktt =+Π++Π+= −− εα
where Xt is a vector of I(1) variable, α is a vector of constant, and εt is error term.
Chapter 5: Methodology and Data
191 Since Xt is I(1), the equation (5.6) can be expressed in first-differenced error
correction form as follows:3
)7.5.(......................................... 1111 tktktktt XXXX εα +Π+ΔΓ++ΔΓ+=Δ −+−−−
where Γi = -(I-Π-……..-Πi), i = 1,……..,k-1 and Π = -(I-Π1 -………..-Πk)
The coefficient matrix Π provides information about long-run relationships between
the variables in the data vector. There are three possible implications. If the rank of Π
= p, it implies that the matrix Π has full rank and the vector process Xt is stationary. If
the rank of Π = 0, the matrix Π is a null matrix and equation (5.7) would be a
traditional differenced vector time-series model. If 0< r < p, it indicates that there
exist r cointegrating vectors; in such a case Π = αβ′, where α and β are p × r matrices.
The cointegrating vectors β have the property that β′Xt is stationary even though Xt
itself is nonstationary.
The Johansen procedure gives two likelihood ratio tests for the number of
cointegrating vectors: (1) the “maximum eigenvalue test” (λmax), which tests the null
hypothesis that there are at least r cointergrating vectors, as against the alternative that
there are r+1; (2) the “trace-test” (λtrace), where the alternative hypothesis that the
number of cointegrating vectors is equal to or less than r+1. The likelihood ratio test
statistics are as follows:
3 Error correction mechanism will be discussed later.
Chapter 5: Methodology and Data
192
)8.5..(..................................................).........1ln( 1max +−−= rT λλ &
)9.5.......(........................................).........1ln(1
i
n
ritrace T λλ &−−= ∑+=
where are n-r smallest estimated eigenvalues in equation (5.9), T is the
sample size, and
nr λλ ˆ,....ˆ1+
iλ& are the ordered (estimated) eigenvalues λ1> λ2> ……>λn.
5.3.3 Error correction mechanism
If the series are found to be nonstationary I(1) and cointegrated, Engle and Granger
(1987) and Granger (1988) suggest including an equivalent error correction model
(ECM) to re-parameterise the model. The ECM combines both short-run properties of
economic relationships in first-difference form and long-run information provided by
the data in level form. Furthermore, the ECM is considered a dynamic process
because it involves lags of dependent and independent variables and it thus captures
short-run adjustments to changes, in particular adjustments to past disequilibrium and
contemporaneous changes in the explanatory variables. The ECM also enables
researchers to estimate the speed of adjustment back to the long-run condition among
the variables. In this regard, Engle and Granger (1987) warn that failure to include the
lagged residual of the cointegrating equation in a (short-run) model in difference form
results in a misspecified relationship because the long-run properties of the model are
ignored.
Chapter 5: Methodology and Data
193
tZ
Thus it can be concluded that if variables are found to be cointegrated, there must
exist an associated error correction mechanism (ECM) (Engle and Granger, 1987).
This can be shown in the following form:
)10.5...(..........3)1(11
231
221
12120 ttkt
p
kk
p
jjtj
p
itit ZXYY εμρφφφφ ++Δ+Δ+Δ+=Δ −−== −= − ∑∑∑
where Yt, Xt and Zt are relevant time-series, Δ denotes the first-difference operator,
μ(t-1) is the error correction term (ECT), where 0 1 2t t tY Xμ α α α= − − − , p is the lag
length (determined by AIC) and ε3 t is the random disturbance term. Here i, j and k
begin at one in order for the series to be related within a structural ECM (Engle and
Yoo, 1987). The ECT, μ(t-1), is the residual series of the cointegrating vector. For the
series to converge to the long-run equilibrium relation, –1≤ρ1≤0 should hold.
However, cointegration implies that ρ1 should not be zero.
5.4 Granger causality test
If the series are found to be I(1), but not cointegrated, we perform the Granger
causality tests.4 To test Granger causality, we estimate a pth order vector
autoregressive model (VAR (p)), and we specify the following bivariate model:
)11.5......(........................................511
0 tjt
p
jjit
p
iit XYY ελβφ +Δ+Δ+=Δ −=−= ∑∑
4 Granger causality testing for equations (5.11) and (5.12) is only valid if X and Y are not cointegrated (MacDonald and Kearney, 1987). However, as discussed earlier, if the series are cointegrated, a different approach to the causality test should be used.
Chapter 5: Methodology and Data
194
)12.5...(..................................................611
0 tjt
p
jjit
p
iit YXX εδαθ +Δ+Δ+=Δ −=−= ∑∑
where it is assumed that the disturbances ε5t and ε6t are uncorrelated. Equation (5.11)
postulates that the current Y is related to past values of itself as well as that of X, and
equation (5.12) postulates a similar behaviour for X. Unidirectional causality from X
to Y (X⇒Y) is indicated if the estimated coefficients on the lagged X in equation
(5.11) are statistically different from zero as a group (∑ λi ≠ 0), and the set of
estimated coefficients on the lagged Y in equation (5.12) is not statistically different
from zero (∑ δj = 0). Conversely, unidirectional causality from Y to X (Y⇒X) exists
if the set of lagged X coefficients in equation (5.11) is not statistically different from
zero (∑λi = 0), and the set of the lagged Y coefficients in equation (5.12) is
statistically different from zero (∑δj ≠ 0).
Feedback (or bidirectional) causality) (X⇔Y) is indicated when the sets of X and Y
coefficients are different from zero and statistically significant in both equations
(regressions). Independence (X ⊥Y) is suggested when the sets of X and Y
coefficients are not statistically significant in both regressions (equations).
5.5 Impulse response function
The impulse response function shows the response of dependent variables in the VAR
system to shocks in the error terms. Shocks or changes will alter the dependent
variable in the current as well as future periods. Since the dependent variable appears
in the regression with independent variables, the changes in the error term will also
Chapter 5: Methodology and Data
195 have an impact on independent variables. In other words, an impulse response
analysis demonstrates how long and to what extent variables react to unanticipated
changes among one of them. The transmission of shocks among the variables is
investigated using the generalised impulse response analysis developed by Koop et al.
(1996) and Pesaran and Shin (1996).
Although two approaches are used to investigate impulse responses, the generalised
impulse response function is considered more efficient than the orthogonalised
impulse response one (see further Pesaran and Shin, 1996). Generalised impulse
responses are invariant to the reordering of the variables in the VAR. They also fully
take account of the historical patterns of correlations observed among different
shocks. Thus here we use the generalised impulse response function.
Impulse responses differ with model types. In the case of nonlinear models, the
impulse response is different across regimes; and it depends on the size of the shock
and the time that it occurs. History and shock independence are lost in nonlinear
models; thus measuring the effect of a shock of a given size hitting at a given time
period using impulse response may be very misleading (Koop et al., 1996). However,
in the case of linear models, the impulse response does not depend on the size of the
shock or the time at which it takes place. In other words, the impulse response
functions for linear models are both shock and history independent.
Furthermore, the impulse response function in a linear model typically measures the
effect of a shock of size 1. Shocks of different sizes produce only a scale effect; for
example, a shock of size 2 would produce an impulse response twice that of size 1.
Chapter 5: Methodology and Data
196 More importantly, the effect of the shock is also independent of the time that it occurs
because the impulse response would be the same regardless of whether the economy
was in expansion or contraction (Koop, 1996).
Koop et al. (1996) developed a generalised impulse response function that addresses
the problems of history and size of shock and is thus applicable to both linear and
non-linear models. The generalised impulse response function uses the expected
values of the series conditional on only the history and/or shock. In precise terms, the
response is a representation of the average of possible reactions with the given choice
of history and current shock.
Let us assume that yt in a simple AR (1) process:
)13.5....(..................................................110 ttt yy εαα ++= −
where εt is a random shock and α0 and α1 are parameters.
A simple form of the generalised impulse response function can then be given as
)14.5.........(..........,,0......,,.........0,0/[
],,0...,,.........0,/[
00111
00111
θθωωεεεθθωωεεδε
=====−
======
−−+++
−−+++
ttntttnt
ttntttnt
yE
yEGI
where GI stands for the generalised impulse response function, θ is the set of
parameters and εt ……. εt+n are shocks. Equation (5.14) measures the effect of a shock
of a given size (δ) hitting at a given time period (ω0t-1), given that no other shocks hit
the system. The first term in equation (5.14) provides the expected realisation given
Chapter 5: Methodology and Data
197
the once-and-for-all shock, and the second term is the expected realisation without the
shock.
Therefore, the generalised impulse response function can be defined as the difference
between the expected yt+n after the shock and the expected yt+n assuming no shocks. In
other words, it compares the value of yt+n after the shock has occurred (first
realisation) with its benchmark value (second realisation) where the economy has not
been subject to any shocks.
5.6 Data sources and their description
Data provided by the national sources differ significantly from those found in
international sources such as the IMF and UNDP.5 This is particularly problematic in
the case of aid data. It is generally believed that OECD aid data are more reliable as
these are collected directly from the donors who have better recording system than
Nepal. Similarly, IMF data on macroeconomic indicators and socio-economic data of
the World Bank are considered more reliable. Although these data are mostly
collected from national sources, the IMF and the World Bank do internal consistency
checks and supplement the data from the national sources with their occasional
sectoral surveys/studies.
The IMF (2004) also identified data problems in Nepal. They noted, “The statistics
are deficient due to lack of comprehensive and regular data sources. The limited
source data suffer from inconsistencies, lags in availability, and insufficient detail.
5 See Mihaly (2002)
Chapter 5: Methodology and Data
198 There are shortcomings in record keeping by agencies and access to records is not
timely due to processing lags. Reflecting source data problems, compilation methods
rely heavily on fixed ratios derived from past year surveys or ad hoc assumptions”
(2004: 51).
Therefore, this research uses data mostly from the international sources whenever
they are available. Table 5.1 lists the sources of variables data used in this study.
Table 5.1: Sources of data
IMF OECD World Bank CBS Nominal GDP
GDP deflator
Gross domestic savings
Gross fixed capital formation (investment) Total revenue (tax and non-tax revenue) Budget deficit Domestic borrowing
Total foreign aid
Bilateral aid
Multilateral aid
Grants aid
Loans aid
Adult literacy rate
Labour force
Total population
Development expenditure Non-development (regular) expenditure Public investment
Notes: (a) IMF: International Financial Statistics (IFS) online database
(b) OECD: International Development Statistics (IDS) online database (c) World Bank: World Development Indicators (WDI) online database (d) CBS: Statistical Year Book of Nepal
Definitions of variables used in estimation
RGDP = real GDP (converted from nominal to real using GDP deflator, (1995 = 100))
RGDPP = per capita real GDP (=RGDP/total population)
AR = total foreign aid as a percentage of GDP (net official development assistance
excluding military aid)
Chapter 5: Methodology and Data
199 BAR = bilateral aid as a percentage of GDP
MAR = multilateral aid as a percentage of GDP
GR = grants aid as a percentage of GDP
LAR = loans aid as a percentage of GDP
SR = gross domestic savings as a percentage of GDP
IR = gross fixed capital formation as a percentage of GDP
KP = capital stock
TR = exports + imports as a percentage of GDP
INF = inflation percentage change in CPI
BORR = domestic borrowing as a percentage of GDP
BDR = budget deficit as a percentage of GDP
MONR = broad money (M2) as a percentage of GDP
ADLR = adult literacy rate
AID = per capita aid (= total aid/total population)
REV = per capita revenue (= total tax and non-tax revenue/total population)
Gd = per capita development expenditure (= development expend/total population)
Gnd = per capita non-development expenditure (= non-dev. expend./total population)
5.6.1 Statistical summary of data and data limitations
Table 5.2 shows descriptive statistics of variables. During 1970-2002, the mean
growth rate of real GDP was 4 per cent. During the same period, aid as a percentage
of GDP grew at an average rate of 4.9 per cent. This indicates the possibility of high
correlation between Nepal’s economic growth and aid flows.
Chapter 5: Methodology and Data
200 Table 5.2: Statistical summary of variables, 1970-2002 Variables Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Normality Probability
RGDP 161137.80 142366.00 306622.70 86236.67 66986.56 0.69 2.22 3.43 0.18 RGDP growth 4.00 4.40 9.68 -2.97 2.97 -0.52 3.21 1.43 0.49
RGDPP 8856.36 8337.57 12459.78 6883.54 1733.39 0.63 2.04 3.45 0.18 RGDPP growth 1.72 2.06 7.30 -5.05 2.86 -0.49 3.25 1.30 0.52
AR 8.06 8.31 15.27 2.66 3.48 0.02 2.22 0.84 0.66 AR growth 4.91 4.21 60.51 -28.43 19.99 0.98 4.34 7.25 0.03
BAR 4.79 4.76 8.96 1.69 1.93 0.11 2.19 0.97 0.62
MAR 3.26 3.54 7.62 0.37 1.72 0.09 2.71 0.16 0.92
GR 5.40 5.63 8.29 1.89 2.07 -0.37 1.92 2.35 0.31
LAR 2.65 2.59 6.98 0.46 1.64 0.69 3.09 2.60 0.27
TR 35.50 31.80 64.04 13.21 14.62 0.36 2.10 1.85 0.40
IR 16.67 17.59 22.53 5.71 4.72 -0.99 3.05 3.28 0.17
SR 10.79 11.23 15.02 2.57 3.47 -0.88 2.89 4.15 0.13
LF 8.11 7.82 10.81 6.11 1.48 0.44 1.94 2.59 0.27
POP 17.49 16.97 24.61 12.11 3.79 0.31 1.88 2.25 0.32
ADLR 28.27 27.00 44.00 16.00 8.46 0.31 1.90 2.19 0.33
INF 8.84 8.35 19.81 2.00 4.72 0.56 2.82 1.74 0.42
MONR 29.61 28.42 53.54 10.62 12.19 0.34 2.31 1.31 0.52
BDR 4.36 3.89 8.98 0.27 2.35 0.27 2.24 1.21 0.55
Notes: (a) RGDP is in Rs. (million), RGDPP is in Rs. (thousand). (b) LF (labour force) and POP (total population) are in millions.
(c) The last two columns give the Jarque–Bera normality test with its probability. The other test statistics measure the difference of the skewness and kurtosis of the series with those from the normal distribution. Skewness is a measure of asymmetry of the distribution of the series around the mean. Kurtosis measures the peakedness or flatness of the distribution of the series.
During the sample period Nepal’s real mean GDP was Rs. 161,137.80 million and real
GDP per capita was Rs. 8,856.36 thousand. The mean investment rate and the mean
saving ratio were 16.7 per cent and 10.7 per cent respectively, showing an average
savings–investment gap of 6 per cent of GDP. During the same period the mean aid
flows was 8.06 per cent of GDP. This shows the importance of aid in filling the savings–
investment gap. The mean aid/GDP ratio is more than the mean savings–investment gap
Chapter 5: Methodology and Data
201 (as a percentage of GDP). This is expected as Nepal receives a significant amount of
humanitarian aid.
The mean trade/GDP ratio (35.5), inflation rate (8.8), budget deficit/GDP (4.4) and
M2/GDP (29.6) indicate that Nepal’s economy was reasonably open and
macroeconomically stable, and its financial sector moderately developed. That is, Nepal
had a reasonably good policy environment during the period of study.
The Jarque–Bera test for normality shows that except for one variable (AR growth =
growth rate of aid/GDP ratio), all variables are normally distributed (Table 5.2). A very
high standard deviation also indicates that the growth rate of the aid/GDP ratio suffers
from wild fluctuations. This has been confirmed by Figure 5.1, which shows the growth
rates of real GDP and aid/GDP ratio. During 1970-81, growth rate of real GDP
fluctuated between negative and positive values. For example, the real GDP growth went
from -0.5 per cent in 1973 to over 6 per cent in 1974. Likewise it fluctuated from -2 in
1980 to over 8 per cent in 1981. The coefficient of variation (CV) during 1970-1982 is
higher than in the period 1983-2002.
Therefore, in chapter 6 where the relationship between GDP and aid is examined, we
shall be using data for the period 1983-2002. Incidentally, this is also the period when
Nepal initiated the Structural Adjustment Program under the guidance of the IMF and
the World Bank, which resulted in an improved macroeconomic environment.
Chapter 5: Methodology and Data
202 Figure 5.1: Growth rates of real GDP and foreign aid/GDP ratio, 1970-2002 CV = 1.37 (1970-1982) CV = 0.55 (1983-2002)
-4-202468
1012
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
Real GDP growth
CV = 1.85 (1970-1982) CV = 1.47 (1983-2002)
-40-20
020406080
100120
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
Aid/GDP growth
Note: CV (coefficient of variation) = standard deviation/mean Source: IMF/IFS and OECD/IDS online databases Since the early 1980s, Nepal has maintained relatively higher economic growth due
mainly to economic liberalisation. During 1983-2002, the mean growth rates of real GDP
and per capita real GDP were 4.81 and 2.43 per cent respectively. During the same
period, the mean ratios of aid/GDP, trade/GDP and M2/GDP were 10, 44 and 37 per cent
respectively (Table 5.2A). The statistical summary of data for the period of 1983-2002
show that GDP and aid growth data are less volatile in the 1980s than the whole sample
period mainly because of high volatility in the 1970s.
Chapter 5: Methodology and Data
203 Table 5.2A: Statistical summary of variables 1983-2002 Variables Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Normality Probability
RGDP 200690.85 192119.83 306622.68 116949.97 57407.22 0.32 -1.05 1.49 0.48 RGDP growth 4.81 4.69 9.68 -2.97 2.68 -1.01 3.44 0.39 0.82
RGDPP 9876.32 9727.68 8927.97 6883.54 1495.71 0.10 -1.10 1.99 0.37 RGDPP growth 2.43 2.34 7.30 -5.05 2.56 -0.93 3.22 0.36 0.83
AR 10.07 9.70 15.27 6.65 2.44 0.45 -0.62 0.94 0.63 AR
growth -0.45 -0.31 23.76 -20.78 13.02 0.23 -0.60 1.78 0.41
BAR 5.95 5.87 8.96 4.07 1.36 0.45 -0.59 1.27 0.53
MAR 4.13 4.08 7.62 1.19 1.37 0.27 1.61 0.59 0.75
GR 6.65 6.71 8.29 4.71 1.17 -0.07 -1.44 1.49 0.47
LAR 3.42 3.17 6.98 0.53 1.56 0.52 0.30 2.15 0.34
TR 43.85 43.26 64.04 30.10 11.96 0.23 -1.70 2.87 0.24
IR 19.56 19.40 22.53 16.44 4.20 -0.85 -0.90 2.54 0.28
SR 12.23 13.30 15.02 7.87 3.04 -0.88 -1.12 2.58 0.27
LF 9.04 8.91 8.27 6.20 0.64 0.22 1.33 1.20 0.55
POP 19.93 19.75 18.19 12.35 1.82 0.17 1.18 1.18 0.56
ADLR 33.75 33.50 44.00 25.00 4.14 0.24 -1.23 1.29 0.52
INF 8.77 8.30 19.00 2.48 4.69 0.60 0.06 0.26 0.88
MONR 37.27 34.91 53.54 27.52 8.80 0.73 -0.81 1.62 0.45
BDR 5.72 5.80 8.98 3.28 1.83 0.34 -1.18 1.63 0.44 Note: See Table 5.2
The data series on savings and investment do not have the same problem as GDP data. Thus, in
chapter 7 we shall use the longer data series (1970-2002), where the relationship between aid and
savings/investment is examined. The fiscal data are available only from 1975. Therefore, for the
investigation of aid and fiscal behaviour (chapter 8), we shall use data from 1975.
5.7 Computer programs and software
We have used Microfit version 4.0 developed by Pesaran and Pesaran (2003) for cointegration and
the error correction mechanism. We have also used Eviews 4.1, developed by Quantitative Micro
Software (2000), for the unit root tests and summary statistical analyses.
Chapter 6
Foreign Aid and Growth in Nepal
“… ‘foreign assistance’ has become virtually a separate factor of production whose productivity and allocation provide one of the central problems for a modern theory of development” (Chenery and Strout, 1966: 679).
6.1 Introduction
This chapter examines the relationship between foreign aid and per capita real GDP.
The theoretical foundation of our analysis is the neoclassical production function,
where foreign aid is assumed to influence technology and capital formation. Using
this neoclassical framework, an empirical model is developed specifying the
relationship between foreign aid and per capita real GDP. This chapter investigates
aid’s influence through technology, while following chapter analyses its influence
through capital formation.
We begin our estimation first with aggregate aid and then disaggregated forms of aid.
