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Who is my Neighbour? Cultural Proximity and the Diffusion of Democracy*
David Wong De-Wei
April 2015
Abstract
What explains the strong spatial and temporal clustering of democratization around the world? Most
theories of democratic diffusion focus on geography: the probability of a state’s democratization is
influenced by developments in geographically neighbouring states. However, this paper challenges
this view through the lens of cultural proximity. I argue that elites and society are influenced by
democratic developments in cultural neighbours because they look to them as reference states, and
relate with them through transnational religious/ethnic imagined communities. I demonstrate this
relationship using both qualitative historical evidence about the ‘third wave’ of democratization, and
quantitative statistical analysis of transitions globally from 1960-2008. The effect of cultural
proximity on democratization is strong and robust across various sample sizes and controls,
consistently removing the effect of geographical proximity.
* Paper prepared for the International Association for Political Science Students (IAPSS) World Congress 2015 titled, “The Politics of Conflict and Cooperation” at Birkbeck University in London, United Kingdom, 14-18 April 2015. This paper received the IAPSS Award for Academic Excellency 2015 for the best paper presented. The abridged version is found here. Contact author for full paper at [email protected]
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Introduction
Over the past few decades, we have seen a dramatic rise in the number of democracies globally.
Between the 1960s to early 2000s, we see about 87 democratic transitions around the world
(Cheibub, Gandhi & Vreeland 2010; Houle, Layser, & Xiang 2013).
An interesting trend in these transitions is that it tends to be clustered across time, and across
geographical space. Countries that are close to each other tend to democratise together, giving
democratisation a ‘wave-like’ characteristic. A key research area has thus been to examine why this
is happening. Why are democratic transitions spreading in this manner? What conditions facilitate
this?
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Existing Literature
Most scholars that study this contagion argue that geographical neighbours influence
democratization (O’Loughlin et al. 1999; Wejnert 2005; Brinks & Coppedge 2006; Simmons,
Dobbin & Garrett 2008). They claim that neighbouring countries tend to have closer and deeper
network ties with each other, allowing democratic ideas to spread. The frequent contact and flow of
people, ideas, goods and services lead to a diffusion of norms. State and opposition leaders may also
look to what is going on in neighbouring countries as mental shortcuts to learn from (Weyland
2012).
Although this seems plausible, it remains theoretically underdeveloped. Why for example do
countries simply copy their geographical neighbours? Who do they look to as their neighbours, and
specifically who do they consider neighbours worth copying?
The presence of dense networks between neighbouring states may increase exposure to democratic
ideas, but it does not necessarily lead to the adoption of democracy; the link between exposure and
adoption needs to be explained.
Although most studies conceptualize space in a geographical sense, space can also be defined
culturally. Differences in language, ethnicity, religion, and colonial history can lengthen the cultural
distance between states, limiting the spread democracy.
A Theory of Cultural Proximity
Cultural distance can be conceptualised as the measure of how similar a state’s culture is from
another. People living in Kuwait and the UAE for example, are on average likely to share more
common values and worldviews, and be sensitive to similar symbols and metaphors, compared to
people living in Greece. Religion, ethnicity, language, and colonial history shape culture, and can be
used to proxy cultural distance between states.
But how does cultural proximity influence the spread of democratisation?
1. Cultural proximity allows for denser networks and thus more information flow. For
neighbouring countries to be affected by developments in other countries, they must receive
information about it, and this information has to be framed as a struggle for democracy, not say
youth violence (cf. Rogers 1995; Scott 2000).
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Direct Communication Indirect Communication (through translator)
Figure 1. All potential networks between DC and IC dyads.
Countries that share a common language will on average have denser networks compared to states
that speak different languages (Melitz 2008; see Figure 1). This allows more information to flow
between countries, and is less likely to be blocked by state officials or the co-optation of translators.
And by translators here, I mean media outlets, publishing houses, etc.
2. Cultural proximity also helps to bridge the gap between exposure and emulation through
shared identity. People hold multiple identities simultaneously. One may associate herself as an
Egyptian, an Arab, a Muslim, a bureaucrat, a mother, and a wife, each with different degrees of
importance.
