Democracy,policy,and inequality: Efforts and consequences in the developing world

Abstract

Are democracies better at delivering material benefits to the poor? What would be a key mechanism to translate social demands for redistribution to more egalitarian outcomes in the developing world? Analyzing an unbalanced pooled time-series dataset for domestic government spending, welfare state generosity, and income inequality in the developing world from 1971 to 2008, we find that (partial) democracies promote higher levels of domestic government spending, but they are not associated with higher levels of welfare state generosity. Our results also indicate that in developing countries, welfare state generosity is related to more equality. However, domestic government spending does not have any significant impact on income inequality even in democracies.

Keywords

Democracy inequality spending welfare generosity developing countries

Introduction

Are democracies better at delivering material benefits to the poor? If so, what would be a key mechanism to translate welfare demands to better redistributional outcomes in the developing world? Many theoretical studies have argued that democracy is somehow related to lower levels of income inequality (Lenski, 1966; Lipset, 1959; and see, particularly, Sirowy and Inkeles, 1990, for a review). The main mechanism addressed by the conventional wisdom to explain the relationship between democracy and income inequality is arguably the increase in social pressures for redistribution. A democratic government is more subject to demands from citizens. In theory, by promoting political equality, democracy provides various groups, such as interest groups, labor unions, and political parties, with open spaces of political competition to represent their own interests and welfare.

Despite theoretically less-controversial reasoning for the negative effect of democracy on inequality, these arguments have received little empirical support. Not only have very few studies attempted to explain the effect of regime type on temporal and cross-sectional variations in income inequality (Gasiorowski, 1997; Huber et al., 2006; Nel, 2008; Reuveny and Li, 2003), but the empirical results of those studies are controversial. Given that the politics of income inequality has been a crucial issue of concern and discussion for several areas of academia and policy, it is surprising that little scholarly attention has been devoted to this topic. More important, although a number of studies hypothesize that democracy will influence inequality, the causal pathways identified by analysts still remain open to question.

This paper takes off from this unknown. Building on the previous literature on the politics of inequality, a key contribution of the analysis we develop is to clarify how democracy may shape various policies and thereby influence levels of income inequality. Following Rueda’s (2008) analytical framework, we begin with separating the effect of democracy on policy (efforts) from the effect of policy on income inequality (consequences). Democracy cannot affect the distribution of income automatically, but accomplishes this mainly through the use of a variety of policies. Therefore, to accurately understand the influence of regime type, one must distinguish between the effect of democracy on policy and of policy on income inequality.

When analyzing the effects of different policies, it should be clearly identified that their redistributive impacts may vary. It can be argued that some policies are more effectively associated with income inequality than others. To make clear the veiled dynamics of different policies, here we consider two overall policy areas that are theorized as having an influence on income inequality: the size of domestic government spending and the generosity of the welfare state.

The remainder of the paper is organized as follows. In the next two sections, we review the theoretical and empirical studies on the issue of the link between democracy and policy, and then we develop the theoretical framework of our analysis. Following this, the next two sections describe the dataset and empirical models we have constructed to test the hypotheses generated by this framework. The subsequent sections present and discuss our empirical results, and we conclude by addressing issues for further inquiry.

Theories: democracy and redistribution

Many scholars have developed guiding political economic models in which democracies produce more public goods and improve an egalitarian distribution of income by illuminating the mechanisms of the democratic institution itself, such as electoral competition and the expansion of political participation (Acemoglu and Robinson, 2006; Boix, 2001, 2003; Bueno de Mesquita et al., 2003; McGuire and Olson, 1996; Meltzer and Richard, 1981).

A simple but important analytical model, relating democratic institutions and redistribution, comes from Meltzer and Richard (1981), who focus on the effects of electoral competition.¹ This model assumes that the median voter is the critical voter in determining the size of government, which is measured by the share of income redistributed. It implies that the size of government hinges on the relationship between mean income and the income of the decisive voter, depending on the regime types. Whereas before the spread of the franchise the median voter may be one of the rich or the upper class, after democratization the median voter may have a below-average income in an unequal society, one of the poor who favors higher taxes and more redistribution. Therefore, compared with authoritarian regimes, democratic governments are likely to provide more public goods to those with low income, which may then redistribute incomes more equally.