The effectiveness of foreign aid is believed to be greater when there is
macroeconomic stability and few distortions. It has been argued that distortionary
policies such as trade restrictions and financial repression reduce the efficiency of
investment. Thus, following recent studies (for example, Burnside and Dollar, 2000;
World Bank, 1998 and Hansen and Tarp, 2000), we incorporate policy variables in
our model to investigate whether policy variables impact on the effectiveness of
foreign aid.
Chapter 6: Foreign Aid and Growth in Nepal
205 Table 6.1 provides a comparative perspective of Nepal in terms of its policy
environment. Among South Asian countries, Nepal experienced the second highest
average growth rate, about 5 per cent during 1990-2002. During the 1990s, there have
been significant improvements in openness, financial deepening and inflation. For
example, average trade/GDP increased from about 32 per cent in the 1980s to over 50
per cent in the 1990s, and during the same period average M2/GDP increased from
28.08 per cent to about 42 per cent.
Table 6.1: Average growth rates of real GDP and policy variables for South Asian countries, 1980-90, 1991-2002 and 1970-2002
Country Average real GDP growth
Average trade/GDP (%)
Average M2/GDP (%)
Average inflation rate
Average budget deficit/GDP (%)
Nepal
1980-1990 4.11 31.57 28.08 10.60 -8.86
1991-2002 5.01 50.34 41.70 8.02 -7.05
1970-2002 4.00 32.97 30.20 8.80 -6.67
Bangladesh*
1980-1990 3.57 20.95 26.03 7.36*** -
1991-2002 4.94 28.59 31.15 4.31 -
1974-2002 4.81 22.99 26.58 5.49** -
India
1980-1990 3.90 14.86 41.66 9.10 -7.34
1991-2002 5.40 22.85 50.50 7.95 -5.54
1970-2002 4.48 17.01 41.45 8.26 -5.60
Pakistan
1980-1990 6.41 33.79 41.27 7.42 -6.64
1991-2002 3.80 36.64 46.18 7.91 -6.91
1970-2002 4.84 32.69 43.55 8.96 -7.10
Sri Lanka
1980-1990 4.87 68.02 30.62 13.61 -10.88
1991-2002 4.74 77.84 35.76 10.62 -7.69
1970-2002 4.58 69.76 30.78 10.30 -8.71 Notes: (a) Nepal’s budget deficit including grants during the periods 1980-90, 1990-2002 and 1970-2002 were -
6.21, -4.97 and -4.36 respectively. (b) *, ** and *** indicate data from 1974-2002, 1987-2002 and 1987-90 respectively, and budget deficit data are not available for Bangladesh.
Source: IMF/IFS online database.
Chapter 6: Foreign Aid and Growth in Nepal
206 In addition, average inflation and budget deficit/GDP decreased to 8 and 7 per cent
respectively in the 1990s. Thus, macroeconomic stability, opening up the economy
and financial deepening may have contributed positively to economic growth in
Nepal. One can therefore expect aid to be more effective during this period because of
a better policy environment.
We perform unit root tests and employ cointegration and the error correction
mechanism to estimate the aid–growth relationship in Nepal using data for the period
1970-2002. However, as explained in chapter 5, due to large fluctuations of GDP and
aid data in the 1970s, sometimes moving from a high positive to a high negative
figure, we have limited our final estimation to a 20-year period (1983-2002). This also
happened to be the period when Nepal initiated policy reforms under the Structural
Adjustment Programs of the IMF and the World Bank and attained macroeconomic
stability.
The organisation of this chapter is as follows. The next section discusses the model,
data and methodology. Section 6.3 describes the results of the unit root test, followed
by an analysis of the results of the cointegration and error correction models. Section
6.4 has concluding remarks.
Chapter 6: Foreign Aid and Growth in Nepal
207 6.2 Model and data
6.2.1 Model specification (aid and growth)
Our estimation proceeds with the formulation of a neoclassical production function
type model, as follows:
)1.6.....(..............................).........( 21 ββαtttt LKFAY =
where Yt is real GDP, Kt is the stock of capital, Lt is the labour force, and At
represents the level of technology with which inputs are used in the production
process. The parameters α, β1 and β2 measure the elasticities of Yt with respect to At,
Kt and Lt respectively. Subscript “t” represents time.
Assuming that the production function displays a constant returns to scale (i.e. β1+ β2
= 1), we can express equation (6.1) in per capita form, and taking natural logarithm,
we derive the following equation:
)2.6.(........................................lnlnln 1 ttt KPARGDPP βα +=
where RGDPPt = per capita real GDP, At = level of technology, and KPt= capital
(K/Population).1 ln is the natural logarithm operator.
1 Strictly speaking, it should be total employment. But due to unavailability of data, we are using total population. This should not affect the overall result where there is a strict positive relationship between total employment and population.
Chapter 6: Foreign Aid and Growth in Nepal
208 Thus, equation (6.2) shows that a country’s per capita real GDP depends on the ratio
of factor inputs and the level of technology.
The level of technology can be affected by foreign aid, because aid contributes to the
acquisition of technical knowledge in developing countries (see Islam, 2003 and
Marvotas, 2002). This happens through two channels: (1) importation of capital
equipment and (2) technical assistance. Aid finances capital imports such as
machinery and equipment from developed countries. The import of new equipment
not only introduces new technology but also upgrades local technological knowledge.
In the context of Nepal, in the mid 1990s over 40 per cent of total aid came in the
form of technical assistance (HMG/N, 2002). Thus, it is reasonable to assume that
foreign aid affects GDP growth through technological progress as technical assistance
contributes to improving institutions and policies.
Foreign aid effectiveness depends on the absorptive capacity of recipient countries,
for which human capital may be considered an important component (see Chauvet
and Guillaumont, 2003). In other words, how effectively imported technology is used
depends on the skill level of the labour force. Labour may be abundant in developing
countries but most people are unskilled. Moreover, theories of technological diffusion
stress the importance of the recipient country having a sufficiently high level of social
capability for successful implementation of technologies imported from more
advanced countries (see, for example, Abramovitz, 1986 and Howitt, 2000). To
capture this, we have included the adult literacy rate as an additional determinant of
technology. We can therefore express the level of technology as follows:
Chapter 6: Foreign Aid and Growth in Nepal
209
)2.6.......(........................................lnlnln 210 aARADLRA ttt ααα ++=
Strictly speaking the level of technology is determined also by accumulated past aid
flows. To some extent the effect of past aid flows is captured in our estimation when
we use VAR with lag values of variables. Substituting equation (6.2a) into equation
(6.2), we get
)3.6..(..........lnlnlnln 1210 tttt KPARADLRRGDPP βαααααα +++=
For the purpose of estimation, we rewrite equation (6.3) as
)4.6.....(..........lnlnlnln 14321 ttttt uARADLRKPRGDPP ++++= θθθθ
where αα0 = θ1, αα1 = θ3, αα2 = θ4, θ2 = β1, and u1t = error term.
Although aid affects GDP through the level of technology and capital formation, we
are only investigating the technology effect in this chapter. The following chapter will
examine the capital formation effect of aid.
Coefficients of ARt and ADLRt measure the effect of aid on real per capita GDP
through their effects on the level of technology; thus equation (6.4) is our main model.
Next we disaggregate total aid down into bilateral and multilateral aid. Bilateral and
multilateral aid may differ along many dimensions such as donors’ motives and aid
Chapter 6: Foreign Aid and Growth in Nepal
210 conditionality (Ram, 2003).2 The contents of the aid package and the conditions
associated with aid seem quite different for both bilateral and multilateral aid.
Multilateral aid has for quite some time been disbursed on a conditional basis for
Structural Adjustment Programs and the fulfillment of certain requirements. On the
other hand, bilateral aid has distinctive features, and largely depends on donors’
strategic interests. Thus, these two types of aid may have different impacts on the
economy, which can be estimated by using the following equation:
)5.6....(..........lnlnlnlnln 243210 tttttt uMARBARADLRKPRGDPP +∂+∂+∂+∂+∂=
where BARt = bilateral aid as percentage of GDP and MARt = multilateral aid as
percentage of GDP.
We also disaggregate total aid into grants and loans aid, assuming that both kinds of
aid may have different impacts on the economy (Gupta et al., 2003). It is generally
argued that grants are free resources, and thus are likely to be misused. On the other
hand, loans are considered to be more effective due to the future repayment
obligations (Islam, 1992). However, loans may have a negative impact on growth by
due to debt burden. We investigate these different impacts incorporating grants and
loans aid in the following equation:
)6.6....(..........lnlnlnlnln 354321 tttttt uLARGRADLRKPRGDPP +++++= δδδδδ
2 See also earlier works such as Griffin and Enos (1970) discussing aid and political motives. Burnside and Dollar (2000) also found that bilateral aid is influenced by donor interest, while multilateral aid is given according to income level, population and policy.
Chapter 6: Foreign Aid and Growth in Nepal
211 where GRt, and LARt are grants and loans aid as percentage of GDP respectively.
6.2.2 Model specification (aid and policy)
In the recent literature, macroeconomic stability and good policy environment are
regarded as a crucial condition for effective aid implementation and thus for rapid
economic growth. The World Bank, for example, has emphasised the need for a
supportive macroeconomic framework for successful structural adjustments.
According to the World Bank, this involves low and predictable inflation, appropriate
real interest rates, real exchange rates that are competitive and stable, sustainable
fiscal policy, and a viable balance of payments position (World Bank, 1990). The
effectiveness of capital flows will be greater when there is macroeconomic stability
and few distortions. Generally, it is argued that distortionary policies such as trade
restrictions and financial repression3 reduce the efficiency of investment. The role
played by macroeconomic factors and distortionary policies has been emphasised by
Kormendi and Meguire, 1985; Fischer, 1991 and 1993 and Easterly, 1993.
The role of international trade is considered to be crucial for technological progress in
developing countries. In the long run, exports spur economic growth through
technological progress (Krueger, 1978). Sengupta and Espana (1994) argue that trade,
particularly exports, bring economy-wide structural changes in the form of technical
innovations and diffusion of skill-intensive externality of human capital, and thus
contribute to a higher level of aggregate productivity. Trade also promotes growth
through increased specialisation, efficient resource allocation, and diffusion of 3 Financial repression arises due to the policy of fixing interest rate ceiling at a level not consistent with high inflation rates of a country. This results in a negative or very low real interest rate. The negative real interest rate discourages savings, and hence is detrimental for the growth of the financial sector. The negative real interest rate also encourages inefficiency in the use of loans, which in turn lowers the returns to investment.
Chapter 6: Foreign Aid and Growth in Nepal
212 international knowledge (Sachs and Warner, 1995). At the same time, it also improves
a country’s credit ratings by generating hard currencies, and thus makes it easier to
obtain foreign loans. However, if imports rise at a faster rate than exports, a country’s
growth may hit a balance of payments constraint (Thirlwall, 2003). According to the
two-gap model, aid can help in this situation.
Choice of policy indicators
Fischer (1993) suggests the inflation rate as the best single indicator of
macroeconomic policies, along with budget surplus/deficit as a second indicator. The
inflation rate indicates government’s overall ability to manage the economy. That is,
high inflation rates imply that the government has lost control of its budget. He also
suggests including budget deficit as an additional explanatory policy indicator.
According to the World Bank (1990), reductions in fiscal deficits have typically been
at the core of successful Stabilisation Programs and are prerequisites for successful
structural adjustment and improved efficiency of investment. Thus, the reduction of
fiscal deficit may contribute to better economic performance. Following Fischer
(1993), we are taking inflation and budget deficit as indicators of macroeconomic
policy in our analysis.
Financial repression is also considered to be detrimental to growth. Many developing
countries over-regulate their financial sector through controls on interest rates and
restrictions on credit to the private sector. This hampers financial intermediation and
financial deepening. Many researchers have used the M2/GDP as an indicator of
financial deepening. We therefore use M2/GDP as an indicator of financial deepening
in our model.
Chapter 6: Foreign Aid and Growth in Nepal
213 Various measures of openness have been proposed and empirically tested. There is no
single best measure; it all depends on availability of data and the methodology to be
employed.4 Therefore, to reflect the degree of openness, we incorporate trade (exports
plus imports as a percentage of GDP) in the model.
In sum, we have used consumer price index (CPI) and budget deficit/GDP as
measures of macroeconomic policy, trade/GDP as a measure of openness, and
M2/GDP as a financial sector policy in the model.5 We begin by looking at the two-
variable relationships to get an idea of how policy variables affect growth. The
equations we estimate are as follows:
)7.6........(..................................................lnln 42321 auTRRGDPP ttt ++= δδ
)7.6......(..................................................lnln 53231 buCPIRGDPP ttt ++= δδ
)7.6.(..................................................lnln 64241 cuMONRRGDPP ttt ++= δδ
where TR = total trade/GDP, CPI = consumer price index, and MONR = M2/GDP.
Next, we estimate the following equations adding two policy variables at a time to the
main model (equation 6.4):
4 Edwards (1998), for instance, used a series of openness indices for trade policy and to proxy trade distortions. Sachs and Warner (1995) considered five conditions – non-tariff barriers, average tariff rates, a black market exchange rate, a socialist economic system, and a state monopoly on major exports – to judge whether a country has a closed economy. If a country has one of these characteristics, then it has a closed economy. All these measures are found to be inadequate in some aspects. (See Dowrick, and Golley, 2004.) 5 Budget deficit as a measure of macroeconomic stability correlated highly with inflation and did not perform well. Therefore, we did not use this budget deficit in our subsequent analyses.
Chapter 6: Foreign Aid and Growth in Nepal
214
)7.6(....................lnlnlnlnlnln 75656554535251 duCPITRADLRKPARRGDPP ttttttt ++++++= δδδδδδ
)7.6.......(..........lnlnlnlnlnln 8666564636261 euMONRTRADLRKPARRGDPP ttttttt ++++++= δδδδδδ
)7.6.....(..........lnlnlnlnlnln 9767574737271 fuCPIMONRADLRKPARRGDPP ttttttt ++++++= δδδδδδ
6.2.3 Data
We use annual time-series data from 1970 to 2002 for Nepal. Data on GDP,
investment, trade, adult literacy, population and labour force are obtained from the
IMF, International Financial Statistics (online) and the World Bank, World
Development Indicators (online). Data on aid flows are obtained from the OECD,
International Development Statistics (online). GDP deflator (1995 = 100) is used to
convert nominal GDP into real terms. Aid data are converted into national currency
using the nominal exchange rate, as IFS data are in national currency terms.
As mentioned in chapter 5, we observe wild fluctuations in the growth rates of aid
flows and GDP during the 1970s. We tried to smooth out data by taking the moving
average but it did not produce better (sensible) results. Therefore, we have used data
from 1983 to 2002 in our final analyses in this chapter.6
6 Although one should have at least 30 years of data for cointegration analysis, we had to limit our analysis to a shorter data length. Studies such as Murthy et al. (1994), Giles (1994), Granger et al. (2000), Ratanapakorn and Sharma (2002), and Sander and Kleimeir (2003) also used short data series. The shorter data series may make the estimates less robust. However, in order to back up our conclusions, we have examined aid effectiveness from alternative perspectives in the following two chapters using longer data series.
Chapter 6: Foreign Aid and Growth in Nepal
215 Estimation of capital stock data
Following Ramirez (2000), capital stock is estimated as follows:
11 −− −+= tttt KIKK δ
where Kt-1 is the stock of capital at time t-1, It is the gross investment during time t
and δ is the rate at which the capital stock depreciated in period t-1. The initial stock
of capital is estimated by summing five years of gross investment (1965-69) assuming
a rate of depreciation of 10 per cent. To ensure the robustness of the econometric
results, two alternative rates of depreciation (5 per cent and 20 per cent) were also
used, but the results were not significant.7 Furthermore, we divide estimated capital
stock by total population to convert the model into a per capita form.
Table 6.2 presents correlation coefficients between real GDP (both total and per
capita) and the variables used in the model. As can be seen, most variables correlate
well with both real GDP and per capital real GDP.
Table 6.2: Correlation coefficients of variables, 1983-2002
Variables Real GDP Per capita real GDP KP 0.93 0.93 AR 0.38 0.38
BAR 0.48 0.49 MAR 0.22 0.22 GR 0.49 0.49
LAR 0.18 0.19 TR 0.90 0.90 LF 0.99 0.99
POP 0.99 0.98 INF -0.30 -0.30
MONR 0.97 0.96 BDR 0.25 0.23
ADLR 0.99 0.98
7 See appendix 6.2 at the end of the thesis (after references).
Chapter 6: Foreign Aid and Growth in Nepal
216 6.3 The empirical results and their interpretations 6.3.1 Unit root tests Prior to testing for cointegration, we examine the stationarity of time-series variables.
Since the final estimation is based on data from 1983 to 2002, ADF tests are
performed for this sub-period. Results of both ADF and PP tests on the level and first
difference of the variables are presented in Tables 6.3 and 6.4 respectively. Since in
the majority of cases AIC selected the lag length of 2, we fixed the lag length of 2 for
both tests. Tables 6.3A and 6.4A show the results with a constant and a time trend,
while Tables 6.3B and 6.4B present the results with a constant only. The use of a
constant and a time trend is a standard practice because of the nature of time-series
data.
The results indicate that the null hypothesis of nonstationarity cannot be rejected for
any of the variables in their level form. When the ADF test is applied to these
variables in first difference under the assumption of a constant and a deterministic
time trend, all variables are found to have unit roots except for lnRGDPP, lnMAR,
lnBDR, lnCPI and lnMONR.
Chapter 6: Foreign Aid and Growth in Nepal
217 Table 6.3A: ADF test (Lag = 2) with constant and time trend, 1983-2002
Variables Levels First
difference 10% critical
value 5% critical
value 1% critical
value
lnRGDPP -0.79 -3.91** -3.26 -3.65 -4.49
lnKP -2.11 -2.88 -3.26 -3.65 -4.49
lnAR -1.41 -2.58 -3.26 -3.65 -4.49
lnTR -2.77 -2.74 -3.26 -3.65 -4.49
lnBAR -2.78 -2.72 -3.26 -3.65 -4.49
lnMAR -0.85 -4.41** -3.26 -3.65 -4.49
lnGR -2.32 -2.57 -3.26 -3.65 -4.49
lnLAR -1.78 -3.10 -3.26 -3.65 -4.49
lnADLR -2.14 -2.84 -3.26 -3.65 -4.49 lnMONR -1.06 -5.76* -3.26 -3.65 -4.49
lnCPI -0.94 -3.37*** -3.26 -3.65 -4.49
lnBDR -2.36 -4.61* -3.26 -3.65 -4.49
Note: *, ** and *** indicate significance at 1%, 5% and 10% levels respectively.
Chapter 6: Foreign Aid and Growth in Nepal
218 Table 6.3B: ADF test (Lag = 2) with constant only, 1983-2002
Variables Levels First
difference 10 % critical
value 5 % critical
value 1% critical
value
lnRGDPP 2.18 -2.46 -2.65 -3.02 -3.80
lnKP -1.74 -2.66*** -2.65 -3.02 -3.80
lnAR -1.26 -2.44 -2.65 -3.02 -3.80
lnTR -2.33 -2.69*** -2.65 -3.02 -3.80
lnBAR -0.44 -2.79*** -2.65 -3.02 -3.80
lnMAR -3.72** -1.45 -2.65 -3.02 -3.80
lnGR -0.98 -2.36 -2.65 -3.02 -3.80
lnLAR -1.71 -3.04** -2.65 -3.02 -3.80
lnADLR -1.30 -2.64 -2.65 -3.02 -3.80 lnMONR -2.53 -3.98* -2.65 -3.02 -3.80
lnCPI 1.37 -2.97 -2.65 -3.02 -3.80
lnBDR -2.15 -4.36* -2.65 -3.02 -3.80
Note: See Table 6.3A.
On the other hand, the test results under the assumption of a constant only show unit
roots in the level form for all variables except for lnMAR, while in its first difference
form only six variables, lnKP, lnBAR, lnTR, lnMONR, lnLAR and lnBDR, are found
to be stationary (Table 6.3B). Thus, the ADF test is found to be inconsistent even in
the first difference form when the 1983-2002 period is considered.
We therefore apply the PP test. As mentioned in the previous chapter on
methodology, the PP test is more appropriate than the ADF test because it considers
Chapter 6: Foreign Aid and Growth in Nepal
219 structural breaks. When the PP test is performed under the assumption of a constant
and a deterministic time trend, all the variables are found to be stationary at the one
per cent significant level in the first difference form only (Table 6.4A).
