¹ Deininger, Klaus and Squire, Lyn, ‘A New Data Set Measuring Income Inequality’, World Bank Economic Review, 10 (1996), 565–591CrossRefGoogle Scholar.

² See, for example, Li, Hongyi, Squire, Lyn and Zou, Heng-fu, ‘Explaining International and Intertemporal Variations in Income Inequality’, Economic Journal, 108 (1998), 26–43CrossRefGoogle Scholar; Chong, Alberto, ‘Inequality, Democracy, and Persistence: Is There a Political Kuznets Curve?’ Economics & Politics, 16 (2004), 189–212CrossRefGoogle Scholar; and Reuveny, Rafael and Li, Quan, ‘Economic Openness, Democracy, and Income Inequality: An Empirical Analysis’, Comparative Political Studies, 36 (2003), 575–601CrossRefGoogle Scholar.

³ Gradstein, Mark and Milanovic, Branko, ‘Does Liberté = Egalité? A Survey of the Empirical Links between Democracy and Inequality with some Evidence on the Transition Economies’, Journal of Economic Surveys, 14 (2004), 515–537CrossRefGoogle Scholar, p. 528.

⁴ For Asia, see Birdsall, Nancy, Ross, David and Sabot, Richard, ‘Inequality and Growth Reconsidered: Lessons from East Asia’, World Bank Economic Review, 9 (1995), 477–508CrossRefGoogle Scholar; for Latin America, see Székely, Miguel, ‘The 1990s in Latin America: Another Decade of Persistent Inequality, but with Somewhat Lower Poverty’, IADB Working Paper No. 454 (Washington, D.C.: Inter-American Development Bank, 2001)Google Scholar.

⁵ UNO-WIDER (World Institute for Development Economics Research), World Income Database (WIID), Version 2 (Helsinki: World Institute for Development Economics Research of the United Nations University/UNDP, May 2007). The DS dataset contains 2,634 observations versus 4,982 for WIID. The sample selection criteria (discussed later) determine the effective increase in observations. Our dataset probably contains a 25–40 per cent increase in country/year observations vis-à-vis most studies using DS.

⁶ In the longer working paper version (available on SSRN), ‘Does Democracy Reduce Inequality: If So How?’, interested parties can find a more in-depth examination of the mechanisms.

⁷ Most people who argue that inequality affects the birth (and death) of democracy believe elite hostility to democracy stems from its redistributional threat. See, for example, Boix, Carles, Democracy and Redistribution (Cambridge: Cambridge University Press, 2003)CrossRefGoogle Scholar.

⁸ The benchmark voter model is Meltzer, Allan and Richard, Scott, ‘A Rational Theory of the Size of Government’, Journal of Political Economy, 89 (1981), 914–927CrossRefGoogle Scholar. For its application to political regimes, see Acemoglu, Daron and Robinson, James, ‘Why Did the West Extend the Franchise? Democracy, Inequality, and Growth in Historical Perspective’, Quarterly Journal of Economics, 115 (1998), 1167–1199CrossRefGoogle Scholar. It should be noted that regime type does not map perfectly onto overall inequality without further assumptions about the distribution of factor income (pre-tax). To take one example: if factor income in a non-democracy were equally distributed, to start with no democratic process could reduce economic inequality. Because factor endowments may vary within regime-type, the democratization hypothesis may be on firmer grounds. That is, given initial endowments, democracy will reduce inequality from whatever be its pre-existing level.

⁹ Saint-Paul, Gilles and Verdier, Thierry, ‘Education, Democracy, and Growth’, Journal of Development Economics, 42 (1993), 399–407CrossRefGoogle Scholar.

¹⁰ Schumpeter, Joseph A., Capitalism, Socialism and Democracy (New York: Harper Brothers, 1942)Google Scholar; Rodrik, Dani, ‘Democracies Pay Higher Wages’, Quarterly Journal of Economics, 114 (1998), 707–738CrossRefGoogle Scholar.