In an extension of the model of Meltzer and Richard (1981), Boix (2001, 2003) and Acemoglu and Robinson (2006) have developed frameworks for the nexus between democracy and redistribution. Analyzing the dynamic of the advent of democracies and authoritarian regimes as a consequence of different levels of inequality and different mixes of assets in the economy, Boix (2003) builds a comprehensive theory to explain the distributional results of different political regimes: Democracies prefer more economic redistribution because they support a broader range of interests of the masses, whereas authoritarian regimes do not because they bolster the interests of the elite. Examining the creation and consolidation of democracy, Acemoglu and Robinson (2006) also construct a sophisticated yet simple model that suggests democracy is preferred by the majority of citizens and is more prone to redistribution.

Another line of inquiry investigating the redistributive effects of democracy focuses on lobbying and the influence of interest groups and activists who provide political resources to certain parties in exchange for policy compromises.² The classic studies of the existence and role of interest groups date back to Olson (1965) and Becker (1983). Organized interest groups contribute to parties and politicians in a more or less direct attempt to exact an expansion of expenditures and to influence their policy formulation through a variety of political actions. Lobbying and campaign contributions are prime examples. Thus, as the number of interest groups increases, we may begin to expect that the level of government spending will rise (Mueller and Murrell, 1986), and also that as interest groups overcome the collective action problem, they can bias policy significantly toward their positions more easily than non-organized groups can.

This model of lobbying implies, first, that redistribution is likely to be greater in democracies than non-democracies because, in principle, democracies produce larger numbers of powerful, independent interest groups, and, second, that the distribution of government spending becomes vastly unequal in societies with a number of well-defined interest groups because lobbying draws the government to ignore the welfare of unorganized individuals. Regarding the first implication, studies of interest groups argue that, intuitively, organized interest groups receive more benefits than unorganized individuals, but state that lobbying does not distort the provision of public goods, which influences unorganized individuals just like anyone else, as beneficiaries, because “lobbies might plausibly consist of individuals with a high preference for the public good, who have a higher stake on the policy outcome and hence are more likely to overcome the free-rider problem of getting organized” (Persson and Tabellini, 2000: 174). As a consequence, lobbying brings about higher levels of government spending.

Empirical findings

Most of the empirical findings from a variety of samples are consistent with their theoretical inference, that is, the positive link between democracy and larger government spending.³ Lindert (1994), looking back to the 19^th century (1880–1930), reaches the conclusion that the expansion of a voting franchise helps interpret the rise of redistribution among mostly OECD countries after World War I. The analysis of US time-series data (1950–1988) by Husted and Kenny (1997) shows that the rise of voting rights is positively associated with the growth of redistributive programs in state and local governments in the USA. A sequence of the empirical work on Latin America also suggests that a democracy funds welfare spending on some subcategories at higher levels than a non-democracy does. Finally, from his sample of 44 African countries, Stasavage (2005) shows robust empirical evidence that democracies have spent more on education.

Besides these region-specific studies, some cross-regional studies support the claim that democracies are likely to produce more government spending than authoritarian regimes. They find evidence that, with respect to increasing globalization, democracies ensure higher levels of social welfare than authoritarian regimes, based on panel data for 65 developing and developed countries (Adsera and Boix, 2002), for developed countries (Mahler, 2004), for 57 developing nations (Rudra and Haggard, 2005), and for all developing countries (Nooruddin and Simmons, 2009).

The argument: The effects of policy on inequality in developing countries [?]

The starting point for this analytical inquiry into the causes of income inequality is the proposition that regime type influences income inequality. Democracies can have an impact on the distribution of income through the design and implementation of policy. The argument supporting the existence of a connection between regime types and income inequality can be expressed in very simple terms. By preferring more government spending or favoring a higher level of welfare state generosity, for example, democracies are likely to compensate market losers and, more generally, to boost the relative living conditions of the poor.