Table 6.4A: PP test (Lag = 2) with constant and time trend, 1983-2002
Variables Levels First
difference 10 % critical
value 5 % critical
value 1% critical
value
lnRGDPP -3.01 -7.44* -3.26 -3.67 -4.53
lnKP -3.41 -8.07* -3.26 -3.67 -4.53
lnAR -2.30 -6.51* -3.26 -3.67 -4.53
lnTR -2.95 -5.49* -3.26 -3.67 -4.53
lnBAR -3.31 -5.94* -3.26 -3.67 -4.53
lnMAR -2.05 -8.56* -3.26 -3.67 -4.53
lnGR -2.29 -5.10* -3.26 -3.67 -4.53
lnLAR -2.87 -8.26* -3.26 -3.67 -4.53
lnADLR -3.39 -7.97* -3.26 -3.67 -4.53 lnMONR -1.22 -4.38** -3.26 -3.67 -4.53
lnCPI -1.40 -3.79** -3.26 -3.67 -4.53
lnBDR -2.72 -4.87* -3.26 -3.67 -4.53
Note: See Table 6.3A. Table 6.4B provides the results of a PP test for the variables in both level and
differenced forms under the assumption of a trend only. We find that all the variables
in their level form are non-stationary except for lnMAR and lnMONR. In the case of
Chapter 6: Foreign Aid and Growth in Nepal
220 first difference form, however, the null hypothesis of nonstationarity is rejected for all
variables. Hence, our investigation of stationarity is based on the PP test.
Table 6.4B: PP test (Lag = 2) with constant only, 1983-2002
Variables Levels First
difference 10% critical
value 5% critical
value 1% critical
value
lnRGDPP -1.58 -7.60* -2.65 -3.02 -3.83
lnKP -2.16 -7.70* -2.65 -3.02 -3.80
lnAR -1.40 -6.38* -2.65 -3.02 -3.80
lnTR -2.86 -5.11* -2.65 -3.02 -3.80
lnBAR -0.75 -6.12* -2.65 -3.02 -3.80
lnMAR -3.78** -5.35* -2.65 -3.02 -3.80
lnGR -1.08 -5.22* -2.65 -3.02 -3.80
lnLAR -2.25 -7.47* -2.65 -3.02 -3.80
lnADLR -1.45 -7.64* -2.65 -3.02 -3.80 lnMONR -2.47 -3.73** -2.65 -3.02 -3.80
lnCPI 1.02 -3.70** -2.65 -3.02 -3.80
lnBDR -1.97 -4.94* -2.65 -3.02 -3.80
Note: See Table 6.3A.
6.3.2 Cointegration and error correction mechanism
We began our empirical investigation simply by taking two variables: per capita real
GDP and foreign aid. This provides us with a preliminary picture of how aid affects
Chapter 6: Foreign Aid and Growth in Nepal
221 per capita real GDP. Results of the Johansen’s Likelihood Ratio test for cointegration
are presented in Table 6.5.
Table 6.5: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (variables lnRGDPP and lnAR) VAR(3) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.80360 r = 0 r = 1 32.55** 43.31** 0.41610 r <= 1 r = 2 10.76 10.76 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt Trend Coefficients 1.000 -0.005 -0.025 Chi Square [0.57] [21.64]* Error correction model for lnRGDPP Variables Coefficients Variables Coefficients Intercept 14.94 ΔlnRGDPPt-1 0.368 (7.99)* (2.82)** ECT -0.085 ΔlnARt-1 -0.027 (-7.98)* (-1.39) Diagnostic tests
R-Square 0.84 FF 0.32 R-Bar-Square 0.81 NORM 0.61 DW 1.70 HET 0.37 S C 0.53 Notes: (a) *, ** and *** indicate significant at 1%, 5% and 10% levels respectively.
(b) Figures within the 1st and 3rd brackets represent the t-statistic and Chi Square respectively. (c) DW = Durbin-Watson test (see Durbin and Watson, 1950 and 1951). (d) SC = Serial Correlation (Lagrange multiplier test of residual serial correlation,: see Godfrey, 1978a and 1978b). (e) FF = Functional Form (Ramsey’s RESET test using the square of the fitted values: Ramsey, 1969). (f) NORM = Normality (based on a test of skewness and kurtosis of residuals: Bera and Jarque, 1981). (g) HET = Heteroscedasticity (based on the regression of squared residuals on squared fitted values, Koenker, 1981).
Chapter 6: Foreign Aid and Growth in Nepal
222
Since SBC and AIC indicate two different optimal lag lengths (4 and 1), we have
chosen 3 as the order of the VAR.8 The results of λmax and λtrace indicate the presence
of one significant cointegrating vector. Thus, it can be ascertained from the LR
statistics that in the presence of a deterministic trend, per capita real GDP and
aggregate aid are cointegrated. In other words, there exists a linear combination of the
I(1) variables that links them in a stable long-run relationship. The second half of
Table 6.5 presents the long-run cointegrating normalised coefficients. It shows that
aid has a positive but statistically insignificant relationship with per capita real GDP.
The error correction mechanism (ECM) results indicate that the error correction
coefficient, estimated at -0.085, is statistically significant at the 1 per cent level.
However, the short-run coefficient of aid is found to be negative and statistically
insignificant. Nonetheless, the diagnostic tests of serial correlation, functional form,
normality and heteroscedasticity confirm a good representation of variables in the model.
In our next step, we estimate the production function with foreign aid as an explanatory
variable in addition to capital stock. The results are presented in Table 6.6. The test
statistics support the hypothesis of one cointegrating vector. Thus, the results suggest
that in the presence of a deterministic trend, per capita real GDP and aid are cointegrated.
More importantly, the long-run normalised coefficients of aid and capital stock are found
to be positive and statistically significant at 5 and 1 per cent respectively. It implies that
with the inclusion of capital stock, aid coefficient is found to be not only significant and
positive, but also elasticity of per capita real GDP with respect to aid increases.
8 The optimal order of the lag length is determined by using the AIC and SBC for all equations considered here. In the case of two different optimal lag lengths, we first chose 2 as the order of the VAR due to the short data lengths, and then checked to see whether the chosen order of the VAR showed significant results and passed the diagnostic tests.
Chapter 6: Foreign Aid and Growth in Nepal
223 In addition, the value of adjusted R2 increased from 0.81 to 0.88. Thus, we can
reasonably conclude that aid contributes to per capita real GDP by enhancing the level of
technical knowledge. This can happen through the new knowledge embodied in imported
capital goods, made possible by aid. Technical assistance aid also contributes to
enhancing technical knowledge.9
Table 6.6: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (variables lnRGDPP, lnAR and lnKP) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.91005 r = 0 r = 1 48.17** 68.67** 0.50469 r <= 1 r = 2 14.05 20.50 0.27588 r <= 2 r = 3 6.45 6.65 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt Trend Coefficients 1.000 -0.009 -0.073 -0.024 Chi Square [4.32]** [7.01]* [33.96]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 15.010 ΔlnKP t-1 0.019 (9.97)* (0.64) ECT -0.084 ΔlnARt-1 -0.043 (-9.95)* (-2.66)**
ΔlnRGDPPt-1 0.425
(3.93)* Diagnostic testsR-Square 0.91 FF 0.55
R-Bar-Square 0.88 NORM 0.60
DW 1.78 HET 0.12
S C 0.58 Note: See Table 6.5.
9 Aid’s contribution to capital formation through importation of capital goods is examined fully in the next chapter.
Chapter 6: Foreign Aid and Growth in Nepal
224
The short-run coefficient of aid is found to be negative and statistically significant.
This indicates that in the short run the country may not be able to manage aid
efficiently because of lack of absorptive capacity (more on this later in the chapter).10
The short-run negative coefficient of aid may also be due to the fact that aid flows
increase initially in response to a fall in GDP as pointed out by Papanek (1972, 1973).
This also shows the importance of examining the long-run aid–growth relationship
along with the examination of short-run dynamics. As our results demonstrate, foreign
aid is positively associated with real GDP per capita in the long-run, although aid’s
contribution in the short-run may be doubtful. That is, there can be a short-run – long-
run paradox in aid effectiveness.
The ECM results further show that the ECT is negative and statistically significant
(0.084) at the 1 per cent level, implying that the aid–growth relationship is stable in
the long-run. The statistically significant error correction coefficient with an
appropriate sign represents the speed of adjustment back to the long-run relationship
among the variables. In precise terms, it implies that disequilibria of this period from
long-run per capita real GDP is adjusted by 8.4 per cent in the next period. While the
model diagnostic tests, that is, the tests of serial correlation, functional form,
normality and heteroscedasticity, confirm a good representation of variables in the
model.
Having examined the existence of a long-run cointegrating relationship between per
capita real GDP, aid and capital stock, we now proceed to estimate our main model,
10 The lack of absorptive capacity perhaps explains the findings of negative aid–growth relationship in some earlier studies.
Chapter 6: Foreign Aid and Growth in Nepal
225
given by equation (6.4). That is, we incorporate the adult literacy rate (ADLR) in
estimating the aid–GDP relationship in the production function.11 The results are
presented in Table 6.7A. As can be seen, the coefficient of aid (AR) increases
(although marginally) with the inclusion of the adult literacy variable. This suggests
that aid effectiveness depends on Nepal’s social capability to use aid.
11 ADLR is taken as an I(0) variable in all equations. Pesaran and Pesaran, (2003) noted: “The additional I(0) variables included in the VAR allows for the short run movements in the I(1) variables which moves them away from their long run equilibrium” (2003: 322). More importantly, it also appears to improve the fit of the regression.
Chapter 6: Foreign Aid and Growth in Nepal
226 Table 6.7A: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.4) lnRGDPP, lnAR, and lnKP (ΔlnADLR as an I(0) variable) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.92797 r = 0 r = 1 52.61** 71.22** 0.52635 r <= 1 r = 2 14.94 18.61 0.16763 r <= 2 r = 3 3.66 3.66 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt Trend Coefficients 1.000 -0.010 -0.075 -0.023 Chi Square [6.72]* [9.48]* [48.25]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 15.234 ΔlnARt-1 -0.043 (10.66* (-2.53)** ECT 0.085 ΔlnKPt-1 0.035 (10.64)* (1.15)
ΔlnRGDPPt-1 0.419 ΔlnADLR 0.004
(3.91)* (1.23) Diagnostic testsR-Square 0.92 FF 0.54 R-Bar-Square 0.89 NORM 0.97 DW 2.09 HET 0.21 S C 0.49 Note: See Table 6.5.
The Joahnsen’s Likelihood Ratio test results indicate the presence of one significant
cointegrating vector and confirm that the variables are cointegrated. In terms of the
long-run relationship, all the coefficients are found to be positive and statistically
significant. Thus, in the long run, aid has a positive relationship with per capita real
GDP. However, the ECM results show that the error correction coefficient, estimated
at 0.085, is positive and statistically significant at the one per cent level. The positive
Chapter 6: Foreign Aid and Growth in Nepal
227
error correction coefficient is not consistent with the theory and suggests that last
period’s disequilibrium is not corrected to converge towards equilibrium.
As the ECT is found to be positive, we re-estimated equation (6.4) by adding a
dummy variable to the model; the results are presented in Table 6.7B. We used a
dummy for political instability, taking the value of 0 for the period 1983-89 and 1 for
1990-2002. Generally, it is believed that political instability lowers the availability of
factors of production and thus impedes economic growth.12 Nepal was relatively
politically stable from 1970 until the late 1980s. But, throughout the 1990s up to the
present, Nepal has been facing severe political instability.13
12 See, for example, Alesina and Perotti (1994), and Edward and Tabellini (1991). 13 As discussed in chapter 3, more than eight governments were formed between 1990 and 2003 and Maoist rebel violence has been escalated across the country, claiming a total of more than 8,000 lives.
Chapter 6: Foreign Aid and Growth in Nepal
228 Table 6.7B: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.4) lnRGDPP, lnAR, and lnKP (ΔlnADLR as an I(0) variable and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.93627 r = 0 r = 1 55.06** 63.38** 0.31041 r <= 1 r = 2 7.43 8.32 0.04340 r <= 2 r = 3 0.88 0.88 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt Trend Coefficients 1.000 -0.019 -0.069 -0.024 Chi Square [6.79]* [9.20]* [54.02]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 15.514 ΔlnARt-1 -0.054 (10.78)* (-2.98)** ECT -0.085 ΔlnKPt-1 0.043 (-10.76)* (1.45)
ΔlnRGDPPt-1 0.427 ΔlnADLR 0.004
(3.93)* (1.16)
Dummy -0.011
(-2.49)** Diagnostic tests R-Square 0.93 FF 0.43 R-Bar-Square 0.90 NORM 0.86 DW 2.24 HET 0.36 S C 0.26 Note: See Table 6.5.
The model diagnostic tests, presented at the bottom of Table 6.7B, do not exhibit any
statistical problems and thus confirm a good representation of variables in the model.
Adjusted R2 shows that the model explains over 90 per cent of variation in per capita
real GDP, and the DW statistics confirm that the error term is serially uncorrelated.
Chapter 6: Foreign Aid and Growth in Nepal
229 The coefficient of the dummy is negative and statistically significant at the five per
cent level, implying that political instability has a direct, negative impact on the
growth rate of per capita real GDP. If we compare the results with the ones without
the dummy, we find that the coefficient of aid (AR) has increased and that of capital
stock (KP) has decreased. That is, political instability has reduced the elasticity of per
capita real GDP with respect to capital stock. This is an interesting finding. This
clearly shows the cost of political instability; political instability adversely affects the
productivity of capital. The increase in aid elasticity shows the importance of aid
flows during political instability. There could be many reasons why aid elasticity
increases in the presence of political instability. One reason could be that the
government spends more aid money on infrastructure to offset any decline in private
expenditure during the political turmoil. The government may also spend more on
social sector (e.g. education) to ease political tensions. Both infrastructure investment
and increased social expenditure positively affect growth.
With the inclusion of the political dummy the coefficient of the ECM becomes
negative and statistically significant. Among the short-run coefficients, while the
coefficient of per capita real GDP is found to be positive and significant at the 1 per
cent level, the coefficients of capital and adult literacy rate are found to be positive
but insignificant.
Once again, we find that the short-run coefficients of foreign aid are negative and
statistically significant in both cases (with and without a political dummy). Poudyal
(1988) also found a negative relationship between aid and growth in the short-run. It
has an important implication in terms of absorptive capacity, aid conditionality and
Chapter 6: Foreign Aid and Growth in Nepal
230
aid volatility. Nepal’s immediate capacity for the effective use of aid appears to be
weak, for various reasons. They include shortages of skill, institutional weaknesses,
budget constraints with regard to counter fund for aid-financed projects. In addition,
the government is sometimes unable to mobilise the volume of aid on time and fails to
persuade donors that remaining funds will be spent efficiently. Thus, disbursement of
aid may be further delayed, hampering the government’s spending ability.14
The negative effect of aid in the short-run may also be due to aid conditionalities. The
government is required to cut expenditure and pursue reforms, such as privatisation.
These may have an adverse effect on economic growth in the short-run.
The volatility of aid flows could contribute to negative GDP growth because of
uncertainty. Some recent empirical studies have focused on the magnitude and
consequences of aid volatility. They find that foreign aid is more volatile than
government current revenue in almost all developing countries.15 According to these
studies, aid effectiveness has been undermined by the (uncoordinated and diverse)
nature of the international aid delivery system. Aid disbursement could also be more
volatile as a result of changing economic and political conditions in the recipient as
well as donor country.
14 It has been argued that in a developing country, absorptive capacity plays a crucial role for the effectiveness of foreign aid (see, Killick, 1991). Other recent studies such as Burnside and Dollar (2000), Hansen and Tarp (2000), and Lensink and White (2001) have used aid square term in the model to see whether returns to aid are diminishing due to absorptive capacity problems. 15 See, for example, Bulir and Hamann (2003), UNCTAD (2000), and Lensink and Morrissey (2000). In one study of 48 developing countries, Gemmell and McGillivray (1998) found that shortfalls in aid disbursement are followed most frequently by reductions in government spending, sometimes by increases in taxes, and sometimes by both. More importantly, the aid recipient country is unable to offset unexpected non-disbursement of aid by borrowing, and thus has to pay very high cost.
Chapter 6: Foreign Aid and Growth in Nepal
231 Summary: The empirical results show that foreign aid has a positive and statistically
significant effect on per capita real GDP in the long-run. The elasticity of per capita
real GDP with respect to aid is about 0.02 per cent. It implies that a 1 per cent
increase in aid flows leads to an increase of 0.02 per cent on average in per capita real
GDP. However, in the case of short-run dynamics, the immediate impact of changes
of aid has a negative impact in the changes of per capita real GDP, possibly due to
lack of absorptive capacity and aid volatility. Thus, there seems to be a paradox
between short-run and long-run effects of aid. We also find that interestingly aid
elasticity of per capita real GDP rises in the presence of political instability.
6.3.3 Effectiveness of different components of aid
Bilateral and multilateral aid
In the next step, total aid is disaggregated into bilateral (BAR) and multilateral
(MAR) aid as a percentage of GDP. We estimate equation (6.5) using only bilateral
aid as an explanatory variable (including capital stock and adult literacy).16 Table
6.8A presents the results, showing that λmax and λtrace are significant enough to
indicate the existence of one cointegrating vector. A long-run equilibrium relationship
therefore exists between variables in equation (6.5). The long-run cointegrating
normalised coefficients are found to be positive and statistically significant at the 1
per cent level. However, the short-run coefficient of growth of bilateral aid is negative
although statistically insignificant. The error correction coefficient, estimated at
0.084, is found to be negative and statistically significant at the 1 per cent level.
The model diagnostic tests do not show any statistical problems.
16 We estimated bilateral and multilateral aid separately to avoid the degrees of freedom problem as we have only 20 observations. However, we have also tried with both variables in the same equation and the results are presented in appendix 6.3 at the end of the thesis (after references).
Chapter 6: Foreign Aid and Growth in Nepal
232 Table 6.8A: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (bilateral aid only, lnRGDPP, lnBAR, and lnKP (ΔlnADLR as an I(0) variable and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.92381 r = 0 r = 1 51.48** 62.33** 0.32654 r <= 1 r = 2 7.90 10.84 0.13662 r <= 2 r = 3 2.93 2.93 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnBARt lnKPt Trend Coefficients 1.000 -0.014 -0.101 -0.023 Chi Square [10.09]* [39.32]* [43.89]*
Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients
Intercept 15.794 ΔlnBARt-1 -0.012 (8.93)* (-0.66) ECT -0.084 ΔlnKPt-1 -0.001 (-8.92)* (-0.05)
ΔlnRGDPPt-1 0.438 ΔlnADLR 0.009 (3.27)* (2.18)** Dummy -0.003 (-0.64)
Diagnostic tests
R-Square 0.90 FF 0.54 R-Bar-Square 0.86 NORM 0.70 DW 2.31 HET 0.26 SC 0.24 Note: See Table 6.5.
Chapter 6: Foreign Aid and Growth in Nepal
233 Table 6.8B: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (multilateral aid only, lnRGDPP, lnMAR, and lnKP (ΔlnADLR as an I(0) variable and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.94053 r = 0 r = 1 56.44** 68.66** 0.43813 r <= 1 r = 2 11.52 12.21 0.033679 r <= 2 r = 3 0.68 0.68 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnMARt lnKPt Trend Coefficients 1.000 -0.013 -0.090 -0.023 Chi Square [5.98]** [13.22]* [53.64]*
Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients
Intercept 15.448 ΔlnMARt-1 -0.044 (12.52)* (-3.92)* ECT -0.091 ΔlnKPt-1 0.040 (-12.50)* (1.49)
ΔlnRGDPPt-1 0.448 ΔlnADLR 0.006 (4.37)* (1.79)*** Dummy -0.004 (-1.20)
Diagnostic tests
R-Square 0.94 FF 0.90 R-Bar-Square 0.91 NORM 0.21 DW 2.05 HET 0.26 SC 0.77 Note: See Table 6.5.
To investigate the effect of multilateral aid, we again estimate equation (6.5)
considering multilateral aid only (Table 6.8B). We find that per capita real GDP and
multilateral aid are cointegrated. In terms of a long-run relationship, the coefficient of
Chapter 6: Foreign Aid and Growth in Nepal
234 multilateral aid is found to be positive and statistically significant at the 5 per cent
level. The long-run coefficient of multilateral aid is about the same as that of bilateral
aid (0.013 and 0.014, respectively). Thus, in the long-run, both bilateral and
multilateral aid play almost equal role in affecting per capita real GDP.
Interestingly, however, the long-run coefficient of total aid (0.019) is higher than the
long-run coefficients of bilateral and multilateral aid individually. This implies
complementarities between bilateral and multilateral aid. This perhaps explains why
the political dummy is not significant when aid is disaggregated.