¹¹ For a critique of the median-voter model, see Milanovic, Branko, ‘The Median-Voter Hypothesis, Income Inequality, and Income Redistribution: An Empirical Test with the Required Data’, European Journal of Political Economy, 16 (2000), 367–410CrossRefGoogle Scholar.

¹² Milanovic, , ‘The Median-Voter Hypothesis, Income Inequality, and Income Redistribution’Google Scholar.

¹³ Compare Kaufman, Robert and Segura-Ubiergo, Alex, ‘Globalization, Domestic Politics, and Social Spending in Latin America 1973–1997: A Cross-Sectional Time Series Analysis,’ World Politics, 53 (2001), 553–587CrossRefGoogle Scholar, against Mulligan, Casey, Gil, Robert and Sala-i-Martin, Xavier, ‘Do Democracies Have Different Public Policies than Nondemocracies?’, Journal of Economic Perspectives, 18 (2004), 51–74CrossRefGoogle Scholar.

¹⁴ See Chu, Ke-young, Davoodi, Hamid and Gupta, Sanjeev, ‘Income Distribution and Tax, and Government Social Spending Policies in Developing Countries’, WIDER Working Paper No. 214 (Helsinki: World Institute for Development Economics Research, 2000)Google Scholar.

¹⁵ Muller, Edward, ‘Democracy, Economic Development, and Income Inequality’, American Sociological Review, 53 (1988), 50–68CrossRefGoogle Scholar; Lake, David and Baum, Matthew, ‘The Invisible Hand of Democracy: Political Control and the Provision of Public Services’, Comparative Political Studies, 34 (2001), 587–621CrossRefGoogle Scholar.

¹⁶ See Engerman, Stanley, Mariscal, Elisa and Sokoloff, Kenneth, ‘Schooling, Suffrage, and the Persistence of Inequality in the Americas, 1800–1945’ (unpublished paper, UCLA, 2001)Google Scholar; Lindert, Peter, Growing Public: Social Spending and Economic Growth since the Eighteenth Century (Cambridge: Cambridge University Press, 2004)Google Scholar; Goldin, Claudia and Katz, Lawrence, ‘The Origins of Technology–Skill Complementarity’, Quarterly Journal of Economics, 113 (1998), 693–732CrossRefGoogle Scholar.

¹⁷ Katz, Lawrence and Autor, David, ‘Changes in the Wage Structure and Earnings Inequality’, in Orley Ashenfelter and David Card, eds, Handbook of Labor Economics, Vol. 3A (Amsterdam: Elsevier, 1998), 1463–1555Google Scholar.

¹⁸ Rodrik, , ‘Democracies Pay Higher Wages’Google Scholar. One of Rodrik’s measures – labour’s share of national income – is misleading; labour’s share is (typically) higher in the United States and United Kingdom than other OECD countries.

¹⁹ See Dew-Becker, Ian and Gordon, Robert, ‘Where did the Productivity Growth Go? Inflation Dynamics and the Distribution of Income’, Brooking Papers on Economic Activities, 2 (2005), 67–127CrossRefGoogle Scholar. The SSRN version of this article examines the labour mechanism using wage inequality data.

²⁰ Mathematically, the Gini coefficient is a reasonable measure of inequality; in practice, however, existing Ginis are based on different definitions of inequality, limiting their comparability.

²¹ See Sirowy, Larry and Inkeles, Alex, ‘The Effects of Democracy on Economic Growth and Inequality: A Review’, Studies in Comparative International Development, 25 (1990), 126–157CrossRefGoogle Scholar.

²² Bollen, Kenneth and Jackman, Robert, ‘Political Democracy and the Size Distribution of Income’, American Sociological Review, 50 (1985), 438–457CrossRefGoogle Scholar.

