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Inequality, Economic Development, and Democratization

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Abstract

Although multiple theories suggest that economic development and inequality somehow affect democratization, these claims have received only limited empirical support. I contend that much of the confusion stems from the implicit assumption held by the literature that development and inequality affect democratization independently of one another. In this paper, I argue that the effect of income distribution on democratization is in fact contingent on the income level: in middle-income countries inequality fosters democratization; in rich countries, however, it harms democratization. Using a data set covering almost all autocracies between 1960 and 2007, I find evidence consistent with my hypothesis.

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Notes

  1. One partial exception is Reenock, Bernhard, and Sobek (2007) who show that deprivation only destabilizes middle-income democracies. However, this study looks at democratic breakdowns—not democratization—and focuses on deprivation, not inequality. Przeworski (2006) argues that inequality is more destabilizing in poor democracies. Again, Przeworski (2006) does not look at the question of democratization, and factors that affect democratization and consolidation are often different (e.g., Przeworski et al. 2000). Boix (2003) argues that the effect of inequality depends on asset mobility—even though his empirical tests do not account for a conditional relationship—which depends partially on development.

  2. In poor countries, inequality is not even significantly related to deprivation (Reenock, Bernhard and Sobek 2007).

  3. Autocracies are assumed to represent the interests of the capital class, and democracies those of the median voter who is a member of the labor class.

  4. There are also other theories on the relationship between inequality and democratization that do not rely on the role of redistribution, such as that of Ansell and Samuels (2010, 2013, 2014). The work of Ansell and Samuels is discussed in more detail below.

  5. These authors, however, do not exclusively rely on the redistribution mechanism.

  6. For studies finding no relationships see Bollen and Jackman (1985); Papaionannou and Siourounis (2005); Houle (2009, 2013), a negative relationship see Muller (1988), (1995); Boix and Stokes (2003); Boix (2003), a positive relationship see Ansell and Samuels (2010, 2014); Midlarsky (1992), and an inverted U-shaped relationship see Burkhart (1997).

  7. Cases in which mass mobilization occurred but did not oppose groups from different social classes are categorized as non-distributive conflict transitions (e.g., Ukraine 1991). These transitions clearly do not provide support for the causal mechanisms of inequality theories.

  8. This cut-off point as well as that between intermediate and high income levels ($8,000) have been estimated in the regressions reported below (see model 2 of Table 3).

  9. This argument is consistent with the results of Fearon and Laitin (2003), according to which GDP per capita decreases the likelihood of civil war by improving the ability of the state to repress insurgents.

  10. Note that my argument does not imply that the observed level of violence should be higher in rich autocracies, or that autocracies at low/middle levels of development should be less repressive. While, for example, the DRC has experienced more state violence than Singapore throughout its history, one could make the argument that regime outsiders could more easily dislodge the regime in the former than in the latter.

  11. In Poland, for example, while the Solidarity movement was clearly based on the industrial working class (Haggard, Kaufman and Teo 2012), its aim was to replace communism with capitalism (which eventually led to an increase in inequality). Similarly, the transition to democracy in South Korea has usually been perceived as caused by an increase in income that led to demands for political rights rather than because the masses wanted more redistribution (Huntington 1991; Inglehart and Welzel 2009). Although mass mobilization did play a crucial role, it involved cross-class mobilization as well as elements of the middle class (Haggard, Kaufman and Teo 2012). Lastly, despite its relatively high per capita income, Suriname is heavily aid-dependent. Although class mobilization did play a central role during the transition, so did international actors, in particular the Netherlands and the United States that suspended all aid following massive military repression (Haggard, Kaufman and Teo 2012).

  12. See also (Calhoun 1982; Feierabend et al. 1969; Haas and Stack 1983, 1967, 2007, 1989).

  13. My argument is also consistent with the findings of Reenock, Bernhard and Sobek (2007), who show that deprivation destabilizes middle income democracies, but not rich or poor ones. Although these authors are primarily interested in democracies, not autocracies, their findings directly connect to mine, since they imply that distributional issues are most destabilizing at middling GDP per capita levels.

  14. The absence of distributional conflict during a transition does not necessarily imply that inequality had no role in explaining why the transition occurred. Since, everything else being equal, the different factions of the elites have more to lose economically when inequality between the elites (as a whole) and the masses is large, transitions through non-distributive conflict may be facilitated by low levels of inequality.