When we consider the ECM results, multilateral aid is found to be negative and
statistically significant. The error correction coefficient, estimated at -0.091, is found
to be statistically significant at the 1 per cent level. Thus, the short-run coefficient of
multilateral aid shows that the immediate impact of changes in multilateral aid is
negatively related with the changes in per capita real GDP. There could be two
reasons for the short-run negative relationship. It can happen due to adverse short-run
effect of conditional disbursement. Because of conditionality, which is often imposed
by multilateral donor, government has to reduce expenditure that may affect growth in
the short-run. At the same time, as in aggregate aid, the short-run negative effect of
multilateral aid on per capita real GDP confirms that Nepal does have problems of
absorptive capacity, and the impact of aid volatility on the economy is large.
Chapter 6: Foreign Aid and Growth in Nepal
235 Grants and loans aid To measure the impact of grants and loans aid, we further disaggregate total aid into
grants (GR) and loans aid (LAR) (equation 6.6). As in the case of bilateral and
multilateral aid, we estimate grants aid and loans aid one at a time. Table 6.9A
presents the results for cointegration. These indicate that during the period under
study, a long-run equilibrium relationship exists between grants aid and per capita real
GDP.
Among the long-run cointegrating normalised coefficients, all coefficients are found
to be positive and statistically significant at the 1 per cent level. More importantly, the
elasticity of per capita real GDP with respect to grants is found to be higher (0.018)
than those of bilateral (0.014) and multilateral aid (0.013). However, the short-run
coefficient of grants is found to be negative although insignificant.
We also estimate equation (6) using loans aid only. Table 6.9B presents the
Johansen’s Likelihood Ratio test results for cointegration. The results indicate that per
capita real GDP and loans aid are cointegrated. In terms of a long-run relationship,
although the coefficients of loans aid and capital stock are found to be positive and
statistically significant at the 1 and 5 per cent levels respectively, the elasticity of per
capita real GDP with respect to loans aid (0.006) is found to be much smaller than
grants aid (0.018). Thus, the results reveal that grants aid is more important to the
Nepalese economy than loans aid. Loans aid causes a debt burden because of future
repayments whereas grants aid is free resources.17 On the other hand, as with
multilateral and aggregate aid, the short-run coefficient of loans aid is found to be
17 See chapter 3 on Nepal’s foreign debt burden. There is a vast literature on the debt crisis in developing countries. See, for example, Sachs (1988).
Chapter 6: Foreign Aid and Growth in Nepal
236 negative and statistically significant, suggesting once again lack of absorptive
capacity and the presence of aid volatility.
Table 6.9A: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (grants aid only, lnRGDPP, lnGR, and lnKP (ΔlnADLR as an I(0) variable and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.91342 r = 0 r = 1 48.93** 64.62** 0.48392 r <= 1 r = 2 13.22 15.68 0.11573 r <= 2 r = 3 2.45 2.45 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnGRt lnKPt Trend Coefficients 1.000 -0.018 -0.086 -0.023 Chi Square [8.65]* [33.65]* [36.33]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients
Intercept 15.534 ΔlnGRt-1 -0.018 (8.63)* (-0.79) ECT -0.082 ΔlnKPt-1 0.008 (-8.62)* (0.23)
ΔlnRGDPPt-1 0.421 ΔlnADLR 0.007 (2.95)* (1.87)*** Dummy -0.001 (-0.37) Diagnostic tests
R-Square 0.90 FF 0.31 R-Bar-Square 0.85 NORM 0.67 DW 2.11 HET 0.22 S C 0.51 Note: See Table 6.5.
Chapter 6: Foreign Aid and Growth in Nepal
237 Table 6.9B: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (loans aid only, lnRGDPP, lnLAR, and lnKP (ΔlnADLR as an I(0) variable and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.92516 r = 0 r = 1 51.84** 66.99** 0.48963 r <= 1 r = 2 13.45 15.14 0.081174 r <= 2 r = 3 1.69 1.69 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnLARt lnKPt Trend Coefficients 1.000 -0.006 -0.088 -0.023 Chi Square [3.22]** [9.26]* [36.74]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients
Intercept 15.805 ΔlnLARt-1 -0.019 (11.18)* (-2.72)** ECT -0.090 ΔlnKPt-1 0.028 (-11.16)* (0.94)
ΔlnRGDPPt-1 0.477 ΔlnADLR 0.007 (3.99)* (2.02)** Dummy -0.002 (-0.64) Diagnostic tests
R-Square 0.92 FF 0.70 R-Bar-Square 0.89 NORM 0.97 DW 2.11 HET 0.24 S C 0.66 Note: See Table 6.5.
Summary: The relationships between disaggregated forms of aid (bilateral,
multilateral, and grants and loans aid) and per capita real GDP are found to be
positive and statistically significant in the long-run. These findings shed light on the
effectiveness of aid in Nepal. First, loans aid has been less effective in the Nepalese
Chapter 6: Foreign Aid and Growth in Nepal
238
economy in the long-run compared with grants aid. Second, in the short-run, aid is
found to affect economic growth negatively, which might be attributed to adverse
effects of conditional attachment of aid disbursement. This also indicates that Nepal
does not have an adequate absorptive capacity. This may also be due to uncertainly
associated with the high volatility of aid flows.
6.4 Aid, policies and per capita real GDP
This part of the chapter examines the role of policy environment in the effectiveness
of aid. In other words, we investigate whether the aid/GDP relationship is affected
when policy variables are considered. As indicators of policy, we include TR (trade as
percentage of GDP – a measure of trade policy)18, CPI (consumer price index – a
measure of macroeconomic policy) and MONR (M2 as percentage of GDP – a
measure of financial sector policy).19
We begin with the investigation of the effect of policy variables on per capita real
GDP. The estimated results are reported in Tables 6.10A to 6.10C.
18 One can argue that tariff rates as a proxy for trade policy variable is more appropriate than trade because aid dependent country like Nepal trade as percentage of GDP might be high, even if policy regime is restrictive. However, tariff rates do not capture the impact of non-tariff barriers, which were very high in Nepal until the mid 1980s and the time series data are not available for the estimates of effective rate of protection. See also footnote of page 212 for more discussion and Sharma (1999) for Nepal’s trade policy. 19 We also used BDR (budget deficit as percentage of GDP) as an alternative measure of macroeconomic policy, but that did not improve the results significantly. As a matter of fact, inflation correlates highly with budget deficit.
Chapter 6: Foreign Aid and Growth in Nepal
239 Table 6.10A: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7a), lnRGDPP and lnTR) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.85829 r = 0 r =1 39.07** 41.53** 0.11557 r <= 1 r = 2 2.45 2.45 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnTRt Trend Coefficients 1.000 -0.017 -0.024 Chi Square [2.86]*** [38.53]* Error correction model for lnRGDPP Variables Coefficients Variables Coefficients Intercept 16.98 ΔlnRGDPPt-1 0.468 (9.32)* (3.63)* ECT -0.094 ΔlnTRt-1 0.027 (-9.30)* (0.93) Diagnostic tests
R-Square 0.86 FF 0.36 R-Bar-Square 0.83 NORM 0.44 DW 2.19 HET 0.16 S C 0.48
Chapter 6: Foreign Aid and Growth in Nepal
240 Table 6.10B: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7b), lnRGDPP and lnCPI) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.86935 r = 0 r =1 40.70** 44.37** 0.16763 r <= 1 r = 2 3.66 3.66 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnCPIt Trend Coefficients 1.000 -0.051 -0.020 Chi Square [5.03]* [22.54]* Error correction model for lnRGDPP Variables Coefficients Variables Coefficients Intercept 14.43 ΔlnRGDPPt-1 0.303 (8.41)* (2.24)** ECT -0.084 ΔlnCPIt-1 -0.139 (-8.38)* (-2.27)** Diagnostic tests
R-Square 0.86 FF 0.39 R-Bar-Square 0.83 NORM 0.58 DW 1.64 HET 0.27 S C 0.37
Chapter 6: Foreign Aid and Growth in Nepal
241 Table 6.10C: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7c), lnRGDPP and lnMONR) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.85307 r = 0 r = 1 38.35** 43.61** 0.23118 r <= 1 r = 2 5.25 5.25 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnMONRt Trend Coefficients 1.000 0.066 -0.027 Chi Square [4.91]* [34.73]* Error correction model for lnRGDPP Variables Coefficients Variables Coefficients Intercept 16.86 ΔlnRGDPPt-1 0.408 (8.94)* (2.89)* ECT -0.094 ΔlnMONRt-1 0.056 (-8.92)* (0.85) Diagnostic tests
R-Square 0.85 FF 0.96 R-Bar-Square 0.82 NORM 0.67 DW 1.66 HET 0.23 S C 0.38 Notes: (a) *, ** and *** indicate significant at 1%, 5% and 10% level respectively.
(b) Figures within the 1st and 3rd brackets represent the t-statistic and Chi Square respectively. (c) DW = Durbin–Watson test (see Durbin and Watson, 1950 and 1951) (d) SC = Serial Correlation (Lagrange multiplier test of residual serial correlation: Godfrey, 1978a and 1978b). (e) FF = Functional Form (Ramsey’s RESET test using the square of the fitted values: Ramsey, 1969). (f) NORM = Normality (based on a test of skewness and kurtosis of residuals: Bera and Jarque, 1981). (g) HET = Heteroscedasticity (based on the regression of squared residuals on squared fitted values: Koenker, 1981).
Chapter 6: Foreign Aid and Growth in Nepal
242 The Johansen’s Likelihood Ratio test results for cointegration show that all three
policy variables are cointegrated with per capita real GDP. Among the long-run
cointegrating normalised coefficients, the coefficients of TR and CPI are found to be
positive and statistically significant at the 10 and 1 per cent levels, respectively
(Tables 6.10A and 6.10B), and the coefficient of MONR is found to be negative and
statistically significant at the 1 per cent level (Table 6.10C). While the long-run
coefficient of trade variable (TR) has the expected sign, the long-run coefficients of
both CPI and financial reform variable (MONR) do not. We expect them to be
associated negatively and positively with real per capita GDP, respectively, in the
long-run.
Next we examine the impact of these policies together on aid effectiveness. However,
we take two policy variables at a time due to the degrees of freedom constraint. That
is, we estimate the model taking a permutation of two policy variables: (1) TR and
CPI; (2) TR and MONR, and (3) CPI and MONR. The combination of CPI and
MONR did not produce statistically significant results and hence are not reported here
(see appendix 6.1). This could be due to high correlation between CPI and MONR.
The estimation results for the other two sets are presented in Tables 6.11A (with TR
and CPI) and 6.11B (with TR and MONR).
Chapter 6: Foreign Aid and Growth in Nepal
243 Table 6.11A: Estimates of Johansen’s Likelihood Ratio test, 1983-2002(equation (6.7d), lnRGDPP, lnAR, lnKP, lnTR, and lnCPI (ΔlnADLR as an I(0) variable) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.97326 r = 0 r = 1 72.42** 141.12** 0.83660 r <= 1 r = 2 36.23** 68.70** 0.58810 r <= 2 r = 3 17.73 32.46 0.45965 r <= 3 r = 4 12.31 14.72 0.11392 r <= 4 r = 5 2.41 2.41 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt lnTRt lnCPIt Trend Coefficients 1.000 -0.032 -0.039 -0.058 0.165 -0.037 Chi Square [4.07]* [0.76] [2.52] [3.94]** [13.66]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 18.099 ΔlnKPt-1 0.080 (7.82)* (1.76)*** ECT 0.079 ΔlnTRt-1 -0.012
(7.80)* (-0.35)
ΔlnRGDPPt-1 0.543 ΔlnCPIt-1 0.267 (3.20)* (2.89)** ΔlnARt-1 -0.089 ΔlnADLR 0.006 (-3.62)* (1.25)
Diagnostic tests
R-Square 0.89 FF 0.84 R-Bar-Square 0.83 NORM 0.52 DW 2.26 HET 0.64 SC 0.18 Note: See Table 6.10C.
Chapter 6: Foreign Aid and Growth in Nepal
244 Table 6.11B: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7e) lnRGDPP, lnAR, lnKP, lnTR, and lnMONR (ΔlnADLR as an I(0) variable) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.96679 r = 0 r = 1 68.09** 148.71** 0.90586 r <= 1 r = 2 47.25** 80.61** 0.61400 r <= 2 r = 3 19.03 33.35 0.44921 r <= 3 r = 4 11.92 14.31 0.11241 r <= 4 r = 5 2.38 2.38 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt lnTRt lnMONRt Trend Coefficients 1.000 -0.059 -0.218 -0.019 -0.289 -0.011 Chi Square [4.60]* [10.55]* [1.05] [3.64]** [1.11] Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 7.481 ΔlnKPt-1 0.018
(5.05)* (0.28) ECT 0.074 ΔlnTRt-1 0.002
(5.03)* (0.04)
ΔlnRGDPPt-1 0.117 ΔlnMONRt-1 -0.188 (0.61) (-1.97)*** ΔlnARt-1 -0.063 ΔlnADLR 0.011 (-2.02)** (1.51)
Diagnostic tests
R-Square 0.78 FF 0.15 R-Bar-Square 0.66 NORM 0.55 DW 1.80 HET 0.64 SC 0.67 Note: See Table 6.10C.
Chapter 6: Foreign Aid and Growth in Nepal
245 The Johansen’s Likelihood Ratio test results show that the variables under study are
cointegrated in both cases (i.e, when TR and CPI and TR and MONR are included in
the model). The long-run cointegrating normalised coefficient of aid increased in both
cases compared to when no policy variable was included (Table 6.7B), indicating that
aid-effectiveness improved in the presence of good policy environment. However,
although all the policy variables have the expected signs, the trade policy variable
(TR) is not significant. In addition, the error correction coefficients in both cases are
found to be a positive. Therefore, we re-estimated the equations (6.7d and 6.7e)
adding a dummy variable (to capture the effect of political instability), and the results
are presented in Tables 6.12A and 6.12B.
Chapter 6: Foreign Aid and Growth in Nepal
246 Table 6.12A: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7d), lnRGDPP, lnAR, lnKP, lnTR, and lnCPI, (ΔlnADLR as an I(0) variable) and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.97440 r = 0 r = 1 73.30** 134.34** 0.83619 r <= 1 r = 2 36.18** 61.04*** 0.57667 r <= 2 r = 3 17.19 24.86 0.21891 r <= 3 r = 4 4.94 7.67 0.12756 r <= 4 r = 5 2.72 2.72 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt lnTRt lnCPIt Trend Coefficients 1.000 -0.036 -0.028 -0.063 0.170 -0.038 Chi Square [4.90]** [0.38] [2.96]*** [4.32]** [14.35]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 18.303 ΔlnKPt-1 0.088
(7.84)* (1.93)*** ECT -0.080 ΔlnTRt-1 -0.011
(7.82)* (-0.30)
ΔlnRGDPPt-1 0.578 ΔlnCPIt-1 0.264 (3.25)* (2.87)** ΔlnARt-1 -0.103 ΔlnADLR 0.004 (-3.66)* (0.82) Dummy -0.017 (-1.81)*** Diagnostic tests R-Square 0.90 FF 0.66 R-Bar-Square 0.83 NORM 0.46 DW 2.33 HET 0.64 SC 0.13 Note: See Table 6.10C.
Chapter 6: Foreign Aid and Growth in Nepal
247 Table 6.12B: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7e), lnRGDPP, lnAR, lnKP, lnTR, and lnMONR, (ΔlnADLR as an I(0) variable and dummy) VAR(2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.98864 r = 0 r = 1 89.55** 165.39** 0.91507 r <= 1 r = 2 49.31** 75.83** 0.50351 r <= 2 r = 3 14.00 26.52 0.40931 r <= 3 r = 4 10.52 12.51 0.09458 r <= 4 r = 5 1.98 1.98 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt lnTRt lnMONRt Trend Coefficients 1.000 -0.297 -0.509 -0.122 -1.317 -0.030 Chi Square [26.14]* [30.98]* [16.87]* [24.21]* [5.07]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept -0.212 ΔlnKPt-1 0.023
(-2.87)** (0.26) ECT -0.063 ΔlnTRt-1 0.010
(-3.32)* (0.16)
ΔlnRGDPPt-1 0.076 ΔlnMONRt-1 -0.320 (0.28) (-2.20)** ΔlnARt-1 -0.178 ΔlnADLR 0.004 (-3.15)* (0.44) Dummy -0.032 (-2.09)** Diagnostic tests R-Square 0.66 FF 0.01 R-Bar-Square 0.42 NORM 0.76 DW 1.89 HET 0.68 SC 0.38 Note: See Table 6.10C.
Chapter 6: Foreign Aid and Growth in Nepal
248 In both cases (when TR and CPI and TR and MONR are considered), the dummy is
found to be negative and statistically significant, meaning that political instability
affects the economy adversely, as the productivity of capital stock declines.
However, with the inclusion of a political instability dummy variable the long-run
coefficients of aid has increased from 0.032 to 0.036, in the presence of trade and
macro policy variables and from 0.059 to 0.3 in the case of trade and financial sector
policy variables. In addition, all the variables in the model have right signs.
The sign and the size of the ECM term are also as per our expectation (negative and
less than one). This indicates that the model with policy variables is stable in the long-
run. The short-run dynamics shows that even in the presence of good policy variables,
changes of aid is negatively associated with the changes of per capita real GDP. The
signs of short-run coefficients of policy variables are also found to be perverse,
implying that it takes time for the economy to adjust to policy changes.
6.5 Summary and conclusion
This chapter presents our main empirical analysis of the effectiveness of aid in Nepal.
We have empirically investigated the impact of aggregate and disaggregated forms of
aid on per capita real GDP. To address the current debate on whether aid works only
in a good policy environment, we have included policy variables for macroeconomic
stability, financial sector development and openness in an extended model.
We generally find that aid is positively related to per capita real GDP in the long-run.
The channel through which aid affects growth of GDP is technological progress. That
Chapter 6: Foreign Aid and Growth in Nepal
249 is, aid helps upgrade technology by helping import capital goods. Aid in the form of
technical assistance also improves Nepal’s institutional capacity. Overall capacity to
reap the benefit of aid depends on Nepal’s social capability as captured by the adult
literacy rate. However, in the short-run the impact of aid is negative. This could be
due to problems associated with absorptive capacity, aid management, coordination
and allocation, and aid conditionalities. We also find that aid assumes additional
importance during times of political instability, when the productivity of capital
declines. Aid flows in that circumstance can maintain the economy.
Among the disaggregated forms of aid, bilateral and multilateral aid play about the
same role. However, bilateral and multilateral aid have strong complementarities.
Grants aid is found to have a stronger positive association with per capita real GDP
than loans aid. These findings have some important implications. First, loan aid
creates a debt burden because of future repayments. Currently, almost 13 per cent of
revenue is used for debt service, which is about 8 per cent of total government
expenditure in Nepal. Debt service payment as a ratio of total exports increased from
less than 1 per cent in the 1970s to over 6 per cent in 2001. This persistently hampers
government’s expenditure on infrastructure and social development.
The second implication is that disbursement of aid is generally conditional on
structural adjustment. Therefore, the direct effect of multilateral aid on GDP may not
be observable as it works through policy variables; but the economy might be affected
negatively in the short-run. As our results show, aid effectiveness improves in the
present of good policies in the long-run. Nepal’s policy environment improved
Chapter 6: Foreign Aid and Growth in Nepal
250 significantly since the mid 1980s when it implemented various Structural Adjustment
Programs.
In sum, aid has been effective in increasing and maintaining the economic growth in
Nepal. Its effectiveness has improved in the presence of a good policy environment.
However, as is well-known, growth does not necessarily trickle down and improve
socio-economic conditions. In fact, as discussed in chapter 2, inequality and poverty
in Nepal have increased over time. So, even though aid seems to have contributed to
economic growth, one can question the quality of growth.