Some of these identities link people with an “imagined community” beyond the confines of their
nation state (cf. Anderson 2006). Religious and ethnic groups, like states, use membership data,
maps of geographic religious/ethnic reach, museums, periodicals, and rituals to bolster a sense of
unity within their in-group, creating within the minds of people that they belong to a wider
community beyond the state.
Figure 2 shows an example of efforts by Christian organisations to construct this imagined
community. The map itself shows no state borders, but simplifies the world into areas that are
‘Christianised’ and those that are not. Maps like these help reinforce a transnational religious identity
by visualising the geographical spread of Christianity, giving Christianity a ‘geo-body’ (Winichakul
1994)
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Figure 2. A Christian ‘imagined community’.
When a state democratizes, its cultural neighbours are likely to observe developments, and may
identify with the struggle for freedom because they consider themselves part of the same
transnational community. This may inspire people, who see themselves in similar cultural contexts,
to push for democracy, amplifying the effect of neighbouring transitions.
In sum, cultural proximity influences democratic diffusion in at least two ways: through a network
effect, and an identity effect.
Historical Evidence: The Iberian-Catholic Wave
I apply this theory to what scholars have called the ‘third wave’ of democratisation from the late
1970s through the mid 1990s (Huntington 1991). The wave of democratization began in Spain and
Portugal, spread to Latin America, then the Philippines, and finally to Eastern Europe and Africa. In
the interest of time, I will only sketch the contagion effect between Southern Europe and Latin
America.
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In 1974, a group of military officers launched a coup aimed at halting Portugal’s colonial wars,
leading to the parliamentary elections of 1976 (Linz and Stepan 1996). Ruling elites in Spain
watched Portugal closely. Although Spain was not entangled in similar colonial wars, Spanish elites
knew that the institutional environment they operated in was similar. Both were Catholic-majority
states and faced heighted pressure for democracy after the Second Vatican Council, when the
Catholic hierarchy in Spain withdrew their support of the regime (Philpott 2004).
Under pressure, then-Vice President of Spain Manuel Fraga lamented that he “did not want to
become the Caetano [the dictator of Portugal] of Spain,” and signalled interest in guiding democratic
change; that he did not want to risk a coup (quoted in Linz and Stepan 1996, p. 76)
The ruling elites thus began negotiations with opposition parties for a top-down transition toward
democracy. The result was a “pact transition”: democratic elections were held in 1977, but only after
a Law of Political Amnesty was passed, which protected the ruling elites of the old regime from any
charges of war crimes or human rights abuses (Ibid; Encarnacion, 2008).
The first countries that experienced the contagion of Portuguese and Spanish transitions were not
geographically proximate Morocco or Algeria, but Latin America. These states were former colonies
of the two Southern European states and had similar inherited political institutions.
The influx of information into Latin America about Portugal and Spain’s transition created increased
societal pressures for democracy. As if mimicking the Spanish transition, Catholic churches began to
withdraw support of dictators, and spoke openly against the regime. (Edmonds 2010) Oppositional
elites across Latin America picked up on these opportunities, and used the institutional resources of
the Church to pressure the regime for democratization.
Ruling elites across Latin America, watching these developments unfold, began to recalculate how
best to preserve some of their personal power and wealth. The top-down transition of Spain provided
the ruling elites with a template that could minimize the cost of a democratic transition by providing
(a) amnesty from earlier war crimes or human rights abuses; (b) and a controlled pace of transition
(Encarnacion 2008).
Many Latin American ruling elites eventually chose this path and negotiated with opposition elites to
create ‘pact transitions’ with amnesty laws – i.e., Chile (1978), Brazil (Amnesty Law of 1979),
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Uruguay (Law Declaring An Expiration of the State’s Punitive Authority, 1986) followed swiftly by
elections.
This trend is especially noteworthy because elite-cantered and relatively peaceful ‘pact transitions’
were rare before Spanish democratization. The two earlier waves of democratisation did not take this
path.