²³ An insightful critique can be found in Atkinson, Anthony and Brandolini, Andrea, ‘Promise and Pitfalls in the Use of ‘Secondary’ Data-sets: Income Inequality in OECD Countries as a Case Study’, Journal of Economic Literature, 39 (2001), 771–799CrossRefGoogle Scholar.

²⁴ We replicate Reuveny, and Li, , ‘Economic Openness, Democracy, and Income Inequality’. We also draw on Li, Squire and Zou, ‘Explaining International and Intertemporal Variations in Income Inequality’; and Chong, ‘Inequality, Democracy, and Persistence: Is There a Political Kuznets Curve?’Google Scholar. Reuveny and Li had roughly sixty Google citations as of May 2009. While Li, Squire and Zou had more citations, their written explanation does not match the years/countries in their models and their econometric models are not ones we favour. Their left-hand side variable begins as early as 1947, but their right-hand side measure of democracy (Freedom House) only appears in 1972; Hong Kong is supposedly one of their countries, but Freedom House does not publish ratings for it. They run a panel model with two time-invariant variables on the right-hand side, no lagged dependent variable, no time dummies and no country-fixed effects. They also report a rho ≈0.9, indicating substantial serial correlation. Chong uses a generalized method of moments (GMM) model, but countries/years in the panel are unclear and there is no explanation for the lag structure used as instruments, making it impossible to replicate. We also note that he used a one-step estimator, which is not robust to heteroscedasticity. He also claimed a non-linear relationship; we tested for this, using Polity2, and found nothing to report.

²⁵ Easterly, William, ‘Life during Growth’, Journal of Economic Growth, 4 (1999), 239–275CrossRefGoogle Scholar. Easterly does not specify how he cleaned the data in the paper Reuveny and Li reference. It seems that he meant only to include surveys with national coverage, regardless of the quality.

²⁶ The logit transformation unbounds the dependent variable.

²⁷ The WIID has four quality ratings: 1 indicates that the income concept is known and the survey methodologically sound; 2 indicates that either the income concept is problematic, or that the primary source is problematic or unknown; 3 indicates that both the income concept and source are problematic or unknown; 4 indicates a memorandum, based in many cases on unreliable sources.

²⁸ Adding Q3 and Q4 surveys and dropping the population matching restriction yields 1,201 country-year observations. Matching on Polity eliminates Barbados (2 observations), Bahamas (2), Hong Kong (5), Guyana (1), Luxembourg (1) and Puerto Rico (2). Using data for 1960 to the present day eliminates 17 observations.

²⁹ Mexico, for example, had three Quality 1 surveys in 2000, all of which were comparable on all seven dimensions; yet the calculated Gini coefficients ranged from 53.2 to 55.6.

³⁰ Li, Squire and Zou and Chong used five-year averages; Reuveny and Li used ten-year averages.

³¹ Honacker, James, King, Gary and Blackwell, Matthew, ‘Amelia II: A Program for Missing Data’Google Scholar, V1.1-34, 2008. See Table 5 in the SSRN version.

³² Unlike DS, WIID reports two Gini coefficients: a ‘preferred’ one and the original from the study. We made the ‘preferred’ Gini our benchmark, but also tested with the ‘reported’ Gini; with and without the recommended income adjustments (e.g. adding 6.6 to expenditure-based surveys and 3 to post-tax surveys); with and without the logit transformation; and with Reuveny and Li’s sample (when possible) and other samples (e.g., all countries, countries with more than observations). Note that the tax adjustment was applied to surveys based on disposable income and net earnings. The various permutations of the dependent variable were inconsequential in terms of our results for democracy; they did, however, affect our control variables.

³³ Marshall, Monty, Jaggers, Keith and Gurr, Ted, Polity IV Project: Regime Characteristics 1800–2004 (College Park: University of Maryland, 2007)Google Scholar; Freedom House, Freedom in the World (Panel Dataset, 2007)Google Scholar.

³⁴ Unless otherwise noted, data for the control variables come from the World Bank, World Development Indicators (Washington, D.C.: World Bank, 2007/2008)Google Scholar.