Chapter 6: Foreign Aid and Growth in Nepal
251 Appendix 6.1: Estimates of Johansen’s Likelihood Ratio test, 1983-2002 (equation (6.7f) lnRGDPP, lnAR, lnKP, lnCPI, lnMONR and ΔlnADLR(as an (I(0) variable) VAR (2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.96791 r = 0 r = 1 68.78** 139.85** 0.86069 r<=1 r = 2 39.42** 71.07** 0.56238 r<=2 r = 3 16.52 31.65 0.44266 r<=3 r = 4 11.69 15.12 0.15782 r<=4 r = 5 3.43 3.43 Long-run cointegrating normalised coefficients
Variables lnRGDPPt lnARt lnKPt lnCPIt lnMONRt Trend Coefficients 1.000 0.015 -0.028 -0.0003 -0.099 -0.028 Chi square [1.48] [0.68] [0.0003] [1.09] [8.51]* Error correction model for lnRGDPP
Variables Coefficients Variables Coefficients Intercept 17.76 ΔlnKPt-1 0.059
(8.83)* (1.76) ECT -1.96 ΔlnCPIt-1 -0.040
(-8.80)* (-0.55)
ΔlnRGDPPt-1 0.363 ΔlnMONRt-1 0.048 (2.19)** (0.71) ΔlnARt-1 0.011 ΔlnADLR 0.005 (0.51) (1.33)
Diagnostic tests
R-Square 0.92 FF 0.46 R-Bar-Square 0.87 NORM 0.66 DW 1.94 HET 0.23 SC 0.93 Notes: *, ** and *** indicate significant at 1%, 5% and 10% level respectively. Figures within the
small and square brackets represent the t-statistics and Chi square respectively.
Chapter 7
Foreign Aid, Savings and Investment
“As a policy problem, the balance of payments limitation is quite similar to the savings–investment limitation… It is not clear a priori … which of these … is more likely to limit growth … The parallelism between the two is completed by the fact that a foreign capital inflow plays a dual role in adding to both investment and foreign exchange resources” (Chenery and Bruno, 1962: 85).
7.1 Introduction
In the previous chapter, we assumed that aid contributes to economic growth via
technological progress. This chapter hypothesises that aid contributes to growth
through enhancing the investment rate. It is generally the case that savings rates in
poor countries like Nepal are very low. This limits investment and thus economic
growth. In other words, they are locked into a “vicious circle” of low income, low
savings, low investment and hence low income.1 This creates a gap between available
savings and investment needed for rapid economic growth. In such circumstances, it
is assumed that foreign economic assistance can fill this gap and hence enhance
economic growth. In this chapter, we look at the impact of foreign aid on the gap
between domestic savings and investment. It is assumed that each dollar of foreign
resources in the form of aid would result in an increase of one dollar in total savings
and investment. This is the basis for the extension of the Harrod–Domar growth
model into the two-gap model by Chenery and his associates.
The national income accounting identity S = I shows that ex post saving and
investment are equal for a closed economy. That is, in a closed economy, investment
1 Chenery and Strout (1966) describe this situation as “investment-limited growth”.
Chapter 7: Foreign Aid, Savings and Investment
253 is bound to be solely financed by domestic savings. Hence, one will get a very high
(almost perfect) correlation between domestic savings and investment. The same is
likely to occur even in an open economy if they have a closed capital account, or as
Feldstein and Horioka (1980) have shown, if capital does not move between
countries.
Most developing countries do not receive substantial private capital flows. Their
savings–investment gap is mostly filled by foreign aid. Therefore, we can apply the
Feldstein and Horioka approach to test the effectiveness of foreign aid in developing
countries. In the context of a developing country, a low savings–investment
correlation would indicate that foreign aid contributes to investment and hence to
economic growth. On the other hand, a high savings–investment correlation would
imply either mis-utilisation or ineffectiveness of foreign aid. In other words, it may
indicate a negative relationship between aid and savings, as argued by Griffin and
Enos (1970), and recently by Boone (1996).
Nepal is a low-saving country with an average savings/GDP ratio of less than 12 per
cent during 1970-2002. The savings rate increased marginally to 13 per cent in the
1990s. This rate is far less than what is required for high enough economic growth to
have any effect on poverty reduction and self-sustaining development. This is a remit
of a low level of income, with almost 40 per cent of the population remaining below
the poverty line. Public sector saving is either negative or very low due to low
revenue mobilisation and high consumption of government. On the other hand, the
average investment/GDP ratio was 16.6 per cent during 1970-2002. It increased from
17.6 per cent during 1980-90 to 20.2 per cent during 1990-2002. Thus, one can see a
Chapter 7: Foreign Aid, Savings and Investment
254 gap between savings and investment, which gap can be financed through foreign
savings.
Table 7.1 presents the situation in Nepal from a comparative perspective. Among the
South Asian counties, Nepal’s average saving rate (SR) is higher than that of
Bangladesh and it is almost equal to that of India during the period 1970-2002.
Nepal’s average investment rate (IR) is also higher than that of Bangladesh and
Pakistan. Among the South Asian countries, Nepal’s aid/GDP ratio has been the
highest. As opposed to other countries, especially India, aid more than fully financed
Nepal’s savings–investment gap. As a matter of fact, a substantial amount of aid goes
for diaster relief. Aid also goes to service the debt on account of past loans.
Chapter 7: Foreign Aid, Savings and Investment
255 Table 7.1: SR, IR, AR and GAP for South Asian countries, 1970-2002
Country SR
(savings/GDP) IR
(investment/GDP) GAP
(SR–IR) AR (aid/GDP) AR-GAP
Nepal 1970-1979 8.32 11.45 -3.13 4.37 1.24 1980-1989 10.44 17.64 -7.19 10.69 3.50 1990-2002 12.97 20.19 -7.22 9.86 2.64 1970-2002 10.79 16.67 -5.88 8.29 2.41 India 1970-1979 9.85 16.77 -6.92 1.22 -5.70 1980-1989 9.80 20.65 -10.85 1.31 -9.54 1990-2002 11.83 22.26 -10.43 0.94 -9.49 1970-2002 10.71 19.96 -9.25 1.14 -8.11 Bangladesh 1973-1979 4.16 8.77 -4.61 9.20 4.59 1980-1989 3.86 11.06 -7.20 9.21 2.01 1990-2002 15.37 20.04 -4.67 3.68 -0.99 1973-2002 8.67 14.19 -5.52 6.84 1.32 Pakistan 1970-1979 10.40 15.28 -4.89 4.97 0.08 1980-1989 9.88 17.02 -7.14 4.02 -3.12 1990-2002 15.11 16.28 -1.17 3.13 1.96 1970-2002 12.07 16.12 -4.06 3.92 -0.14 Sri Lanka 1970-1979 13.43 17.51 -4.08 5.01 0.93 1980-1989 13.07 25.50 -12.43 9.58 -2.85 1990-2002 15.97 24.42 -8.45 4.71 -3.74 1970-2002 14.35 22.34 -7.99 6.12 -1.87 Source: IMF/IFS and OECD/IDS online databases
In this chapter, we investigate the relationship between aid and savings-investment
gap in Nepal. We employ cointegration and the error correction mechanism.
Furthermore, if the series are found to be I(1) but not cointegrated, we perform the
bivariate Granger causality test. In addition, we analyse the impulse response function
to examine the dynamic stability of the relationships under investigation.
The structure of the chapter is as follows. The next section contains a brief over-view
of the literature on aid and the savings–investment debate. Section 7.3 develops the
Chapter 7: Foreign Aid, Savings and Investment
256
empirical model based on national income identities. Section 7.4 presents the data,
model and methodology. Section 7.5 discusses the empirical results. The final section
provides a summary and conclusion.
7.2 Foreign aid and savings–investment – a brief review of the debate
Many early studies have focused their investigation of the effects of foreign aid on
savings. Hansen and Tarp (2000) refer to them as “second-generation” studies.2
However, aid’s role in filling the savings–investment gap remains a controversial
issue. During the mid 1960s, the discussion was dominated by the cogent two-gap
model, which advocated that foreign aid plays an important role in the development of
poor countries. In the second phase of discussion, the debate turned to the possibility
of an inverse relationship between foreign capital inflows and domestic savings.
About the time Chenery and his associates were developing the two-gap model, which
assumes a positive link between foreign aid and domestic savings-investment gap,
Haavelmo (1963) hypothesised that if capital inflows were very high, domestic
savings could be negative. Following a slightly modified Haavelmo model, Rahman
(1968) ran a regression of savings ratio on the ratio of capital inflows to GNP.3 He
used cross sectional data for 31 developing countries for the year 1962, and found
evidence to support the Haavelmo hypothesis. Griffin and Enos (1970) and Weisskopf
(1972), in cross-country empirical analyses, also found an inverse relationship
2 Aid–growth production function type studies such as the one considered in the previous chapter are referred to as “first-generation” studies. 3 Rahman (1968) suggested the following equation, s (t) = aY(t) + b1 H (t), where s is domestic savings, Y is GNP, and H is capital inflows. He specified the model using savings ratio and foreign capital ratio to GNP.
Chapter 7: Foreign Aid, Savings and Investment
257
between foreign inflows and domestic savings. They argued that instead of
accelerating development, foreign capital inflows retarded it and made developing
countries more dependent on such inflows. In particular, Griffin and Enos (1970)
generated controversy as they claimed that aid was provided not on the basis of
economic needs but in accordance with political expediency.4 They also stressed the
fungibility nature of aid by arguing that as a result of donors’ biased strategies, at least
some portion of aid was spent on consumption rather than investment. Recently,
consistent with these early studies, Boone (1996) found no significant relationship
between foreign aid, growth and domestic saving. He found that most aid was spent
on consumption.
Griffin and Enos’ conclusions generated a series of responses. For example, Papanek
(1972, 1973), and Kennedy and Thirlwall (1971) argued that a country receives aid
because of its low savings rate, and more importantly, when savings are low, more aid
is given to meet shortfalls in domestic savings. Thus, one can find a negative
correlation between aid and domestic savings. In three generations of empirical work,
Hansen and Tarp (2000) found a strong and positive relationship between aid, savings
and growth (see further chapter 4). Their sample of 41 aid–savings regressions
revealed that foreign aid led to an increase in total savings.
Thus, the empirical estimates of the effects on savings of foreign aid vary with the
sample selection and model specification. More importantly, the lack of any
agreement as to the relationship between domestic savings and foreign aid may be due
4 More precisely, Griffin and Enos argued: “How much a country lends to another country will not be determined by its need, or its potential, or its past economic performance, good or bad, or its virtue, but by the benefit it yields in terms of political support” (1970: 315).
Chapter 7: Foreign Aid, Savings and Investment
258 to the estimation problems associated with early studies. The early studies were based
on static cross-country analysis with inappropriate assumptions such as countries are
homogenous with respect to size, factor endowment, openness, economic structure
and institutional quality. Thus, one should address the issue of the impact of foreign
aid on domestic savings and the savings–investment gap in a dynamic framework
using time-series data from individual countries with systematic statistical tests for
nonstationarity and cointegration.
7.3 Theoretical considerations and empirical models
The theoretical rationale for the relationship between aid and the savings–investment
gap lies in the national income identities, where GDP (Y) is divided into four
components of expenditure: consumption (C), investment (I), government purchases
(G) and net exports (NX). Therefore, for an open economy, we have
)1.7...(..................................................MXGICY −+++=
where X – M = net exports (NX)
GDP can also be decomposed as
)2.7.........(............................................................TSCY ++=
where GDP (Y) equals the sum of consumption (C), saving (S) and taxes (T).
From (7.1) and (7.2) we get
,TSCMXGIC ++=−+++
or GTISMX −+−=−
or IGTSMX −−+=− )(
Chapter 7: Foreign Aid, Savings and Investment
259
where S and (T – G) = private and government savings respectively and I =
investment, X = exports, M = imports. Thus, ex-post, the gap between aggregate
domestic saving (private and public) and domestic investment is equal to the gap
between exports and imports.
However, ex-ante, these two gaps may not be equal. Growth potential depends on
whichever gap is the largest. According to the two-gap model, if the foreign exchange
gap (X – M) required to achieve a target rate of growth is greater than the domestic
savings–investment gap, foreign aid is needed to fill the foreign exchange gap.
Similarly, foreign aid is needed to fill the savings–investment gap if it is the larger of
the two gaps.5 In other words, foreign aid is needed to relax the limits to growth. In
the context of Nepal, we are assuming that growth is investment limiting, and that
foreign capital inflows can relax this by supplementing domestic savings. This is in
line with the historical sequence of experience originally suggested by Chenery and
his associates, that is, in the pre-take-off stage a developing country would have a
dominant savings–investment gap, followed by a dominant foreign exchange gap
(Thirlwall, 1999: 368). Foreign capital flows can be foreign direct investment, short-
term portfolio investment and foreign aid. However, in the case of Nepal, foreign
direct and portfolio investments are negligible. Thus, foreign aid (FA) is the only
option for foreign capital inflows (FS). Thus:
)3.7(..................................................eDSFAI ++=
5 Here we are referring to gaps produced by the savings or exports required for the planned investment or importation of capital goods to achieve a target growth rate. In this case, the gaps are (a) savings–investment gap = s*Y – sY, where s* is the target savings rate and s is the actual savings rate; (b) foreign exchange gap = m*Y – mY, where m* is the target import rate and m is the actual import rate, permitted by export earnings.
Chapter 7: Foreign Aid, Savings and Investment
260 where FA is foreign aid and DS is total domestic savings (private + public) and the
term (e) captures the impact of any other financial flows on investment. It also
captures net income (primary and secondary) from abroad.
7.3.1 Empirical models
One can test the two-gap model or the effectiveness of aid in filling the gap by
directly estimating equation (7.3) if the term e is not observable. However, if e is not
negligible as in the case of Nepal, the direct estimation of equation (7.3) using current
period data will not produce any meaningful results. In Nepal, workers’ remittance
(included in e) is an important source of foreign exchange and is close to 2 per cent of
GDP. As a matter of fact, critics argue that findings of many earlier studies were
misleading as they were merely estimating an identity.
Therefore, we can postulate a behavioural relationship between IR, SR and AR. We
hypothesise that savings positively affects investment. This follows from the loanable
fund theory; that is higher the savings, lower is the cost of borrowings and hence
higher will be the rate of investment.6 Aid can also positively affect the investment
rate due to complementarities between private investment and aid funded public
projects such infrastructure, education and health. Therefore, we use a Cobb-Douglas
type relationship as follows:
)4.7....(............................................................).........( 32 ααβ ttt ARSRIR =
6 However, if one uses an acceleration type model, then higher savings may reduce investment due to a deficiency in aggregate demand.
Chapter 7: Foreign Aid, Savings and Investment
261 where β represents institutional and regulatory factors that affect IR, and α2 and α3
are elasticities of IR with respect to AR and SR, respectively.
Taking natural logarithms on both sides of equation (7.4), we obtain,
)5.7......(..............................lnlnln 1321 tttt uARSRIR +++= ααα
where lnβ = α1 and IR, SR and AR are ratios to GDP respectively. A positive
coefficient of AR would indicate that aid relaxes the investment limit to growth.
We first begin our empirical work with the estimation of a simple investment-savings
relationship:
)6.7.....(..................................................lnln 221 ttt uSRIR ++= ββ
where IR is the ratio of gross domestic investment to GDP and SR is the
corresponding ratio of gross domestic savings to GDP. If the value of β2 is close to 1,
it would indicate that the entire source of finance of domestic investment is domestic
savings. That is, FA = 0 in equation (7.3). This will support Feldstein-Horioka (1980)
hypothesis. On the other hand, a value of β2 equal to 0 would mean that capital is
perfectly mobile and foreign capital (which in this case is foreign aid) is a perfect
substitute for domestic savings. That is, DS = 0 in equation (7.3). This will support
the extreme case of Griffin-Enos hypothesis. A value of β2 between zero and 1 would
mean both foreign aid and domestic savings contribute to investment.
Chapter 7: Foreign Aid, Savings and Investment
262 Next we directly examine the relationship between domestic savings and foreign aid.
In particular, we want to see whether aid supplements or substitutes domestic savings.
For this we estimate the following equation:
)7.7...(..................................................lnln 31211 ttt uARSR ++= ββ
where β11 is the average saving rate, AR is a ratio of aid to GDP and β12 captures the
impact of aid on the saving rate. If β12 > 0, aid supplements domestic savings;
if β12 < 0, aid substitutes domestic savings.
We also estimate the relationship between aid and investment as
)8.7...(..................................................lnln 42221 ttt uARIR ++= ββ
Finally, we examine the role of aid in augmenting investment rate by estimating
equation (7.4).
7.3.2 Data and methodology
In this chapter, we use annual time-series data from 1970 to 2002 for Nepal. Data on
GDP, investment, and savings are obtained from the IMF, International Financial
Statistics (IFS) online database. Data on aid flows are obtained from the OECD,
International Development Statistics (IDS) online database.
Chapter 7: Foreign Aid, Savings and Investment
263 We use gross fixed capital formation as a measure of investment and gross domestic
savings as a measure of savings. We have converted aid data into national currency
using nominal exchange rate and transformed all variables into percentage of GDP.
Table 7.2: Correlation matrix in growth, 1970-2002 Variables ARgr SRgr IRgr
ARgr 1.00 SRgr 0.17 1.00 IRgr 0.13 0.84 1.00
Note: SR = savings/GDP, IR = investment/GDP,
AR = aid/GDP, “gr” stands for growth rate
The correlation matrix shows a very strong positive association between savings and
investment rates (Table 7.2). Growth of aid/GDP ratio has a positive relationship with
the growth of both saving and investment rates. This implies that aid is positively
contributing to both savings and investment rates. Interestingly, the sum of partial
correlation coefficients of investment growth with savings and aid growth is close to
one, confirming the nature of identity as in equation (7.3). However, the partial
correlation coefficient with savings growth is much higher than that with aid growth.
This implies that savings play a more important role than aid in augmenting
investment.
Chapter 7: Foreign Aid, Savings and Investment
264 Figure 7.1: Trends of investment rate (IR) and saving rate (SR), 1970-2002
0
5
10
15
20
25
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
S RIR
Source: IMF/IFS online database Figure 7.2: Trends of aid/GDP ratio (AR) and GAP (= SR–IR), 1970-2002
-12
-8
-4
0
4
8
12
16
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
GAP (SR-IR)AR
Source: IMF/IFS and OECD/IDS online databases
Figures 7.1 and 7.2 present trends of variables under study. It shows that throughout
the 1970s, the GAP (=SR–IR) remained relatively small; on average it was less than 4
per cent of GDP. However, from the early 1980s to the late 1990s, the GAP on
average increased to over 7 per cent of GDP, and slightly decreased in 2000. When
we compare the trends in the aid/GDP ratio and GAP, Figure 7.2 indicates that on
average the aid/GDP ratio is larger than the GAP. This suggests that aid was either
misused or used for purposes other than investment, such as diaster relief and debt
repayments.
Chapter 7: Foreign Aid, Savings and Investment
265 7.4 Unit root tests
Since we are employing the cointegration test as our estimation procedure, we
perform first unit root tests to ensure that all variables are I(1). As in the previous
chapter, in order to test for the stationarity, both the ADF and PP tests are used. The
results of both tests on the levels and first difference of the variables are presented in
Tables 7.3 and 7.4. We have fixed the lag length of 2 based on AIC. The top section
of each Table shows the results with a constant only, while the bottom section shows
the results with a constant and a time trend.
Table 7.3: ADF test (Lag = 2), 1970-2002 ADF test With constant only Variables Levels First difference10% critical value5% critical value 1% critical value
lnAR -2.07 -2.23 -2.63 -2.96 -3.67
lnSR -2.63 -3.75* -2.63 -2.96 -3.67
lnIR -3.59** -2.27 -2.63 -2.96 -3.67 With constant and time trend Variables Levels First difference10% critical value5% critical value 1% critical value
lnAR -0.31 -2.97 -3.21 -3.56 -4.29
lnSR -2.64 -3.95** -3.21 -3.56 -4.29
lnIR -2.79 -2.79 -3.21 -3.56 -4.29 Note: *, ** and *** indicate significant at 1%, 5% and 10% levels respectively.
The ADF results under the assumption of constant only indicate that lnSR is
nonstationary in its level form but stationary in its first difference form at the 1 per
cent significant level. Similarly, under the assumption of constant and time trend, the
results show that lnSR is nonstationary in its level form and stationary in the first
Chapter 7: Foreign Aid, Savings and Investment
266 difference form at the 5 per cent significant level. On the other hand, the ADF test
results for lnIR under the assumption of constant only indicate that it is stationary in
its level form, while with a constant and a time trend the results show that InIR is
nonstationary in both level and first difference forms. lnAR is nonstationary in both
assumptions even in its first difference form.
When we performed the PP test, the results under the assumption of constant only
indicate that lnSR and lnIR are stationary in their level forms, while lnAR is
stationary in the first difference form at one per cent significant level. However, under
the assumption of a constant and a time trend, all variables are nonstationary in their
level forms and stationary in their first difference forms at the one per cent significant
level. Thus, these variables are fit for cointegration testing. That is, they are I(1)
variables as required by theory.