Yet, this may not be the case in countries that have not had enough time to make political institutions work. In the context of new democracies, it is likely that the procedures of making decisions and of carrying out policies are neither as transparent as assumed nor as successful as those in old democracies. It is likely that political institutions may not be effective or strong enough to block the influence of economically and politically privileged groups. Even when governments have the best intentions to increase redistribution, it is likely that welfare expenditures are prone to disproportionately benefit upper-income groups and fail to serve the intended goal of alleviating inequality.

Political scientists, particularly specialists in Latin America, have expressed some skepticism about the positive effects of size of the welfare state in Latin America (Ferreira et al., 2004; Huber, 1996). Social welfare programs can be helpful for the poor as long as they are tied to universalistic rules to better serve the most vulnerable groups. However, such programs do not have progressive effects on income inequality in developing countries because social insurance and social security systems generally target people with formal sector employment. In Latin America in particular, welfare state policies “increase the discretion of political leaders and bureaucrats with regard to the allocation of resources and thus the incentives for patronage and corruption” (Huber, 1996: 181).

The implication is that redistributional politics, that is, democratic governments’ efforts (policy) and their economic outcome (inequality), in developing countries might not be monolithic. Diffuse policies may lead to the same consequences, and the same policy may bring about different consequences, depending on various political arrangements and the extent of the effectiveness of political institutions.

Accordingly, we wish to make one basic point concerning the relationship between regime type and income inequality. As mentioned above, democracies cannot influence the distribution of income directly, but depend on the use of a variety of policies. To arrive at a more accurate picture of redistribution across developing countries, it is critical to first inspect whether regime type influences specific policies to accomplish any degree of income distribution, and then whether these policies influence income inequality. To solve the puzzle of whether politics produces changes in redistributional efforts and outcome among developing countries, we focus on two policies that are clearly assumed to have an effect on levels of income inequality: the size of domestic government spending and the generosity of the welfare state.

The reasons for considering these two policies as the product of democracies seem clear. Following the two lines of inquiry mentioned above, it would be reasonable to expect that democracies are likely to have a larger government and to spend more to provide public goods and services to the relatively poor majority due to the mechanism of elections and the power of interest groups. How these policies influence income inequality, in particular, across developing countries is rather ambiguous, however. Of course, little needs to be said about the expectation that welfare state generosity would promote the egalitarian distribution of income. As we shall discuss later, it is operationalized to gauge democracies’ efforts to target relatively poor people.

However, as for government spending, we want to emphasize two contradictory expectations. As mentioned earlier, the second implication of the interest group theory concerns the disproportionate allocation of government spending in democracy. This theory posits that benefits are concentrated on a few organized groups, but the costs are dispersed throughout the society at large through generalized taxation. Suppose a politician has the authority to distribute some budgetary amount to two different groups and one group is politically well defined but the other is not. In this context, government spending is likely to be unequally distributed, that is, the organized group is overprovided and the non-organized group is underprovided. The organized lobbying groups gain more if their members have a higher interest in a policy’s impacts or if politicians pay more attention to lobbying groups’ preferences to maximize expected votes and win elections. Accordingly, government spending may not have positive ramifications for income inequality unless a greater diversity of interests is represented in the policymaking process, regardless of their power.

Also, if everyone receives the same transfer (a universal flat-rate benefit), as Meltzer and Richard (1981) assume, increased government spending in democracies would be expected to reduce inequality. However, if this is not the case, that is, if the phenomenon of “concentrated benefits and dispersed costs” (Persson and Tabellini, 2000: 160) derived from a model of lobbying comes true, there will be no guarantee that higher levels of government spending will boost the actual living conditions of the poor. Moreover, it would be more common to witness the phenomenon of unequal redistribution among the developing world than the advanced world.

The theoretical predictions outlined in the previous sections are summarized in Figure 1. The figure shows why it is critical to distinguish between aggregate levels of policy and relevant allocations. In a nutshell, if all else is equal, democracies are more likely to increase government spending and welfare state generosity, and welfare generosity is more likely to reduce income inequality. The theoretical hypothesis regarding the effect of government spending on inequality is somewhat ambiguous, for the reasons discussed earlier.