³⁵ Portfolio inflows are no longer reported for many countries; since the theoretical rationale for portfolio inflows was thin and it was never significant in their tests, we exclude it (gdp = gross domestic product).

³⁶ We favour Models 4 and 6 because the fixed effects are jointly significant.

³⁷ Results with other data samples are available from the author.

³⁸ While perhaps no measure of democracy adequately captures the (most) relevant theoretical concept of a leftward shift in the median-voter/citizen, we presume that moving up the Polity scale or down the Freedom House scale is a close approximation. The Polity measures are highly correlated with alternative measures, notably those found in Vananhen, Tatu, ‘A New Dataset for Measuring Democracy, 1810–1998’, Journal of Peace Research, 37 (2000), 251–265CrossRefGoogle Scholar. They have also faired reasonably well in head-to-head comparisons. But they are clearly imperfect, especially when interpreted linearly. See, for example, Hadenius, Axel and Teorell, Jan, ‘Same, Same – But Different: Assessing Alternative Indices of Democracy’ (unpublished paper, University of Uppsala, 2005)Google Scholar.

³⁹ We backtracked Polity to 1950 and ran an auto-regressive distributed lag model with 1–3 lags of Polity (i.e. up to T ₋₂₀); the joint significance of the lags was assessed with a Wald test. These models test the relationship between inequality and the average level of democracy over time.

⁴⁰ We tried to fit generalized method of moments (GMM) models with deeper lags of the relevant variables. Unfortunately, there were insufficient observations.

⁴¹ Endogenous selection is a potential threat, though perhaps not a grave one. The literature typically suggests that democracy and egalitarian income distributions are reinforcing (e.g., Boix, Democracy and Redistribution). If true, OLS would be biased in favour of finding a negative relationship between democracy and inequality, contrary to our non-finding. As a simple check for selection problems, we ran binary regressions (logit, probit and gompit) to estimate the determinants of democracy (0–1 dummy). In those tests (shown in the SSRN version), neither Gini nor Gini² had any predictive power in terms of determining which becomes a democracy – consistent with a recent analysis by Gassebner, Martin, Lamla, Michael and Vreeland, James, ‘Extreme Bounds of Democracy’ (unpublished paper, Swiss Federal Institute of Technology, Zurich, 2008)Google Scholar.

⁴² We present models with both lagged levels and first differences for Polity given that some theories suggest simultaneous changes, while others suggest an equilibrium relationship. Models without any first differences and models with a full set of first differences can be found in the SSRN version.

⁴³ For a summary, see Katz, and Autor, , ‘Changes in the Wage Structure and Earnings Inequality’Google Scholar.

⁴⁴ The data come from Barro, Robert and Lee, Jong-Wa, ‘International Data on Educational Attainment: Updates and Implications’, Oxford Economic Papers, 53 (2001), 541–563CrossRefGoogle Scholar. They provide multiple measures of education. Theoretically, a measure reflecting the dispersion of human capital should be most relevant (e.g., the difference between the percentage of people with no schooling and those with university education); empirically, secondary education completed fits the data well. Changing the measure of human capital or excluding it altogether does not change the democracy result.

⁴⁵ Results from the first stage are available.

⁴⁶ The SSRN version gives details of these controls.

⁴⁷ See Bénabou, Roland, ‘Inequality and Growth’, in Ben Bernanke and Julio Rotemberg, eds, NBER Macroeconomics Annual (Cambridge, Mass.: MIT Press, 1996), pp. 11–74Google Scholar.

⁴⁸ To retain observations, negative values for inflation were replaced with infinitesimal positive values (e.g., 0.0000009) in a way that preserved the rank order (GDP = Gross Domestic Product.)