Table 7.4: PP test (Lag = 2), 1970-2002 PP test With constant only Variables Levels First difference10% critical value5% critical value 1% critical value
lnAR -1.95 -6.57* -2.63 -2.96 -3.67
lnSR -3.73* -6.77* -2.63 -2.96 -3.67
lnIR -3.84* -7.61* -2.63 -2.96 -3.67 With constant and time trend Variables Levels First difference10% critical value5% critical value 1% critical value
lnAR -0.52 -7.88* -3.21 -3.56 -4.29
lnSR -3.52 -6.96* -3.21 -3.56 -4.29
lnIR -2.54 -9.03* -3.21 -3.56 -4.29 Note: *, ** and *** indicate significant at 1%, 5% and 10% levels respectively.
Chapter 7: Foreign Aid, Savings and Investment
267 7.5 Empirical results and their interpretations
For the two variable relationships, we first perform a residuals based approach to test
for cointegration, as proposed by Engle and Granger (1987). We have chosen 5 for the
maximum order of the ADF statistics. The results are presented in Table 7.5. Using
the ADF test, residuals from the regression between lnIR and lnSR are found to be
nonstationary even at the 10 per cent significant level (Part A of Table 7.5).
According to the theory, if the residual is I(1) the regression between lnIR and lnSR is
not a cointegrating regression. In other words, the relation between lnIR and lnSR
obtained from the OLS is spurious.
Table 7.5: ADF test for residuals for testing cointegration, 1970-2002 Part A: Residuals between lnIR and lnSR Critical value Critical value ADF (1) ADF (2) ADF (3) ADF (4) ADF (5) 5% 10% Test statistics -2.48 -2.43 -1.96 -1.18 -1.94 -3.58 -3.22 Part B: Residuals between lnIR and lnAR Critical value Critical value ADF (1) ADF (2) ADF (3) ADF (4) ADF (5) 5% 10% Test statistics -1.63 -1.59 -2.18 -1.43 -1.05 -3.58 -3.22 Part C: Residuals between lnSR and lnAR Critical value Critical value ADF (1) ADF (2) ADF (3) ADF (4) ADF (5) 5% 10% Test statistics -1.89 -1.96 -2.25 -1.93 -1.4 -3.58 -3.22
Similarly, residuals from the regression equation between lnIR and lnAR are found to
be nonstationary; hence they are not cointegrated (Part B). We find the same results
for the residuals between lnSR and lnAR; that is, they are not cointegrated (Part C).
Chapter 7: Foreign Aid, Savings and Investment
268 Since the residuals-based cointegration test is not found to be conclusive, we further
extend our test for cointegration using Johansen’s Maximum Likelihood test, which is
considered more efficient for the estimation.7
We first focus our empirical investigation on the savings-investment relationship
(equation 7.6). As noted in chapter 5, we select the optimal lag length of 3, based on
the AIC and SBC. The results show that the variables are cointegrated (Table 7.6).
The long-run normalised coefficient of savings rate is found to be positive but
insignificant.
Table 7.6: Estimates of Johansen’s Likelihood Ratio test, 1970-2002 (equation (7.6), lnIR and lnSR) VAR (3) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.45751 r = 0 r = 1 18.34*** 25.01*** 0.19919 r <= 1 r = 2 6.66 6.66 Long-run cointegrating normalised coefficients
Variables lnIRt lnSRt Trend Coefficients 1.000 -0.109 -0.006 Chi Square [0.08] [0.46] Notes: (a) *** indicates significant at 10% level.
(b) Figures within the third brackets represent Chi Square.
According to the Feldstein and Horioka (1980) model, the low coefficient, estimated
at 0.10, is evidence in favor of international capital mobility (see also Leachman,
1991; Argimon and Roldan, 1994). In precise terms, in the case of Nepal, it implies
that most investment is financed by other sources such as foreign aid. In the first Five
7 See chapter 5 for detailed discussion of the cointegration test.
Chapter 7: Foreign Aid, Savings and Investment
269 Year Plan (1956-1960), foreign aid was used to finance almost 100 per cent of
development expenditure. In recent years, aid is still used to finance over 50 per cent
of development expenditure (see Paudyal, 2003).
Next, we look at the relationship between foreign aid and investment (equation 7.8).
The results indicate that the variables are cointegrated (Table 7.7). The long-run
coefficient of aid is found to be positive and statistically significant at the 1 per cent
level. Thus, foreign aid has been contributing to financing investment. Once again,
this result confirms the positive association between aid and investment, and our
result is consistent with the Feldstein and Horioka interpretation.
Table 7.7: Estimates of Johansen’s Likelihood Ratio test, 1970-2002 (equation (7.8), lnIR and lnAR) VAR (4) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.48970 r = 0 r = 1 19.50** 28.49** 0.26650 r <= 1 r = 2 8.98 8.98 Long-run cointegrating normalised coefficients
Variables lnIRt lnARt Trend Coefficients 1.000 -0.284 -0.015 Chi Square [5.63]* [11.69]* Notes: (a) * and ** indicate significant at 1% and 5% levels respectively.
(b) Figures within the 3rd brackets represent Chi Square
Next, we investigate the relationship between domestic savings and foreign aid,
equation (7.7). The test results show that only the trace test is significant at the 10 per
cent level. The results are presented in Table 7.8. The coefficient of aid is found to be
positive but it is statistically insignificant.
Chapter 7: Foreign Aid, Savings and Investment
270 Table 7.8: Estimates of Johansen’s Likelihood Ratio test, 1970-2002 (equation (7.7), lnSR and lnAR) VAR (2) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.41811 r = 0 r = 1 15.80 25.29*** 0.26560 r <= 1 r = 2 9.49 9.49 Long-run cointegrating normalised coefficients
Variables lnSRt lnARt Trend Coefficients 1.000 -0.153 -0.050 Chi Square [0.50] [5.96]* Notes: (a) * and *** indicate significant at 1% and 10% levels respectively.
(b) Figures within the 3rd brackets represent Chi Square
Finally, we investigate the influence of savings and aid on investment (equation 7.4).
The results show that the variables under study are cointegrated (Table 7.9).
Table 7.9: Estimates of Johansen’s Likelihood Ratio test, 1970-2002 (equation (7.4), lnIR, lnSR and lnAR) VAR (3) Hypothesis LR test based on Eigenvalues Null Alternative λmax λtrace 0.65298 r = 0 r = 1 31.75** 56.23** 0.41119 r <= 1 r = 2 15.88 24.48*** 0.24918 r <= 2 r = 3 8.59 8.59
Long-run cointegrating normalised coefficients
Variables lnIRt lnSRt lnARt Trend Coefficients 1.000 -0.711 -0.254 0.013 Chi Square [17.11]* [14.58]* [5.92]** Notes: (a) *, ** and *** indicate significant at 1%, 5% and 10% levels respectively.
(b) Figures within the 3rd brackets represent Chi Square
The long-run cointegrating normalised coefficients show that both savings and aid
have a positive and statistically significant (at 1 per cent) relationship with investment
in the long-run. The elasticity of investment with respect to savings, estimated at 0.71,
Chapter 7: Foreign Aid, Savings and Investment
271 is quite high; it was found to be only 0.109 in the absence of aid (Table 7.6). Thus,
we can conclude that domestic savings play a more important role than foreign aid.
7.5.1 Granger causality test results
In the previous section, the residuals based tests showed that the variables under study
are not cointegrated. Furthermore, the Johansen tests revealed that they are
cointegrated mostly at only the 10 per cent level, which may be considered weak
evidence. Thus, we find it necessary to perform the bivariate Granger causality test
among the variables. It is worth mentioning that very few attempts have been made to
address the issue of a causal relationship between aid and savings (see Bowles, 1980
and Hasan, 2002). Thus, we examine the directions and patterns of the causal
relationships between aid, savings and investment by performing the bivariate
Granger causality test.
The empirical evidence of a negative aid–savings relationship suggests several
possible hypotheses. First, the “dependency hypothesis” posits that foreign aid causes
lower domestic savings (Griffin and Enos, 1970). Second, the reverse causality
hypothesis implies that countries with lower savings rates and unfavorable economic
conditions receive more foreign aid on the basis of their needs (Papanek, 1972, 1973).
Finally, the hypothesis of the feedback effect states that high inflows of aid cause low
domestic savings and low domestic savings attract high inflows of aid.
On the other hand, foreign aid and domestic saving may be independent of each other.
It is possible to argue that foreign aid depends on donors’ interests and exogenous
Chapter 7: Foreign Aid, Savings and Investment
272 decisions, whereas domestic savings depends on income level along with other
domestic factors such as credit policy and financial deepening. Therefore, aid inflows
and domestic savings may not be correlated.
Since the causality test results are sensitive to the choice of the lag length, we have
used three different lag lengths, 2, 3 and 4, for all variables in each equation. The null
hypothesis in each case is that the variable under consideration does not “Granger
cause” the other variable. The causality test results are presented in Table 7.10.
Table 7.10: Bivariate Granger causality test results, 1970-2002
Causality results CHSQ, Lag = 2
CHSQ, Lag = 3
CHSQ, Lag = 4
DlnIR ⇒ DlnSR 17.26* 16.24* 13.41* DlnSR ⇒ DlnIR 4.89*** 8.08** 8.70** DlnSR ⇒ DlnAR 7.07** 19.35* 25.47* DlnAR ⇒ DlnSR 5.87** 6.17 4.97 Notes: (a) All variables are in natural logarithm8 and Dln stands for change.
(b) CHSQ stands for Chi Square (c) *, ** and *** indicate 1%, 5% and 10% significant levels respectively.
The results indicate that there exists bidirectional (feedback) causality between
changes in investment rate (IR) and savings rate (SR) in all three different lag lengths,
that is, IR ⇔ SR. Consistent with theory; savings cause an increase in investment,
which causes income to rise and hence savings. Investment also increases savings
directly, without an intervening increase in income. This happens through inflationary
financing and is known as forced savings (see Kalecki, 1976).
8 As we have transformed the variables in natural logarithm, we have used Chi Square instead of F-test, which is considered more efficient.
Chapter 7: Foreign Aid, Savings and Investment
273 We also find unidirectional causality from savings rate (SR) to aid flows (AR),
consistent with some of the early studies. As mentioned earlier, Papanek (1972, 1973)
and Kennedy and Thirlwall (1971) argued that developing countries with a low
savings rate receive more aid on the basis of their needs. That is, countries with low
savings receive a higher amount of aid. It is also argued that aid is given in proportion
to the extent of poverty and other crises in the recipient country as measured by the
level and growth of income. On the other hand, the Chi Square statistics shows that
reverse causality from aid to savings does not exist when lag lengths 3 and 4 are
considered. This casts doubt on Griffin and Enos’ (1970) hypothesis that aid inflows
cause lower domestic savings.
7.5.2 Generalised impulse response analysis
Having examined the relationship between aid, savings and investment, we proceed to
examine certain dynamic properties by simulating the response of each variable to
exogenous shocks in other variables. That is, we analyse the time profile of the effect
of shocks at a given point in time from one variable to another. This is done by using
the generalised impulse response function (see further chapter 5). Specifically,
variables are given shocks of one standard error (SE) and the impulse response
functions are obtained from the cointegrating relations. Thus we analyse these
variables in the context of the VAR (3) model with the assumption of unrestricted
intercepts and restricted trend coefficients. As all variables are found to be I(1), we
have used their first difference forms (D stands for first difference) for the impulse
response analysis and all variables are in natural logarithm. The results are presented
in Figures 7.3 to7.10, for horizon of 14-year period.
Chapter 7: Foreign Aid, Savings and Investment
274
Figure 7.3: Generalised impulse response of DlnSR
to one S.E. shock in DlnIR
DlnIR
DlnSR
Horizon
-0.05
-0.10
0.00
0.05
0.10
0.15
0.20
0 2 4 6 8 10 12 14
Figure 7.3 shows the impulse response of savings (DlnSR) to investment (DlnIR). At
the beginning, the shocks have larger effects, almost a 15 per cent rise in savings, but
it dies out quickly by about a four-year period. The feedback response of investment
(via the rise in savings) to the initial shock to investment itself is less than the
response of savings, implying that the system converges to equilibrium. Figure 7.4
shows the response of investment to one SE shock to savings. Investment increases
immediately by about 8 per cent, and the impact dies out by about the 7th year.
Chapter 7: Foreign Aid, Savings and Investment
275
Figure 7.4: Generalised impulse response of DlnIR
to one S.E. shock in DlnSR
DlnIR
DlnSR
Horizon
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0 2 4 6 8 10 12 14
Figure 7.5: Generalised impulse response of DlnAR
to one S.E. shock in DlnIR
DlnIR
DlnAR
Horizon
-0.05
-0.10
0.00
0.05
0.10
0.15
0 2 4 6 8 10 12 14
The impulse response of aid (DlnAR) to investment (DlnIR) is presented in Figure
7.5. Until about second year, there is a mismatch between the response of aid and that
of investment to the initial shock to investment. After that aid response follows the
pattern of investment response, but aid overshoots investment. The feedback
responses die out by about the sixth year. Figure 7.6 demonstrates that the initial
response of investment to shocks to aid flows is negative, and in the subsequent years
the response is not very pronounced. This may be due to Nepal’s weak absorptive
capacity.
Chapter 7: Foreign Aid, Savings and Investment
276 Figure 7.6: Generalised impulse response of DlnIR
to one S.E. shock in DlnAR
DlnIR
DlnAR
Horizon
-0.05
0.00
0.05
0.10
0.15
0.20
0 2 4 6 8 10 12 14
Figure 7.7: Generalised impulse response of DlnAR
to one S.E. shock in DlnSR
DlnSR
DlnAR
Horizon
-0.05 -0.10 -0.15
0.00 0.05 0.10 0.15 0.20 0.25
0 2 4 6 8 10 12 14
Figure 7.7 shows the shocks response of aid to savings. The shock response of savings
and aid’s response are very similar to the response of investment to the initial shock to
aid flows. The impulse response of aid to savings (Figure 7.8) is also very similar to
aid’s response to investment shocks.
Chapter 7: Foreign Aid, Savings and Investment
277
Figure 7.8: Generalised impulse response of DlnSR
to one S.E. shock in DlnAR
DlnSR
DlnAR
Horizon
-0.05
-0.10
-0.15
0.00
0.05
0.10
0.15
0 2 4 6 8 10 12 14
Figure 7.9 shows the responses of savings and aid to a one SE shock to investment.
The response to savings is larger than that of aid. This implies that although aid flows
respond to increased investment, domestic savings is the dominant source of
financing. Figure 7.10 shows the response of savings and investment to a one SE
shock to aid flows. We find that the initial impact is a drop in both savings and
investment, but after that both continue to rise and the impacts die out by the fourth
year.
Figure 7.9: Generalised impulse responses of DlnSR and DlnAR
to one S.E. shock in DlnIR
DlnIR
DlnSR
DlnAR
Horizon
-0.05
-0.10
0.00
0.05
0.10
0.15
0 2 4 6 8 10 12 14
Chapter 7: Foreign Aid, Savings and Investment
278
Figure 7.10: Generalised impulse responses of DlnSR and DlnIR
to one S.E. shock in DlnAR
DlnIR
DlnSR
DlnAR
Horizon
-0.05
-0.10
-0.15
0.00
0.05
0.10
0.15
0 2 4 6 8 10 12 14
7.6 Summary and conclusion
In this chapter, we have made an attempt to shed light on the issue of aid and the
savings–investment gap in Nepal. The cointegration results indicate that there exists a
weak long-run relationship between domestic savings and investment. This implies
that foreign aid has been an additional source of financing investment. This result is
further confirmed by the positive association between aid and investment.
The bivariate Granger causality tests results show that there is bidirectional causality
between changes in domestic savings and investment. While there exists
unidirectional causality from changes in savings to changes in foreign aid, we do not
find support for the reverse causality from aid to savings. Hence, our results are
consistent with the hypothesis that aid is given based primarily on recipients’
investment needs, as reflected by their low savings rates.
Chapter 7: Foreign Aid, Savings and Investment
279 We have also analysed impulse response functions among variables. In most cases,
the responses die out by 6-7 years. We also find that the domestic savings response is
larger than the aid response to shocks in investment, showing the importance of
domestic financing of investment.
Chapter 8
Foreign Aid and Government’s Fiscal Behaviour
“The magnitude of fungibility depends on a country’s budgetary structures, the degree to which governments are able to manage their finances and the extent of donor involvement…… What really matters in evaluating the effect of aid, however, is what the government does with the resources it otherwise would have devoted to the project. It could do the next best project not yet financed…or could choose to do a white elephant project with political payoffs but with a return to the economy of zero” (World Bank, 1998: 70-73).
8.1 Introduction
In the previous two chapters we investigated aid–growth, aid–savings and aid–
investment relationships. In particular, we evaluated aid effectiveness in terms of its
association with per capita real GDP and the savings–investment gap. The aid–growth
relationship was first assumed to work through technological progress via aid’s
favourable effects on technical knowledge. Aid’s contribution to growth was then
analysed through its effect on capital accumulation, in particular, the savings–
investment gap.
One of the deficiencies of studies of aid–growth and/ or aid and savings–investment
gap relationships is that they fail to explicitly recognise that aid is given primarily to
the government. Thus any impact of aid on the economy will depend on government
behaviour. Furthermore, the government’s financial (budgetary) position is a major
determinant of domestic savings.
Table 8.1 presents a comparison between Nepal and three South Asian countries
(India, Pakistan and Sri Lanka) in terms of government revenue and expenditures and
aid. On an average Sri Lanka has the highest revenue/GDP and expenditure/GDP
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
281
ratios, followed by Pakistan, during the period 1975-01. Nepal’s revenue and
expenditure as percentages of GDP are the lowest among the South Asian countries.1
However, Nepal received higher aid as a percentage of GDP compared to other South
Asian countries. The higher flows of aid perhaps contributed to lower public sector
borrowing in Nepal.
Table 8.1: Government revenue and expenditure for South Asian countries, as percentage of GDP, 1975-2001 Country/Year Aid/GDP Revenue/GDPBorrowing/GDP Total expenditure/GDP
Nepal 1975-84 6.93 7.94 1.69 15.04 1985-94 12.25 9.19 1.89 18.28 1995-01 8.68 11.18 1.21 18.22 India
1975-84 1.19 12.37 5.07 13.47 1985-94 1.24 13.30 6.48 16.31 1995-01 0.75 12.49 4.98 15.6 Pakistan 1975-84 4.38 15.14 4.52 18.17 1985-94 4.27 17.65 5.71 23.17 1995-01 2.59 16.41 4.47 22.46
Sri Lanka 1975-84 8.36 19.96 6.29 31.84 1985-94 8.21 20.51 5.46 29.72 1995-01 3.05 18.01 6.70 26.22
Note: Bangladesh is not included due to non-availability of data. Source: IMF/IFS online database and Statistical Year Book of Nepal, 1995 and 2003
This chapter examines the impact of aid on the fiscal (revenue and expenditure)
behaviour of the Nepalese government. Particularly, we look at the following
relationships: (a) aid and government’s development and non-development
expenditure; and (b) aid and revenue. The chapter is organised as follows. The next
section provides a graphical exposition of aid and fiscal behaviour. Section 8.3
presents the model, data and methodological procedures. The empirical results and
1 See chapter 2 on the trends in and patterns of revenue in Nepal. Pervasive corruption, a narrow tax structure and inefficient tax administration have been major obstacles to revenue collection in Nepal.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
282
analyses are reported in section 8.4. The final section provides summary and
conclusion.
8.2 Fiscal response models
The issue of fiscal response has been addressed in the literature through two different
approaches. The first approach follows the model developed by McGuire (1978), and
is concerned with the question of aid fungibility. Aid is said to be fungible if the
recipient uses aid for purposes other than those intended by the donors. The
assumption is that donors intend aid flows to finance specific activities; the question
is whether the flows are diverted to other purposes. In other words, if aid intended for
investment is actually diverted to government consumption spending, then the
potential growth impact of aid may be reduced.2 Generally, government investment
spending is considered to make a greater contribution to growth than government
consumption spending. Thus, aid should not to be diverted to consumption spending.
Studies of this approach are Khilji and Zampelli (1991), Pack and Pack (1990, 1993),
Feyzioglu et al. (1998), and Swaroop et al. (2000).
The second type of model, based on the seminal work of Heller (1975), assumes
utility-maximising behaviour for the government, and examines the pattern of
different components of government expenditure when it is faced with a budget
constraint which is defined by revenue, borrowings and aid. To this end, governments
set targets for various expenditures and also set revenue targets for tax and borrowing.