Figure 1.

Theoretical expectation: regime type, policy, and income inequality.

The variables of interest

Income inequality

The dependent variable, income inequality, comes from Solt’s (2009) Standardized World Income Inequality Database (SWIID). By alleviating the chronic problem of trade-offs between comparability and coverage among existing income inequality datasets, such as the Luxembourg Income Study (LIS) and the World Income Inequality Database (United Nations University-World Institute for Development Economics Research [UNU-WIDER]), SWIID enlarges the comparability of Gini coefficients for the broadest available set of countries and years from 1960 to the present (4540 observations from 153 countries). Therefore, this dataset is more appropriate for extensive cross-sectional studies, especially for developing countries.

Domestic government spending

We employ total central government spending as a fraction of gross domestic product (GDP) derived from the International Monetary Fund (the International Financial Statistics [IFS] database). Most studies on government spending pay little attention to the components that influence the scope of military spending. Instead, our analysis is based on the nature of domestic government spending. Given that our concern is redistributional discrepancies among regime types with regard to the role of government, we measure domestic government spending by excluding military spending from total government spending. Two critical reasons are worth noting. First, in theory, given that military spending is the general case of a public good and is dependent on external military tension with other countries, such as the Cold War, it is not associated with a government’s efforts toward compensating the poor in the market.

Second, in practice, the developing world may be the case in which inferences from total government spending is problematic. Figure 2 displays the percentages of democracy and total democracy, as well as the mean of military spending among developing countries from 1960 to 2008. As Figure 2 presents, the global wave of democratic transition was accompanied by a global transformation, the end of the Cold War. The percentage of total democracies has increased from around 20% in the early 1970s to more than 60% in the 21^st century (from 10% to more than 30% for democracy). In contrast, the mean of military spending reached its zenith in the mid-1980s (4.94% in 1984) and has dwindled consistently (2.15% in 2008), which indicates a trend opposite to that of global democratic transition. Therefore, we might underestimate democracies’ public spending efforts if we do not account for the worldwide pattern of decreased military spending. Table 1 confirms our concern by reporting the means of military spending of various regime types. Democracies clearly spend less on military affairs than other regime types do: On average, non-democracies (4.14%) are prone to spend more than double the amount democracies spend (1.91%).⁴

Figure 2.

Trends of democratization and the average of military spending in developing countries, 1960–2008.

Table 1.

Military spending in developing countries by regime type, 1960–2008.

Regime Type	Obs	Mean	Std. Dev.	Max
Democracy	1062	1.91	1.39	9.1
Partial democracy	1006	2.38	1.63	11
Non-democracy	2811	4.14	4.44	36.5

In this analysis, between two often-used datasets from the US Arms Control and Disarmament Agency (ACDA) and Stockholm International Peace Research Institute (SIPRI), we employ the data from SIPRI because it systematically offers standardized amounts (military spending/GDP) for a large number of countries and consecutive years.

Welfare state generosity

Total government spending and social spending as a percentage of GDP have been widely used as the measures of the welfare state because they are available, easy to compare, and differ across countries and time. Although these may be sound indicators for some purposes, scholars have also acknowledged that there are clear drawbacks in their potential to measure welfare state generosity (Castles, 2002; Clayton and Pontusson, 1998; Scruggs, 2008). Their essential shortcomings, among others, concern the fact that such measures mostly fail to take account of the size of the recipient population, differential rates of economic growth, and tax systems. That is, even though public spending ratios are constant, the extent of real benefits recipients will receive from welfare programs can be reduced if social demand for welfare is increasing as a result of rising levels of insecurity or aging, or if the tax treatment of transfers is regressive (see Scruggs, 2008: 63–65).