⁴⁹ Establishing a preferred specification posed a challenge because missing data changed the sample; secondary education and female labour force participation particularly constrained the sample. Secondary education reduced the width, while female labour force participation reduced the time dimension (to post-1985 observations). We choose to include secondary education in the reported results, despite the loss of observations, because it was one of only three relatively robust controls, with inflation (logged) and manufacturing value-added being the others. The results for a fourth one variable GDPPC (logged) depended on the other conditioning variables in the model. None of the other control variables consistently had T-stats above 1. Because changing the control variables (within our universe of potential covariates) does not alter the conclusions about Polity/democracy, models with non-robust controls have been relegated to the SSRN version.

⁵⁰ Dropping the lagged DV and/or the unit FE does not alter this conclusion. Neither does changing the definition of democracy (Table 3B in the SSRN version) or moving to any other data configuration.

⁵¹ We ran multiple IV specifications, ranging from merely including the lag of polity as an instrument for polity to specifications in which most right-hand side variables, including the lagged DV, were instrumented with their lags. With IV regressions, the point estimate on Polity was generally positive, even with the most favourable data sample.

⁵² Spain probably comes closest. Even there, however, the decline was gradual, modest and ephemeral (see Leandro Prados de la Escosura, ‘Inequality, Poverty and the Kuznets Curve in Spain, 1850–2000’ (Working Papers in Economic History 07–13, Universidad Carlos de Madrid, 2007)Google Scholar.

⁵³ See Förster, Michael, Jesuit, David and Smeeding, Timothy, ‘Regional Poverty and Income Inequality in Central and Eastern Europe: Evidence from the Luxembourg Income Study’, UNO-WIDER Working Paper No. 65 (Helsinki: World Institute for Development Economics Research of the United Nations University, 2003)Google Scholar.

⁵⁴ Honacker, et al. , ‘Amelia II: A Program for Missing Data’Google Scholar.

⁵⁵ Several reasons for the different findings stand out. First, Easterly’s version of DS contained some unusual observations, notably for Argentina. These observations appear to have been influential (omitting them reduces the significance level of Polity, even using just pre-1997 data). Secondly, we added additional years for a number of countries, generating many of the sign switches in Table 3. Finally, we added more countries (Table 4).

⁵⁶ Mulligan et al., ‘Do Democracies Have Different Public Policies than Nondemocracies?’; Ross, Michael, ‘Is Democracy Good for the Poor?’ American Journal of Political Science, 50 (2006), 860–874CrossRefGoogle Scholar; Scheve, Ken and Stasavage, David, ‘Institutions, Partisanship, and Inequality in the Long Run’, World Politics, 61 (2009), 215–253CrossRefGoogle Scholar.

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⁵⁸ See, for example, Landa, Dimitri and Kapstein, Ethan, ‘Inequality, Growth and Democracy’, World Politics, 53 (2001), 264–296CrossRefGoogle Scholar.

⁵⁹ Laver, Michael and Hunt, W. Ben, Policy and Party Competition (London: Routledge, 1992)Google Scholar.

⁶⁰ Roemer, John, ‘Why the Poor Do Not Expropriate the Rich: An Old Argument in New Garb’, Journal of Public Economics, 70 (1998), 399–424CrossRefGoogle Scholar.

⁶¹ The relationship between democratic forms and inequality is worth exploring. We confined ourselves to the democracy/non-democracy distinction for several reasons: first, it is consistent with the theories we worked with; secondly, the data do not readily lend themselves to such an analysis because changes in the form of democracy are rare. For contrasting views, see: Iversen, Torben and Soskice, David, ‘Electoral Institutions and the Politics of Coalitions: Why Some Democracies Redistribute More than Others’, American Political Science Review, 100 (2006), 165–181CrossRefGoogle Scholar; and Aidt, T. S., Dutta, Jayasri and Loukoianovo, Elena, ‘Democracy Comes to Europe: Franchise Extension and Fiscal Outcomes 1830–1938’, European Economic Review, 50 (2006), 249–283CrossRefGoogle Scholar.