The first ‘long wave’ of democratization that spread and evolved across Europe in the 18th and 19th
century was punctuated with violence and unrest. Following the French revolution, industrialist and
intellectuals rebelled against monarchs, and attempted to topple these regimes. Only after a long
conflict between state and society did continental Europe move toward some form of universal
suffrage and representative democracy (Spielvogel, 2009).
Moreover, the post-World War II ‘second wave’ of democratization was primarily a result of the
Allied powers imposing democratic institutions on fascist states, and departing colonizers
transferring power to colonial legislatures following independence, not elite pacts with those
currently in power (Huntington 1991).
We thus see that some form of copying and emulation of the Spanish model was actually happening;
that it was not just a coincidence or chance correlation that these countries were democratising at the
same time. The process itself was similar.
However, some may still be believe that this seeming pattern of democratisation is either
idiosyncratic or spurious – i.e., caused by geographical proximity or domestic factors like per capita
income or inequality or trade. I thus turn to statistical analysis to control for alternative explanations
and test the generalizability of my theory.
Statistical Analysis
I ran a survival analysis to test the association between cultural proximity and transitions to
democracy in a global sample of 129 states from 1960-2008.
[Table 2 at bottom]
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I controlled for various domestic variables that scholars often cite as important to democratisation.
Values that are positive indicate that this variable increases the likelihood of democratisation.
Negative values indicate they reduce the likelihood. Values that are highlighted yellow, and with
stars are variables that actually have an effect; that are statistically significant
Table 2 tests the effect of having democratic neighbours on the likelihood of transition. At the first
column, model 1, I ran a regression with just domestic variables. Model 2, 4, and 6 includes the
geographical neighbour influence variable, which we see is statistically significant before we control
for cultural proximity. I ran multiple models to ensure that the number of observations remains
unchanged, since we want to make sure that it is due to the variable, and not the change in sample
that is causing the results.
I include cultural proximity variables in model 3, 5, 7, seen through the proxies of religious,
language, and colonial neighbour. They are strongly statistically significant, and in two cases they
remove the effect of geographic proximity.
[Table 3 at bottom]
In Table 3, we look at the effect of having neighbours who experienced democratic transitions. We
see that in every case here, the moment we control for the democratisation of cultural neighbours, the
effect of geography is removed.
Now I am not saying that cultural proximity is the only thing that influences democratisation. Indeed,
we see that oil, trade, and other variables continue to have an effect. What I am arguing here is that
cultural proximity is one of the variables, and indeed an important one, influencing the likelihood of
democratic transitions in states.
These findings are substantively and statistically strong, and are robust even after controlling for
various domestic determinants of democracy and other means of diffusion. Indeed, they alter the
strength and significance of domestic variables often thought to influence democracy, implying that
analysis that omit cultural proximity variables suffer from omitted variable bias.
In contrast, the effect of geographical diffusion is consistently removed once cultural proximity is
controlled, implying that the effect of geography found in earlier studies may be spurious.
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The overreliance on geographic space and distance simplifies complex diffusion processes that are
often influenced by culture. As we see from the results, we continue to live in a world that remains
largely embedded in culture and identities beyond nation state. Studies that look democratisation and
other political dynamics should pay careful attention to these ‘softer’ elements, and not only on
‘hard’ economic or material factors.
References
Anderson, Benedict. 2006. Imagined Communities: Reflections on the Origin and Spread of Nationalism, New Edition. New York: Verso.
Brinks, Daniel, and Michael Coppedge. 2006. “Diffusion is No Illusion: Neighbor Emulation in the Third Wave of Democracy.” Comparative Political Studies, 39 (1): 463-489.
Cheibub, Jose, Jennifer Gandhi and James Vreeland. 2010. “Democracy and Dictatorship Revisited.” Public Choice 143: 67-101.
Edmonds, Amy. 2010. “Authoritarianism and the Catholic Church in Latin America.” PhD diss., Baylor University.
Encarnacion, Omar. 2008. “Reconciliation After Democratization: Coping with the Past in Spain” Political Science Quarterly 123 (3): 435-459.
Houle, Christian, Mark A. Kayser, and Jun Xiang. 2013. “Diffusion or Confusion? Debt and Democratization Around the World.” Paper presented at conference, “Think Globally, Act Locally,” at the London School of Economics, 6-7 March, 2013.