  15. None of these averages are statistically significantly different from one another.

  16. Houle (2009) argues that these predictions by Acemoglu and Robinson (2006) are driven by the assumption that the cost of repression for the elites is binary, i.e., (1) the elites either repress or do not repress (in which case the cost of maintaining an autocracy is zero); and (2) when they repress the cost of repression does not depend on inequality.

  17. Summary statistics are provided in Table A1 of the online appendix.

  18. Acemoglu and Robinson (2006) and Przeworski et al. (2000) use the version of Rodrik (1999).

  19. In the main analysis, I use the version of Houle (Forthcoming) who imputes values for nearly all countries. As shown in section 3 of the Online Appendix, my results are robust to the use of the original data of Ortega and Rodriguez (2006) (see Table A2).

  20. Freeman and Quinn (2012) have recently pointed to some problems with the use of capital shares. I address these issues in section 1 of the Online Appendix and provide more information on capital shares and the problems related to the use of its main alternatives.

  21. I use Amelia II to impute missing values. See section 3 of the Online Appendix for detail.

  22. Soifer’s (2013) indicator takes the value one if a state has administrated a census within the last 10 (rather than 12) years. However, when I use 10 years, the proportion of countries that lack extractive capacity is very high (27.65 %). This proportion drops to 20.03 % when I use 12 years. As explained below, I expect only the very poorest countries to completely lack the capacity to redistribute. Hanson (2015) also uses the administration of a census to measure state capacity.

  23. The COW dataset covers security forces that can also be used to combat foreign armies.

  24. Oil is taken from Haber and Menaldo (2011) and Muslim and Ethnic Fractionization from Przeworski et al. (2000).

  25. These are calculated using the codes provided by Matt Golder (https://files.nyu.edu/mrg217/public/interaction3.pdf). Control variables are set at their mean or median. In nonlinear models, the marginal effect of a variable varies with its level. Therefore, Fig. 2 evaluates the marginal effect of capital share at its mean. I also evaluated the marginal effect of capital share across its full range (minimum and maximum values) using other marginal effects plots. The shape of the relationship is unchanged (available upon request).

  26. Among the very poorest countries (GDP per capita below $400), the relationship is positive. However, very few countries are that poor. In fact, there has been only one democratization among such countries in the sample (Burundi 2005). Moreover, as shown in Fig. 3, even in countries with a GDP per capita as low as $600, there is actually no relationship between inequality and democratization.

  27. Observations from countries that remained authoritarian during the full period (e.g., Saudi Arabia) and years during which no autocracy within the sample democratized (e.g., 1964) are dropped.

  28. In section 6 of the Online Appendix, I test whether democratization in the future affects inequality and income levels today (Tables A11 and A12). Results show that it does not. This is essentially a test of whether the prospect of democratization affects inequality and income, which is among the main paths through which they could be endogenous to democratization.

  29. Data on financial openness is from Freeman and Quinn (2012), agricultural share of GDP from the World Bank, population from Haber and Menaldo (2011), and those on the other variables from Przeworski et al. (2000).

  30. Boix (2003) makes the argument that the effect of inequality on democratization may be contingent on capital mobility, although his estimations do not account for a conditional effect. Therefore, I run models in which the effect of inequality is conditioned by the agricultural share of GDP (Table A16).

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Acknowledgments

Winner of the 2011 Kellogg/Notre Dame Award for best paper in comparative politics presented at the MPSA convention. Earlier versions of this paper were presented at the Annual Meeting of the Midwest Political Science Association, Chicago, at the Annual Meeting of the International Political Economy Society, College Station TX, and at the Comparative Politics Workshop, University of Rochester. I gratefully acknowledge comments and suggestions from Alexandre Debs, Mark Fey, Jennifer Gandhi, Gretchen Helmke, Timothy Hicks, Tasos Kalandrakis, Mark A. Kayser, Jeremy Kedziora, G. Bingham Powell, Curtis Signorino, Randall Stone, Olesya Tkacheva, Jay Ulfelder, Milan Svolik and Jeffrey Weber. I am also grateful to Jonathan Hanson and Rachel Sigman, and Hillel Soifer for sharing data. I would also like thank Jessica Fortin for discussions on different measures of state capacity. All errors are mine.

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  1. Department of Political Science, Michigan State University, East Lansing, MI, 517-353-7970, USA

    Christian Houle

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Houle, C. Inequality, Economic Development, and Democratization. St Comp Int Dev 51, 503–529 (2016). https://doi.org/10.1007/s12116-016-9220-z

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