2 Even if aid is used in the intended manner, it allows the government to increase its consumption expenditure or fund other projects, which may not be so productive. In that case, too, aid effectiveness will be low.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
283
Then, they maximise their goal (economic growth or social welfare) by attaining these
revenue and expenditure targets. The assumption here is that the realisation of
revenue and expenditure targets maximises the goals. The flow of aid can change
either government’s expenditure targets or revenue/borrowing targets. Government
can also adjust its both expenditure and revenue/borrowing targets in response to aid.
In formulating our empirical model, we follow the work of Pack and Pack (1990,
1993) and Feyzioglu et al. (1998), which use a McGuire type theoretical framework.
The reason for using this type of specification is that it does not suffer from the
methodological problems of Heller type models. As White (1994) has pointed out, the
Heller type models suffer from important estimation problems. These arise from the
fact that the Heller type models use target variables in the utility function of the
government. If the available revenue (aid plus domestic revenue) fails to meet the
target expenditure, then utility is not maximised. However, target variables are not
observable and hence need to be estimated. The targets are taken to be the fitted
values from the regression equations linking target variables to their past values and
some plausible exogenous factors. White (1994) expressed doubts about whether
target values thus derived through estimation would necessarily be equal to the values
of target variables derived from the optimisation exercise. If the target value is very
close to the actual value then one would be regressing the variable on itself, producing
R2 which will be very close to 1. On the other hand, if the R2 is low, it would be very
difficult to see how the fitted values calculated using the estimated coefficients may
be meaningfully interpreted as the values of the targets. Thus, White (1994: 159)
notes: “the fit will be poor either because the wrong variables have been included in
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
284
the target equation, or because the outturn was far removed from the target. In the
later case, the coefficients will not be those used in the formation of targets”.
On the other hand, Pack and Pack (1990, 1993) and Feyzioglu et al. (1998) specify
various types of government expenditure and revenue as functions of GDP and some
plausible variables, all of which are observable. Hence these models do not need any
estimated variables such as targets as in the Heller type models. Pack and Pack and
Feyzioglu et al. used a standard utility function involving public goods to be
maximised subject to the government budget constraint.
Therefore, following Pack and Pack (1990, 1993) and Feyzioglu et al. (1998), we
examine the relationship between aid and three different categories of government
revenue and expenditures in Nepal as follows:
)1.8......(........................................87lnlnln 2222120 tttd uDAIDGDPPG
t++++= λλλ
)2.8.....(........................................87lnlnln 3323130 tttnd uDAIDGDPPGt
++++= λλλ
)3.8...(........................................87lnlnln 4424140 tttt uDAIDGDPPREV ++++= λλλ
where Gd = per capita development expenditure, Gnd = per capita non-development
expenditure or current expenditure, Rev = per capita government revenue (tax plus
non-tax), AID = per capita aid and GDPP = per capita GDP. ln = natural logarithm.
All variables are expressed in current prices.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
285
D87 is a dummy variable (= 0 for 1975-86 and 1 for 1987-02). The dummy captures
the impact of Structural Adjustment Programs, which have important bearings on
government expenditure and revenue. In particular, the IMF-World Bank supported
Structural Adjustment Program (signed by Nepal in 1987) requires revenue effort to
increase and expenditure to be contained or cut in order to achieve a sustainable
budget outcome.
8.3.1 Data and summary statistics of the variables
We have used time-series data from 1975 to 2002; no reliable data prior to this period
are available. Government revenue and expenditure data are obtained from the Central
Bureau of Statistics (CBS) publication, Statistical Year Book of Nepal (1981, 1982,
1991, 1999, and 2003). Foreign aid data are obtained from the OECD publication,
IDS online database. For the model estimation, all variables are expressed as per
capita form at current prices and transformed into natural logarithm.3 Table 8.2
presents the correlation among model variables. As can be seen, all variables are
highly correlated, indicating that our model relating them is highly plausible. We also
find that aid growth correlates highly with the growth of both development and non-
development expenditure as well as with the growth of revenue (Table 8.2A).
3 Since AID is in per capita form, the notation is different than previous chapters (AR).
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
286
Table 8.2: Correlation matrix of model variables, 1975-2002
Variables GDPP AID REV Gd Gnd GDPP 1.00 AID 0.93 1.00 REV 0.98 0.90 1.00 Gd 0.97 0.98 0.95 1.00 Gnd 0.98 0.87 0.99 0.92 1.00
Table 8.2A: Correlation matrix of variables, 1975-2002 Variables AIDgr Gdgr Gndgr REVgr
AIDgr 1.00 Gdgr 0.37 1.00 Gndgr 0.28 0.06 1.00 REVgr 0.21 0.01 0.38 1.00
Notes: (a) All variables are expressed as a percentage of GDP.
(b) “gr” stands for growth.
8.4 Unit root tests
Since we are using cointegration tests to examine the relationship between aid and
various components of government revenue and expenditure, it is necessary to ensure
that all variables under study are of the same order. In other words, the standard
cointegration analysis requires the classification of the variables into I(1), that is, they
need to be nonstationary. In order to test for stationarity in the next step, therefore, we
perform ADF, and PP unit root tests.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
287
Table 8.3: ADF test with constant only (Lag = 2), 1975-2002
ADF test with constant only Critical values Variables Levels First difference 10% 5% 1% lnGDPP 1.94 -2.70*** -2.62 -2.97 -3.69 lnAID -2.69*** -1.05 -2.62 -2.97 -3.69 lnGd -2.60 -2.05 -2.62 -2.97 -3.69 lnGnd 0.03 -2.85*** -2.62 -2.97 -3.69 lnREV -0.81 -2.38 -2.62 -2.97 -3.69 Notes: (a) *** indicates significant at 10% level.
(b) All variables are expressed in natural logarithm form.
Table 8.3A: ADF test with constant and trend (Lag = 2), 1975-2002 ADF test with constant and trend Critical values Variables Levels First difference 10% 5% 1% lnGDPP -2.46 -3.52*** -3.22 -3.58 -4.32 lnAID -0.17 -2.30 -3.22 -3.58 -4.32 lnGd -0.24 -3.67** -3.22 -3.58 -4.32 lnGnd -2.41 -2.79 -3.22 -3.58 -4.32 lnREV -1.22 -2.36 -3.22 -3.58 -4.32 Note: ** and *** indicate significant at 5% and 10% levels respectively.
The ADF test results are presented in Tables 8.3 and 8.3A. The results show that only
two variables, lnGDPP and lnGnd, are found to be stationary at the 10 per cent
significant level in their first difference form with the assumption of a constant only.
On the other hand, only lnGDPP and lnGd are found to be stationary at the 10 and 5
per cent significant levels, respectively, with the assumption of a constant and trend.
Thus, a unit root problem exists even in their first difference form for lnAID, lnGnd
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
288
and lnREV with the assumption of a constant and a time trend; thus they are
nonstationary under the ADF test results.
Table 8.4: PP test with constant only (Lag = 2), 1975-2002 PP test with constant only Critical values Variables Levels First difference 10% 5% 1% lnGDPP 1.36 -7.41* -2.62 -2.97 -3.69 lnAID -3.89* -5.60* -2.62 -2.97 -3.69 lnGd -3.35** -3.95* -2.62 -2.97 -3.69 lnGnd -0.45 -7.17* -2.62 -2.97 -3.69 lnREV -0.74 -4.88* -2.62 -2.97 -3.69 Note: * and ** indicate significant at 1% and 5% levels respectively.
Since the ADF tests indicate inconclusive results, we perform the PP unit root test; the
results are presented in Tables 8.4 and 8.4A. As with the ADF test, we have fixed lag
lengths of 2 based on the AIC. Almost all variables have a unit root problem in their
level form both with a constant, and with a constant and a time trend assumptions.
However, they are found to be stationary in their first difference form at the one per
cent significant level. Thus, under both assumptions of a constant only and a constant
with a trend, the variables can be considered nonstationary in their level and
stationary in their first difference forms.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
289
Table 8.4A: PP test with constant and time trend (Lag = 2), 1975-2002
PP test with constant and time trend Critical values Variables Levels First difference 10% 5% 1% lnGDPP -2.41 -8.61* -3.22 -3.58 -4.32 lnAID -0.40 -8.35* -3.22 -3.58 -4.32 lnGd -0.05 -5.23* -3.22 -3.58 -4.32 lnGnd -3.09 -7.01* -3.22 -3.58 -4.32 lnREV -1.65 -4.86* -3.22 -3.58 -4.32 Note: * indicates significant at 1% level.
8.5 Cointegration test results
As the variables under study are found to be I(1), we proceed to perform cointegration
tests by applying Johansen’s Maximum Likelihood approach. We begin with equation
(8.1) relating development expenditure to aid and per capita GDP. As in the other
chapters, prior to testing for the cointegrating vectors, lag length of the vector
autoregressive system is determined by using the SBC and AIC. The λmax and λtrace
statistics are reported in Table 8.5 (Part A). The test results show that there is a
significant long-run relationship between aid and development expenditure.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
290
Table 8.5: Cointegrating test results, 1975-2002
(equation (8.1), lnGd, lnGDPP and lnAID), Part A
VAR (3) Hypothesis Eigenvalues H0 H1 λmax λtrace
0.86332 r = 0 r = 1 49.75** 64.09** 0.55756 r <= 1 r = 2 20.38** 34.35** 0.42787 r<= 2 r = 3 13.95** 13.95** Normalised cointegrating vectors (normalised on lnGd), Part B
lnGd lnGDPP lnAID Trend
1.000 -0.397 -0.111 -0.049
Chi Square [8.56]* [5.15]** [11.87]* Note: * and ** indicate significant at 1% and 5% levels respectively.
The normalised cointegrating vectors are presented in Part B. The results show that
per capita development expenditure is positively associated with both per capita aid
and per capita GDP in the long-run. The long-run aid coefficient is significant at the 5
per cent level, but the elasticity of per capita development expenditure with respect to
per capita aid is quite low (0.11). The estimation of equation (8.1) with a dummy for
the Structural Adjustment Program did not change the result significantly, and the
dummy was not found to be significant. This implies that the Structural Adjustment
Program possibly did not affect development expenditure.
Next we estimate equation (8.2) relating per capita non-development expenditure to
per capita GDP (lnGDPP), per capita aid and a dummy (D87). The results (Part A of
Table 8.6) show that the variables under study are cointegrated at the 5 per cent
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
291
significant level. More importantly, there exists a long-run relationship between per
capita aid and per capita non-development expenditure. All the normalised
cointegrating vectors are found to be positive except for dummy (Part B). Because aid
is generally given for development purposes, the positive and significant association
between per capita aid and per capita non-development expenditure may be
considered a diversion of development aid to non-development expenditure. The
significant and negative coefficient for dummy implies that the Structural Adjustment
Program had negative impacts on non-development expenditure. That is, the
conditionality imposed by the World Bank and the IMF through the Structural
Adjustment Program seemed to have been effective in changing the government’s
spending patterns.4
Table 8.6: Cointegrating test results, 1975-2002
(equation (8.2), lnGnd, lnGDPP, lnAID and Dummy (D87)), Part A
VAR (3) Hypothesis Eigenvalues H0 H1 λmax λtrace
0.76756 r = 0 r = 1 36.47** 47.81** 0.33819 r< = 1 r = 2 10.31 11.33 0.03971 r< = 2 r = 3 1.01 1.01 Normalised cointegrating vectors (normalised on lnGnd), Part B
lnGnd lnGDPP lnAID D87 Trend
1.000 -0.221 -0.613 0.423 -0.074
Chi Square [0.56] [18.84]* [17.49]* [27.66]* Notes: (a) * and ** indicate significant at 1% and 5% levels respectively.
(b) Since dummy is placed at Part B for a convenient purpose, the sign of the coefficient is taken as positive in Table, which is actually negative.
4 The government reduced expenditure through the privatisation of public enterprises, which were running with huge losses. The government had already cut subsidies to some enterprises, thus maintaining a low budget deficit and domestic borrowing.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
292
Interestingly, the elasticity of per capita non-development expenditure with respect to
per capita aid is found relatively larger (0.61) than that for development expenditure.
In other words, a 1 per cent increase in per capita aid leads to an approximately 0.6
per cent increase in the per capita non-development expenditure, whereas it leads to
only 0.11 per cent increase in per capita development expenditure (see Table 8.5).
Since aid is generally given for development expenditure, these results indicate the
possibility of diversion of aid to non-development expenditure. As is the case with
other developing countries, diversion of development aid is not a new phenomenon in
Nepal. In practice, due to political reasons, one can find many examples of diversion
of development aid to non-development expenditure.
Table 8.7: Cointegrating test results, 1975-2002
(equation (8.3), lnREV, lnGDPP and lnAID), Part A
VAR (3) Hypothesis Eigenvalues H0 H1 λmax λtrace
0.65678 r = 0 r = 1 26.73** 51.35** 0.41795 r< = 1 r = 2 13.52 24.61*** 0.35827 r< = 2 r = 3 11.08 11.08 Normalised cointegrating vectors (normalised on lnREV), Part B
lnREV lnGDPP lnAID Trend
1.000 -0.123 -0.482 -0.057
Chi Square [10.09]* [12.67]* [15.39]* Note: *, ** and ** indicate significant at 1%, 5% and 10% levels respectively.
Table 8.7 (Part A) presents the results of cointegration between per capita revenue,
per capita GDP and per capita aid. The results show that there is a long-run
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
293
relationship between all three variables. All the long-run normalised coefficients are
found to be positive (Part B). The long-run normalised coefficient of per capita aid is
found to be positive and significant at the one per cent level. A 1 per cent increase in
per capita aid contributes to almost 0.5 per cent increase in per capita revenue. Thus,
the results indicate that aid did not lead to a reduction in revenue raising efforts. This
may be due to the influence of aid (through technical assistance) on improving
administrative and institutional quality.5 The finding of a positive influence of aid on
revenue is contrary to earlier studies such as Heller (1975), Franco-Rodriguez (2000)
and Pack and Pack (1993).
8.6 Impulse response function
To measures the time profile of the effect of shocks at a given point in time on the
expected future values of variables in a dynamic system, we have used the generalised
impulse response function. Here, we present the impulse response analysis of three
variables at a time. As noted earlier, all three variables are in natural logarithms,
measured on a per capita basis. Since all the variables under study are found to be
I(1), we proceed our analysis in the context of a cointegrated VAR(3) model with
unrestricted intercepts and restricted trend coefficients.
5 There has been considerable technical assistance for the preparation and the implementation of VAT, as well as for broadening structural base of the Nepalese taxation system.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
294
Aid and government expenditure
Figures 8.1 to 8.3 indicate the generalised impulse response over a 25-year period.
Figure 8.1A shows the response of per capita GDP (DlnGDPP) and per capita aid
(DlnAID) to once for all one standard error shock to per capita development
expenditure (DlnGd). We find that the shock has a larger and more persistent effect
on per capita development expenditure itself followed by per capita aid. This is quite
expected as development projects are of longer duration and once commenced cannot
be abandoned. The shock response of per capita aid to per capita development
expenditure shows a cyclical pattern over 16 years and then tends to die out.
Interestingly, the shock response of aid flows follows the response pattern of
development expenditure. It implies that the larger the development expenditure, the
larger will be the aid flow.
Figure 8.1A: Generalised impulse response(s) of DlnGDPP and
DlnAID to one S.E. shock inDlnGd
DlnGd
DlnGDPP
DlnAID
Horizon
-0.02 -0.04
0.00 0.02 0.04 0.06 0.08 0.10
0 5 10 15 20 25
Figure 8.1B shows the responses of per capita GDP and per capita development
expenditure to once for all one standard error shock to per capita aid. The effects of
shock to per capita aid decreased from a positive 13 per cent to an almost negative 4
per cent within a one-year period, and responses of aid to a shock to itself die out
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
295
quickly. This implies that changes in aid flows cannot be sustained for long. That is,
aid flows follow an average trend. Once again, we find that responses of development
expenditure to shocks in aid flows follow the same pattern as the responses of aid
itself. This implies a close connection between aid and development expenditure.
Figure 8.1B: Generalised impulse response(s) of DlnGd and
DlnGDPP to one S.E. shock in DlnAID
DlnGd
DlnGDPP
DlnAID
Horizon
-0.05
0.00
0.05
0.10
0.15
0 5 10 15 20 25
Figure 8.2A: Generalised impulse response(s) of DlnGDPP and
DlnAID to one S.E. shock in DlnGnd
DlnGnd
DlnGDPP
DlnAID
Horizon
-0.01 -0.02 -0.03
0.00 0.01 0.02 0.03 0.04 0.05 0.06
0 5 10 15 20 25
Responses of per capita GDP and per capita aid to once for all one standard error
shock to per capita non-development expenditure are presented in Figure 8.2A. It
shows that responses of non-development expenditure to a shock to itself die out
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
296
relatively quickly than was the case for per capita development expenditure. Aid’s
response to a shock in non-development expenditure follows the responses of non-
development expenditure. We also find that responses of per capita non-development
expenditure to a one standard error shock to aid flows do not persist (Figure 8.2B), as
aid’s response to a shock to itself dies out quickly.
In sum, we find that in general aid responds to shocks to both development and non-
development expenditure. Additionally, shocks to aid flows cannot be sustained for
long.
Aid and government revenue
Figure 8.3A demonstrates the responses of per capita GDP and per capita aid to a one
standard error shock to per capita revenue. The response of revenue to shocks to itself
initially begins with a larger positive effect of over 8 per cent and then declines to
negative 6 per cent. It then converges quickly towards zero. Thus, it suggests that per
capita revenue does not have much cyclical effects of shocks. Interestingly, when
revenue response is negative in the early period, the aid response is found to be
positive. That is, aid is needed to fill the shortfall in revenue.
The responses of per capita GDP and per capita revenue to a one standard error shock
to per capita aid are displayed in Figure 8.3B. Generally, the responses of revenue to
the shock in aid flows follow the opposite pattern of responses of aid to the shock to
itself. This is largely in line with the pattern of responses of aid to a shock to revenue
(Figure 8.3A). That is, aid is needed to cover the short-fall in revenue.
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
297
Figure 8.3A: Generalised impulse response(s) of DlnGDPP and DlnAID to one S.E. shock in DlnREV
A
DlnREV
DlnGDPP
DlnAID
Horizon
-0.02 -0.04 -0.06 -0.08
0.00 0.02 0.04 0.06 0.08 0.10
0 5 10 15 20 25
Figure 8.3B: Generalised impulse response(s) of DlnGDPP and DlnREV to one S.E. shock in DlnAID
DlnREV
DlnGDPP
DlnAID
Horizon
-0.05
0.00
0.05
0.10
0.15
0 5 10 15 20 25
Chapter 8: Foreign Aid and Government’s Fiscal Behaviour
298
8.7 Summary and conclusion
We have investigated the revenue and expenditure behaviour of the Nepalese
government in the presence of aid flows. We have found that per capita aid, per capita
revenue and per capita development and non-development expenditure are all
cointegrated. The results also show that aid positively affects both development and
non-development expenditure in the long-run. However, since aid is mainly given for
development expenditure, the positive long-run relationship between aid and non-
development expenditure may indicate aid fungibility. This is in line with findings for
most developing countries.
However, contrary to most of the early studies, we have found that aid is positively
related to revenue in the long-run. Relevant to this may be aid in the form of technical
assistance to improve tax administration and the efficiency of the tax system.
The analysis of the impulse response function shows that aid responds positively to
shocks in both development and non-development expenditure as well as to shocks in
revenue. That is, government expenditure programs influence aid disbursement, and
aid is needed to cover the shortfall in revenue. This implies that aid is generally used
as revenue in the government budget. That is, aid flows can relax government budget
constraint, and there is no evidence that aid flows reduce revenue efforts.
Chapter 9
Summary, Conclusions and Policy Recommendations
“The central challenge for today’s conventional country-focused aid delivery system is managing divergent views on strategies for development and poverty reduction, while improving coordination, increasing ownership, and reducing aid dependence” (Kanbur and Sadler, 1999: 4).
Foreign aid has been and remains an important source of financing the needs of
developing countries in their quest for economic progress. This is no different for
Nepal. About half of Nepal’s development expenditure remains financed by foreign
aid. Yet Nepal remains one of the poorest countries of the world with nearly 40 per
cent of its population living in absolute poverty. However, there has been no
comprehensive macroeconomic study of foreign aid effectiveness in Nepal. This
thesis aims to fill this gap.
The impact of foreign aid on economic growth remains a subject of considerable
debate. Its performance varies across countries due to geography, policy environments
and socio-economic conditions. A substantial portion of aid may be used to finance
projects with low rates of return, and in some cases, aid promotes consumption rather
than investment. In particular, aid can contribute to the increase in a government’s
recurrent expenditure and reduced revenue effort. In other words, aid can make a
government lazy. Critics have also pointed out that aid facilitates corruption.