Huntington, Samuel. 1991. The Third Wave: Democratization in the Late Twentieth Century. Norman: University of Oklahoma Press.
Linz, Juan, and Alfred Stepan. 1996. Problems of Democratic Transitions and Consolidation: Southern Europe, South America, and Post-Communist Europe. Baltimore: John Hopkins University Press.
Melitz, Jacque. 2008. “Language and Foreign trade,” European Economic Review 52: 667-699. O’Loughlin, John, Michael Ward, Corey Lofdahl, Jordin Cohen, David Brown, David Reilly,
Kristian Gelditsch, and Michael Shin. 1999. “The Diffusion of Democracy, 1946-1994.” Annals of the Association of American Geographers 88 (4): 545-574.
Philpott, Daniel. 2004. “The Catholic Wave.” Journal of Democracy 15 (2): 32-46. Rogers, Everett. 1995. Diffusion of Innovations, Fourth Edition. New York: Free Press.
Scott, John. 2000. Social Network Analysis: A Handbook, 2nd Edition. London: Sage Publications. Simmons, Beth, Frank Dobbin and Geoffrey Garrett. 2008. “Introduction: The Diffusion of
Liberalization.” In The Global Diffusion of Markets and Democracy edited by Beth Simmons, Frank Dobbin and Geoffrey Garrett. Cambridge: Cambridge University Press.
Spielvogel, Jackson. 2009. Western Civilization, Volume II: Since 1500, 8th Edition. Boston: Wadsworth.
Wejnert, Barbara. 2005. “Diffusion, Development, and Democracy, 1800-1999.” American Sociological Review 70 (1): 53-81.
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Weyland, Kurt. 2012. “The Arab Spring: Why the Surprising Similarities with the Revolutionary Wave of 1848?” Perspectives on Politics 10 (4): 917-934.
Winichakul, Tonhchai. 1994. Siam Mapped: A History of the Geo-Body of a Nation. Honolulu: University of Hawaii Press 1994.
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Table 2. Predicted Likelihood of Democratic Transition from 1960 to 2008 Based on Proportional Measure Concept Explanatory Variable 1 2 3 4 5 6 7 Domestic Variables
Log GDP Per Capita .178 (.171)
.189 (.180)
.174 (.174)
.280 (.193)
.284 (.185)
-.068 (.211)
-.204 (.204)
Urbanization .007 (.009)
.002 (.009)
-.000 (.009)
-.003 (.010)
-.017+ (.009)
.013 (.010)
.009 (.010)
Log Economic Openness
1.94+ (1.06)
1.63 (1.05)
1.42 (1.07)
1.90 (1.26)
1.11 (1.25)
1.87 (1.17)
1.76+ (1.03)
Log Economic Openness2
-.341* (.146)
-.294* (.145)
-.258+
(.147) -.329+ (.174)
-.187 (.169)
-.326* (.162)
-.301* (.144)
Major Oil producer -1.38** (.450)
-1.27** (.449)
-1.10* (.457)
-1.38** (.497)
-.879+ (.496)
-1.02* (.454)
-1.02* (.448)
Island state -.023 (.315)
-.285 (.325)
-.457 (.330)
-.591 (.376)
-1.20** (.387)
-.081 (.331)
-.368 (.336)
Landlocked state -.365 (.301)
-.272 (.306)
-.387 (.308)
-.245 (.339)
-.612+ (.357)
-.088 (.343)
-.125 (.337)
Geography Geographical neighbour influence
.013*** (.004)
.012*** (.004)
.013*** (.004)
.000 (.004)
.012** (.004)
.003 (.004)
Cultural Proximity
Religious neighbour influence
.011* (.005)
Linguistic neighbour influence
.056*** (.007)
Colonial neighbour influence
.035*** (.006)
Time at risk 3996 3996 3996 3346 3346 3466 3466 No. of Subjects 129 129 129 100 100 110 110 No. of Transitions 87 87 87 76 76 73 73 Log Likelihood -133.17 -127.55 -124.79 -105.58 -63.71 -115.37 -99.99 Notes: Weibull Survival Model; Coefficients shown, standard errors in parenthesis. Coefficients need to be exponentiated (ex) in order to obtain hazard ratios. The effect of a one unit increase in the explanatory variable = ex – 1. Significant level: + ≤.1, *≤ .05, **≤ .01, ***≤.001.