Some scholars have developed more refined categories of social spending to evaluate welfare state generosity across advanced industrial countries (e.g. Castles, 2002; Scruggs, 2008; Scruggs and Allan, 2006). Unfortunately, however, these alternatives are particularly unsuited for the study of the welfare state in the developing world due to lack of availability. In this analysis, following Iversen and Cusack (2000) and Rueda (2008), we measure welfare state generosity as the ratio of social transfers to government expense over the ratio of the non-working to the total population. This is better than measures about absolute levels of spending because it takes into consideration at least one factor that may cause a measurement bias, such as the size of the dependent population. The data on the ratio of social transfers to government expense and the ratio of non-working to the total population come from World Development Indicators.⁵

Democracy

To empirically measure a democracy in our sample from 1971 to 2008, we depend on the Polity IV dataset (Marshall and Jaggers, 2010). Because the Polity IV dataset does not provide a dichotomous category of democracy, researchers are required to draw an arbitrary cut point for where democracy starts. To develop the trichotomous measures of democracy, we employ two dummy variables: Partial Democracy is coded 1 for any country scored from 1 to 7 on the Polity Scores index, 0 for others; and Democracy is coded 1 for any country scoring 8 or above, 0 for others. Polity IV offers the reasoning behind our selection of 8 and above as Democracy. In the dataset, 8 points is the threshold to be a “mature and internally coherent democracy” (Marshall and Jaggers, 2010, Dataset Users’ Manual).

Finally, to test the long-term effect of democratic experience, we include two age variables, Age of Total Democracy (log), including both partial democracy (scoring from 1 to 7 on Polity2) and democracy (from 8 to 10) and Age of Democracy (log) (only democracy, excluding partial democracy), that are sums of years where (partial) democracy has been maintained without a break. We count age of democracy in a certain country from the first year with uninterrupted positive values (total democracy) or 8 and above (democracy) on the Polity2 index up to 2008. We employ the method of logarithmic transformation because it can be assumed that the impact of age of democracy is not linear.

Control variables for the analysis of policy

Alongside the key variables of interest, a number of economic and demographic control variables traditionally used in the government spending literature are included. Globalization in this article is operationalized by the level of Trade integration and FDI inflows as a percentage of GDP: Here, the measure of trade openness is the sum of the total imports and exports as a share of a country’s GDP (trade openness = [imports + exports]/GDP), FDI inflows is the value of net inflows of FDI (foreign direct investment) as a share of a country’s GDP. To account for Wagner’s Law, we control for the GDP, defined as the log of Gross Domestic Product per capita (in constant dollars, Chain Index, expressed in international prices, base 2000), taken from the Penn World Tables. For the possibility of the curvilinear relationship between them, the square of GDP, GDP², is added. These two variables are centered to control for collinearity.

We include three demographic control variables, the percentage of Elderly Population (65 years old or older), the percentage of the Youth Population (under 15 years of age), and Total Population (log), because health care, social security, and education spending are sensitive to how many people are old or young. Also, we account for population to control for a negative association between the burden of government and country size due to economies of scale in the service of public goods (Alesina and Wacziarg, 1998).The data for all the aforementioned control variables, except for GDP per capita, come from The World Bank World Development Indicator.

To address the possibility of a spatial contemporaneous correlation of errors, we introduce time-specific factors into the models in the form of a dummy variable for the 1^st Oil Crisis (1973–74) and the 2^nd Oil Crisis (1979–80), except for oil-exporting countries. Given that it is plausible to expect that the impact of an increase in oil prices differs between oil-exporting and oil-importing countries, we develop the variable of Oil Exporter. Finally, to take into account the effects of the different type of political and economic regimes, we use a dummy variable for Left Totalitarian countries because they have claimed and demonstrated universal provision of basic social insurance and services through the state.

Control variables for the analysis of income inequality

Following previous pooled time-series analyses (Alderson and Nielsen, 2002; Huber et al., 2006; Nielsen and Alderson, 1997; Rudra, 2004), we include several economic and demographic control variables to capture the impacts strongly related to inequality. In addition to Trade, FDI inflows, Youth Population, GDP, and GDP², another control variable is Sector Dualism, which we measure as the absolute difference between the percentage of the labor force in agriculture and agriculture’s share of the GDP. Previous researchers (Alderson and Nielsen, 2002; Huber et al., 2006; Nielsen and Alderson, 1997) have found evidence that sector dualism is significantly likely to have a positive impact on overall inequality. The data for Sector Dualism come from World Development Indicator.