Furthermore, while bilateral aid is mainly based on a donor’s political and
commercial motives, multilateral aid is often attached with conditions, which may not
necessarily coincide with the recipient’s own preferences or needs. More importantly,
Chapter 9: Summary, Conclusion and Policy Recommendations 300
aid is only one factor contributing to economic growth; its effectiveness depends on
many other factors such as absorptive capacity, quality of institutions, resource
endowment and policy environment.
These diverse and complex issues have important implications for evaluating aid
effectiveness. Therefore, in this study of Nepal, we have examined the effectiveness
of aid in both aggregate and disaggregated forms (for example, loans versus grants),
as well as in terms of its sources, that is, bilateral and multilateral. We have
incorporated policy variables to investigate whether aid effectiveness improves in the
presence of a good policy environment. We have also examined the nature of
government expenditure and revenue efforts in the presence of foreign aid.
9.1 Summary of findings
The analysis employs time-series econometric techniques such as cointegration and
the error correction mechanism, using data for the period 1970-2002. The empirical
analysis is divided into three parts. In the first part, the relationship between aid and
per capita real GDP is examined within a framework of the neoclassical production
function. In the second part, the relationship between aid and investment is examined
within the framework of the two-gap model. In the third part, the relationship between
aid and government’s expenditure and revenue is investigated within the framework
of the fiscal response model. The results show that aid has a positive and significant
relationship with per capita real GDP, savings and investment. The fiscal response to
aid suggests that aid induces more non-development expenditure than development
Chapter 9: Summary, Conclusion and Policy Recommendations 301
expenditure; however, aid does not have any negative impact on revenue raising
efforts.
9.1.1 Aid and per capita GDP Within the framework of the neoclassical production function, aid is assumed to
augment technology through technical assistance and new knowledge embodied
imported capital goods. Thus, foreign aid becomes a variable in the production
function. In addition to examining the impact of total aid, we have disaggregated aid
by its forms (for example, loans and grants) and sources (for example, bilateral and
multilateral aid). The analysis has been extended to examine the influence of policy
environment on aid effectiveness.
Aid, whether in aggregate or in disaggregated form, is found to have a significant
positive relationship with per capita real GDP in the long-run. Grants aid have a
relatively stronger positive association with per capita real GDP than loans aid. This
finding has important implications. Loans aid adds to debt burden, and if government
revenue and export earnings do not rise fast enough, the debt burden may impede
economic growth.
Both bilateral and multilateral aid have been found to play an equally important role.
However, judging from their joint effect on per capita real GDP, it seems that there
are significant complementarities between bilateral and multilateral aid. This may be
due to the fact that bilateral donors are linking their support to the approval of the
multilateral donors since the introduction of Structural Adjustment Program.
Chapter 9: Summary, Conclusion and Policy Recommendations 302
Our model has been extended by incorporating three policy variables with regard to
macroeconomic stability, openness and financial deepening. The indicators used for
this are inflation, total trade as a proportion of GDP and M2/GDP. The results suggest
that aid effectiveness improves in Nepal in the presence of a stable macroeconomy, a
liberalised trade regime and a liberalised financial sector. We also find that political
instability affects the economy adversely, as indicated by the significance of the
dummy variables used for political instability. In such situations, aid can keep the
economy going.
Finally we find that aid has a negative relationship with per capita real GDP in the
short-run. This indicates that Nepal suffers from excessive aid volatility and a lack of
absorptive capacity. This may also be due to aid conditionality. Reforms imposed by
conditionality may adversely affect the economy in the short-run. On the other hand,
the failure to implement conditionality by the deadline causes delay in aid
disbursement, which disrupts government expenditure plans.
9.1.2 Aid and the savings–investment gap
The purpose of investigating the relationship between aid and the savings–investment
gap is to evaluate aid’s contribution to economic growth via its contribution to capital
formation. The starting point of this investigation is the hypothesis that a low
correlation between domestic investment and domestic savings is an indication that
foreign financing is filling the savings–investment gap. The empirical results confirm
this hypothesis. The result is further confirmed by the findings of positive associations
between aid and investment.
Chapter 9: Summary, Conclusion and Policy Recommendations 303
We also find unidirectional causality from changes in savings to changes in foreign
aid. However, we did not find reverse causality between them. This implies that aid
responds positively to savings shortfalls and, contrary to the views of some critics, aid
does not adversely affect domestic savings. We have also analysed the impulse
response functions among variables. Changes in all variables converge towards zero,
after a shock suggesting that they are in equilibrium relationships in the long-run. The
analysis further reveals that the investment response to shocks in domestic savings is
larger and takes longer to die out than the response to shocks in aid. This indicates
that domestic savings is a more dominant source of finance. This has also been
confirmed by the findings of bidirectional causality between savings and investment.
9.1.3 Aid and fiscal behaviour
Since government’s budgetary position is an important determinant of domestic
savings and the government plays an important role in a nation’s capital formation,
we investigate aid’s impact on government’s expenditure and revenue. The empirical
findings show a positive and significant relationship between per capita aid and per
capita non-development expenditure and a low elasticity of development expenditure
with respect to aid. This indicates perhaps the problem of aid fungibility as aid is
mainly given for development purposes. But this may also be due to the fact that
Nepal receives significant amounts of humanitarian aid.
The impulse response analysis shows that the shocks to aid have relatively less effects
on non-development expenditure compared to effects on development expenditure.
Chapter 9: Summary, Conclusion and Policy Recommendations 304
This reflects the long-term nature of development expenditure, which cannot be
adjusted quickly to shortfalls in funding.
9.2 Concluding remarks
Based on our empirical findings we can conclude that the overall contribution of
foreign aid in Nepal has been positive. Foreign aid fully financed the development
expenditure of the First Five-Year Plan and still contributes over 50 per cent to the
development expenditure.
Before 1950 when the country was ruled by the Rana Regime, Nepal did not have any
link with the rest of the world except with the then British India and Tibet. The
movement of goods and people from one part of the country to another usually
required passage through India. Travel time to the capital Kathmandu from some parts
of the country could take a minimum of 15 to 30 days.1 There were a few all-weather
roads in Kathmandu only – none in other parts of the country. This lack of
infrastructure made it almost impossible for Nepal to expand trade and economic
activity. There were no educational institutions in the country except for the Tri-
Chandra Campus and Darbar High School in Kathmandu and some Sanskrit Schools
(for the priests). Traditional (herbal and spiritual) medicine provided the only
available heath service for the majority of the population. Thus, life expectancy at
birth was too low, while child mortality rate was very high. The situation has
improved markedly since then.
1 For example, while the flying time between Bhojpur district and Kathmandu is about 45 minutes, the land travel used to take almost one month in the 1960s.
Chapter 9: Summary, Conclusion and Policy Recommendations 305
9.2.1 Nepal with foreign aid
Soon after the downfall of the Rana Regime in 1951, foreign assistance came into the
country mainly for the development of infrastructure. Since then Nepal has achieved
notable progress. For example, motorable roads increased from less than 280
kilometres in 1951 to over 15,000 kilometres in 2003. Likewise, irrigated land
increased from about 6,000 hectares in 1951 to over 716,000 hectares (excluding the
farmer-managed irrigation system) in 2003. During the same period, production of
electricity increased from less than 1.5 megawatts to over 370 megawatts (Mihaly,
2002). Moreover, one can now find many schools, universities and hospitals across
the country. Telephone lines, healthcare facilities and the availability of safe drinking
water also substantially increased. These have contributed to a remarkable progress in
Nepal’s social development. For example, the adult literacy rate increased from 16 per
cent in 1970 to 45 per cent in 2002; life expectancy at birth increased from 42 years in
1970 to 60 years in 2002, and the under-five mortality rate (per 1000 live births)
decreased from 234 in 1970 to 83 in 2002.
As noted by Poudyal (1988), these achievements have been possible through foreign
assistance; Nepal’s own revenue was too low to meet the development effort it
required. In other words, resource gaps (namely, the savings–investment and foreign
exchange gaps) were huge in Nepal. To enable the country to meet its development
objectives, these gaps have been financed by foreign aid.
Therefore, one can conclude that despite the low rate of economic growth, foreign aid
has been an important contributory factor in Nepal’s socio-economic development.
Chapter 9: Summary, Conclusion and Policy Recommendations 306
Hence, our findings that aid contributes to economic growth are consistent with the
fact of Nepal’s socio-economic progress in the last 50 years. The findings of our study
are in line with those of such studies as Papanek (1972, 1973) and Hansen and Tarp
(2000). Our findings also show the importance of policy environment.
9.2.2 Foreign aid could be more effective
This thesis is concerned with macro issues of aid effectiveness; thus micro issues of
aid effectiveness are not discussed explicitly. However, from the results of our macro
analyses, we can infer some bearings of micro issues such as absorptive capacity, aid
management and coordination and the like on aid effectiveness. These issues are
identified below as possible contributory factors to the weakness in aid utilisation in
Nepal. These weaknesses appear to have caused a short-run – long-run paradox. That
is, while aid has positive impacts in the long-run, in the short-run aid has negative
impacts.
Lack of absorptive capacity and coordination Nepal’s new era began with the political change that ended the Rana Regime in 1951.
Nepal made an attempt to modernise by introducing more liberal socio-economic
policies. However, it was not an easy task because the entire system (of family rule)
had to be replaced with democratic norms and values. Thus, when aid came into the
country, policy makers had little knowledge about how to use and channel aid
effectively. Still, because it had an underdeveloped economy and because of donors’
strategic interests, aid started pouring in. Nepal seriously needed guidelines for the
supervision and allocation of aid. In the absence of a proper system of assessment,
Chapter 9: Summary, Conclusion and Policy Recommendations 307
one observes a persistent misuse of aid. The negative or low returns to aid caused by
the misselection of capital intensive projects were never examined. Furthermore,
Nepal’s technological and institutional capabilities were too weak to utilise aid
effectively. There was no skilled manpower, and there were always a shortage of
policy makers in the early days of the country’s development.
Some of these weaknesses still persist, causing a low absorptive capacity. The
problem is compounded by a lack of coordination among various government
departments. There is also no proper coordination among donors, leading to high aid
volatility, overlapping aid-funded projects and lopsided allocation of aid.
Donor driven aid As noted above, Nepal was unprepared and almost unable to utilise aid funds when
aid started pouring in after 1951. Consequently, aid to Nepal was mainly based on
donors’ own perceptions and Nepal had little control over the use of aid. Many
projects and programs are still donor driven in Nepal. This has been acknowledged by
the government: “many projects and programs are still excessively driven by donor
demands. As a consequence, the effectiveness of foreign aid is reduced” (HMG/N,
Foreign Aid Policy, 2002: 5). In addition, bilateral aid, which is motivated by donors’
strategic interests, accounts for over 60 per cent. Nepal’s two traditional donors are
India and China. Their strategic interests were more dominant in the early 1950s until
the early 1980s, when they competed with each other to influence Nepal’s foreign and
economic policies. As Mihaly (2002) noted, India (as did the United States) always
tried to diminish Chinese influence in Nepal. Indian aid went to infrastructure that
held militarily rather than socio-economic importance. The competing strategic
Chapter 9: Summary, Conclusion and Policy Recommendations 308
interests in Nepal at times created not only political tensions but also adversely
affected the economy.2
Lack of country ownership
Critics have identified lack of country ownership as a major cause of aid
ineffectiveness through the failure to implement policy reforms. Although Nepal has
implemented policy reforms demanded by aid conditionality, it has often dragged its
feet as it has found some reforms, especially privatisation, too difficult to implement.
Political resistance to reforms is not uncommon when reforms are imposed rather than
designed through a democratic process. This is all more important for Nepal where
there is a strong left leaning political movement.
Aid allocation Aid effectiveness depends on its allocation. Although tied project aid is not
necessarily beneficial for a country, aid effectiveness may decline if a significant
amount of aid goes to finance current government consumption or non-development
expenditure. In Nepal, there has been a high propensity to spend aid money for non-
development purposes and for the non-traded sector. On the other hand, when aid
money goes to development expenditure involving large capital-intensive
infrastructure projects, it may facilitate corruption, an issue discussed below.
Evidence from other studies shows that aid spent on pro-poor projects such as public
health and primary education and rural development is more effective.
2 During 1988, Nepal purchased 500 truckloads of arms as per Nepal’s arms deal with China. India reacted strongly and that created political tension between Nepal and India. Consequently, the relationships between the two countries were strained, particularly in 1989 when India closed 14 of 16 its transit points after the dispute. Nepal had to bear a heavy economic cost due to insufficient transit points to trade not only with India but also the rest of the world.
Chapter 9: Summary, Conclusion and Policy Recommendations 309
Current state of corruption Until recently in Nepal’s history, there was never any investigation into the corruption
of high profile government officials or ministers, despite the fact that Nepal is one of
the corrupt nations in the world. Political observers believe that aid was directly used
to strengthen the corrupt regime in power during the party-less Panchayat system of
1961-90. Thus, the effectiveness of aid was obviously reduced. Only after the early
1990s has the problem of corruption been addressed more seriously, as part of
conditions imposed by international donors such as the World Bank and the IMF. Yet
all the evidence shows that corruption remains ripe in Nepal. When it comes to the
utilisation of foreign aid, the problem of corruption is compounded by the fact that
Nepal does not have a transparent and reliable recording system for all foreign aid
resources. If donors direct aid to project accounts without informing the relevant
government department, the aid cannot be included in the national budget. As a result,
a significant amount of such transactions can be misused. In other words, aid
effectiveness falters due to lack of accountability and a sound management system,
both of which encourage corruption.
In sum, Nepal suffered from the absence of a coherent foreign aid policy. Being an
aid-dependent country, Nepal should have prepared a comprehensive foreign aid
policy for the effective utilisation of aid years ago. Instead, Nepal has been utilising
foreign aid without any guidelines or system for assessing the impact of aid on the
economy for over a half century. While Nepal has become more aid-dependent, it has
failed to prioritise sectors that would have reaped the maximum benefit of aid inflows.
The lack of a comprehensive aid policy has been responsible for the uncoordinated
Chapter 9: Summary, Conclusion and Policy Recommendations 310
inflow of foreign aid for donor domination and for the mismanagement of aid funds.
Only very recently Nepal has formulated a national foreign aid policy.
9.3 Policy recommendations
The rationale for foreign aid is that it assists a developing country to achieve rapid
economic growth and poverty reduction. In the case of Nepal, foreign aid can help
achieve targeted economic growth by improving aid effectiveness of aid through the
design and implementation of appropriate and consistent foreign aid policies
compatible with national interests. More precisely, aid should be channelled to those
areas/sectors where aid can have relatively high economic and social returns. For
example, more aid should be directed to pro-poor sectors such as agriculture, primary
health and education.
Nepal’s main source of income and employment is the agricultural sector. Yet most of
Nepal’s poor live in rural areas. Thus, in the context of Nepal, poverty reduction that
is enhanced by rapid economic growth can be achieved through productivity growth
in Nepal’s agricultural sector. Despite some efforts in the past, the agricultural sector
is still far behind in lifting the living standard of the majority of the Nepalese. As
NPC (2003) noted, with more than three-quarters of the total population still engaged
in agriculture, the sector needs to be given a high priority. By recognising past
mistakes through appropriate assessment, supervision and policy implementation,
Nepal can rectify persistent problems and maximise the benefits of aid in this sector.
Chapter 9: Summary, Conclusion and Policy Recommendations 311
However, Nepal’s sectoral distribution of aid indicates that more amount of aid has
been directed to the building of capital infrastructure across the country rather than to
the development of the agricultural sector. Nepal therefore needs to channel more
foreign aid to the agricultural sector, and it needs to do so effectively. Aid has a direct
impact on the productivity growth of the agricultural sector. Aid brings new
technology, which plays a key role in modernising the sector. Aid can finance
improvements as well as the building of new irrigation facilities across the country.
More importantly, aid helps finance agriculture research that facilitates the use of land
in accordance with geographical conditions and farmers’ needs.
A larger proportion of aid should also go to the primary healthcare sector. Studies find
that the productivity of workers is directly related to the condition of their health (see
Dasgupta, 1993 and Sachs, 2001). Nepal’s poor suffer not only from malnutrition, but
also have very poor access to safe drinking water and basic healthcare facilities. The
Nepal Human Development Report has rightly advocated for larger public expenditure
in this sector.
Since Nepal has a shortage of skilled labour, increased emphasis also needs to be
given to the development of its human resources. Labour productivity can be
improved through appropriate education and training. Nepal’s adult literacy rate is
still below 50 per cent, and the female literacy rate is lower than the male rate. Since a
skilled labour force is directly linked to economic growth (being a factor of
production), providing education and training (specifically vocational) to illiterate
people is certain to improve living standards, by giving people an opportunity to earn
Chapter 9: Summary, Conclusion and Policy Recommendations 312
higher income. Therefore, investment in primary education and vocational training
should be increased.
This will strengthen the aid absorptive capacity that is required for Nepal to achieve
rapid economic growth and poverty reduction. One can in fact justify a higher
allocation of aid and investment in education on other grounds. For example,
educating an illiterate person will indirectly help improve health and sanitation at the
personal and family levels. In other words, education has a positive multiplier effect
in changing a backward society into a more modern, (economically) productive
society.
Since aid effectiveness also depends on the extent of corruption in the recipient
country, Nepal should also combat corruption. An efficient foreign aid management
team (specific government department) with strong financial discipline is required to
maximise the benefits of aid. As donor agencies stress the importance of
decentralisation, strong corruption measures should be introduced at the local
government levels (such as district council and Village Development Committee). In
addition, regular evaluation of the effectiveness of projects and programs needs to be
conducted, to ensure that targeted socio-economic returns are being met. By carefully
scrutinising and supervising capital-intensive infrastructure projects, Nepal can
minimise corruption.
While conditionality in aid disbursement can influence aid allocation and utilisation,
the donors should take extreme care in designing conditionality. To begin with, the
pace and sequence of reforms should be within the country’s administrative and
Chapter 9: Summary, Conclusion and Policy Recommendations 313
institutional capacity. Secondly, reforms should be politically accepted, and hence
should be agreed through the political process of dialogue, involving various stake-
holders.
Aid to Nepal comes not only from donor governments but from International Non-
governmental Organisations (INGOs) as well. Although a large number of INGOs are
working in Nepal, the government does not always have a direct link with them in
terms of their economic assistance. To maintain transparency and accountability,
regular supervision and effective reporting provisions (in the national budget) about
the operations and effectiveness of INGOs are required. It is also important to compile
data on INGOs aid for future research.
Finally, while foreign aid is an important source of revenue, Nepal should be able to
improve and broaden its domestic sources of revenue. Aid can help in many ways. For
example, technical assistance can help to improve and extend the tax base as well as
create a more efficient tax administration. Aid contributes to higher economic growth,
which eventually helps to expand domestic revenue. Most significantly, Nepal’s aid
dependency can be reduced through linking aid-financed projects to an improved
domestic revenue mobilisation capacity. To achieve all this, the question of reducing
Nepal’s aid dependency over a reasonable time frame needs to be addressed.
Scope for future research
In this thesis, we have empirically examined the aid and growth relationship and
found that aid has been generally effective in promoting economic growth. Yet
Nepal’s socio-economic conditions remain appalling. The poverty rates among the
Chapter 9: Summary, Conclusion and Policy Recommendations 314
socio-economically disadvantaged people and in rural and mountain areas are very
high. This has resulted in high inequality. Corruption is also rampant in the country.
All these conditions imply that the benefits of growth are not trickling down.
It is also generally believed that aid could have been more effective in the absence of
corruption and political interference in aid allocation. The literature indicates that
there could be a two-way relationship between aid and corruption, especially when
donors are motivated by their own political and strategic objectives. This is an
important aspect given Nepal’s strategic location between two rival Asian powers,
India and China.
We also find in the literature that aid allocation can lead to resentment, which in turn,
can become violent. This implies that aid can be used to dampen social violence and
to reconstruct the economy. This is a relevant issue for Nepal, as the country is beset
with Maoist insurgency fuelled by extreme poverty and inequality. Therefore, this
aid-growth research could be extended to examine the following issues:
(a) Aid’s impact on human development such as poverty, literacy rates, and infant
mortality rate along the lines suggested by Mosley et al. (2004) and Gomanee
et al. (2005);
(b) The link between aid and corruption along the lines suggested by Sevensson
(2000), Knack (2001) and Gupta et al. (1998);
(c) The role of donor motives in aid effectiveness as suggested by Khadka (1997)
and Mosley (1985);
(d) The link between aid and social conflict as suggested by Collier and Anke
(2004) and Gounder (2005).
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