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Table 3 Predicted Likelihood of Democratic Transition from 1960 to 2008 Using Change in Proportion of Democratic Neighbours
Explanatory Variable Religious Language Colonial Lag 1 Lag 2 Lag 1 Lag 2 Lag 1 Lag 2
Dom
estic
Var
iabl
es
Log GDP Per Capita .189 (.171)
.082 (.175)
.201 (.171)
.120 (.172)
.288 (.185)
-.151 (.194)
.301 (.185)
-.077 (.195)
-.061 (.203)
-.032 (.204)
-.047 (.202)
.038 (.206)
Urbanization .006 (.008)
.011 (.009)
.005 (.009)
.008 (.009)
.001 (.009)
.013 (.009)
.000 (.009)
.009 (.010)
.017+
(.010) .021* (.009)
.016+
(.010) .017+
(.009)
Log Economic Openness 1.90+ (1.05)
1.77+ (1.05)
1.85+ (1.05)
1.67 (1.05)
2.27+ (1.29)
5.82** (2.05)
2.19+ (1.28)
2.91+
(1.50) 2.24+ (1.19)
3.81* (1.67)
2.18+ (1.18)
3.10* (1.53)
Log Economic Openness2
-.334* (.145)
-.306* (.144)
-.327* (.145)
-.289* (.143)
-.385* (.177)
-.79** (.271)
-.375* (.176)
-.430* (.203)
-.382* (.164)
-.554* (.221)
-.374* (.164)
-.467* (.204)
Major Oil producer -1.36** (.450)
-1.35** (.451)
-1.34** (.450)
-1.32** (.451)
-1.47** (.500)
-.888+
(.497) -1.44** (.500)
-.985* (.497)
-1.10* (.454)
-2.55*** (.748)
-1.08* (.454)
-2.12*** (.635)
Island state -.013 (.316)
.006
(.316) -.007 (.316)
-.052
(.317) -.363 (.372)
-.044
(.372) -.357 (.373)
-.132
(.371) .130
(.316) .114
(.323) .142
(.323) .056
(.324)
Landlocked state -.353 (.301)
-.700* (.343)
-.345 (.302)
-.666* (.335)
-.316 (.331)
-.520* (.335)
-.310 (.331)
-.623+
(.334) -.197 (.336)
-.045 (.340)
-.189 (.336)
-.073 (.340)
Diff
usio
n
Democratization of Geographic Neighbour
2.06+ (1.08)
.856 (1.18)
2.12** (.779)
1.27 (.840)
2.09+ (1.1)
-4.22** (1.40)
2.17** (.790)
-.757 (1.12)
.993 (1.33)
.020 (1.40)
1.58+
(.878) .626
(.933) Democratization of
Religious Neighbour 10.58*** (1.00) 10.31***
(1.03)
Language Neighbour 7.46*** (.667) 4.85***
(.472)
Colonial Neighbour 8.38*** (.974) 7.62***
(.879) Time at risk 3946 3946 3896 3896 3308 3308 3270 3270 3421 3421 3376 3376 No. of Subjects 129 129 129 129 100 100 100 100 110 110 110 110 No. of Transitions 87 87 87 87 76 76 76 76 73 73 73 73 Log Likelihood -131.58 -101.75 -129.86 -100.90 -108.87 -54.45 -107.16 -68.45 -118.67 -86.86 -117.21 -89.40 Notes: Weibull Survival Model; Coefficients shown, standard errors in parenthesis. Coefficients need to be exponentiated (ex) in order to obtain hazard ratios. The effect of a one unit increase in the explanatory variable = ex – 1. Lags refer to the change in proportion of democratic neighbors over x years. Significance level: + ≤.1, *≤ .05, **≤ .01, ***≤.001.
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