With respect to distributional outcomes, some regional implications are of particular importance. We include five regional dummy variables, Post-Communist, Latin America, East Asia, South and Southeast Asia, and Africa, to control for historical, region-specific effects on income inequality, treating the rest of the countries as the reference category (see Yi, 2013, for more discussion).

Model specification

We test the hypotheses about the relationships among regime type, policy, and income inequality with an unbalanced, pooled time-series cross-sectional data of spending and Gini that cover 110 and 69 developing countries, respectively, during the period 1971–2008.

To control for the possibility of non-spherical disturbances, Beck and Katz (1995) introduce an econometric technique that runs an ordinary least squares (OLS) regression with the lagged dependent variable plus unit and period dummies and calculates panel-corrected standard errors. Whether unit dummies and a lagged dependent variable should be included in the model is, however, still an open question, because running an OLS model with them may remove some of the non-spherical disturbances problem, but it may also kill much of the beneficial story about the variables of interest. Thus, this widely used technique may run the risk of throwing out the substantial and theoretical baby with the residual’s and methodological bathwater.

Therefore, we employ OLS estimation using panel-corrected standard errors (PCSE) to deal with panel heteroscedasticity but do not include a lagged dependent variable and unit dummies. Following the recommendation of Plumper et al. (2005), we use the Prais–Winsten transformation to eliminate serial correlation of errors, assuming first-order autocorrelation within panels (an AR1 process). All explanatory variables are lagged by 1 year to control for the potential exogenous effects of income inequality (see Yi, 2013, for more discussion).

Admittedly, it is also plausible to suspect that our empirical results are biased simply due to excluding the lagged dependent variable and the unit dummies that have been widely included in econometric models of the recent comparative political economy literature. However, models that include them are not appropriate for this analysis, not only due to the methodological reasons argued earlier but also due to some technical issues: The data on inequality (Gini coefficient) are greatly unbalanced, and key explanatory variables of theoretical interest are almost perfectly correlated with unit dummies. Accordingly, in order to further assess the robustness of the results, we consider the random-effects models.

Results and discussion

As discussed above, there are two groups of empirical results required for testing the hypothesis in this analysis (see Rueda, 2008, for a similar analysis). The first group of regressions catches the impacts of the regime type on policy outcomes (domestic government spending and welfare state generosity).⁶ For each policy, there are two specifications of the model, the Prais–Winsten regressions with PCSEs and the random-effects generalized least squares (GLS) regressions. The second group of regressions captures the impacts of policies on inequality. Like the first set, there are two specifications for each policy, and in order to see how different its impacts are in each regime type, we add the interaction terms between policy and regime type.

According to the theoretical claim and empirical finding from Gerring et al. (2012) and Huber and Stephens (2012), the “stock” of democracy is more likely to be associated with good governance in policies, which leads to a more equal redistribution. Our empirical findings do not, however, support this hypothesis. The effect of age of total democracy is positive and statistically significant, which indicates that the increase in the stock of democracy is associated with higher levels of income inequality, whereas the signs of age of democracy’s coefficients are not consistent and rarely significant in Table 3. This result appears at odds with previous theoretical argument, but one may expect this because the sample consists of only developing countries. In the sample here, the mean of age of total democracy is just 15 years: only Portugal and Spain have reached almost 40 years, and the duration of all post-communist countries’ democratic system is less than 17 years. This finding implies that a brief experience of democratic governments is less likely to produce a more egalitarian income distribution unless it presents a higher quality of democratic governance (Yi, 2013).

Turning back to the substantive variables summarized in Figure 1, (partial) democracies were expected to relate to higher levels of domestic government spending. The relationship between domestic government spending and inequality, however, was ambiguous given the logic of the interest group theory. The results in Tables 2 and 3 provide a somewhat significant amount of support to these hypotheses. They show that (partial) democracies promote higher levels of domestic government spending, but the impacts of this spending on inequality are not statistically significant.

Table 2.

Determinants of domestic government spending and welfare state generosity.

	Domestic government spending		Welfare state generosity
	Prais–Winsten	GLS	Prais–Winsten	GLS
Democracy	2.126***	2.931***	0.080^	0.075^
Democracy	(0.534)	(0.459)	(0.043)	(0.043)
Partial democracy	0.809*	1.274***	−0.058	0.012
Partial democracy	(0.335)	(0.393)	(0.030)	(0.041)
Trade (log)	4.935***	4.082***	−0.001	0.160***
Trade (log)	(0.545)	(0.520)	(0.041)	(0.044)
FDI inflow	−0.012	−0.001	−0.001	0.007***
FDI inflow	(0.029)	(0.034)	(0.002)	(0.002)
GDP per capita (log)	3.720***	1.181^	0.017	0.338***
GDP per capita (log)	(0.887)	(0.607)	(0.045)	(0.038)
GDP per capita (log)²	0.978**	0.904***	0.008	0.005
GDP per capita (log)²	(0.341)	(0.225)	(0.022)	(0.017)
Total population (log)	−1.199***	−1.193***	0.095***	0.213***
Total population (log)	(0.309)	(0.371)	(0.018)	(0.030)
Elderly population	0.316	−0.344^
Elderly population	(0.270)	(0.180)
Youth population	0.134	−0.283***
Youth population	(0.110)	(0.054)
1^st Oil crisis	1.470***	0.523
1^st Oil crisis	(0.450)	(0.681)
2^nd Oil crisis	0.119	0.037
2^nd Oil crisis	(0.344)	(0.542)
Oil exporter	0.973	0.941
Oil exporter	(1.149)	(1.189)
Left totalitarian	3.541	−1.559	0.108	0.074
Left totalitarian	(2.196)	(4.698)	(0.133)	(0.348)
Constant	11.692	31.262***	0.675	−3.002***
Constant	(10.647)	(8.103)	(0.521)	(0.550)
R ²	0.6764	0.3098	0.7492	0.3551
N of developing countries	110	110	105	105
N of observations	1920	1920	934	934

Note: All explanatory variables are 1-year lagged.

p ≤ .10; *p ≤ .05; **p ≤ .01; ***p ≤ .001.

Table 3.

Determinants of income inequality.

	Income inequality
	Prais–Winsten	Prais–Winsten	GLS	Prais–Winsten	GLS
Democracy (D)	0.947	1.800^	−1.319	−1.133	−2.646*
Democracy (D)	(1.053)	(1.194)	(1.054)	(1.321)	(1.195)
Partial democracy (PD)	1.012	1.225	−0.569	−3.250*	−1.305
Partial democracy (PD)	(1.167)	(1.194)	(1.031)	(1.467)	(1.234)
Domestic gov. spending (DGS)	0.061	0.046^	0.016
Domestic gov. spending (DGS)	(0.025)	(0.024)	(0.027)
D × DGS		0.028	0.097
D × DGS		(0.071)	(0.069)
PD × DGS		−0.092	0.008
PD × DGS		(0.074)	(0.076)
Welfare state generosity (WSG)				−0.573	−2.001**
Welfare state generosity (WSG)				(0.450)	(0.637)
D × WSG				−7.103***	−3.094*
D × WSG				(2.140)	(1.481)
PD × WSG				−5.645**	−2.502
PD × WSG				(1.869)	(1.600)
Age of democracy	−0.437	−0.611^	−0.028	0.554	−0.113
Age of democracy	(0.361)	(0.341)	(0.365)	(0.566)	(0.608)
Age of total democracy	1.098**	0.893*	0.988*	3.343***	1.528*
Age of total democracy	(0.419)	(0.371)	(0.443)	(0.698)	(0.689)
Trade (log)	0.352	1.018	0.030	−0.580	−0.815
Trade (log)	(0.818)	(0.768)	(0.700)	(1.456)	(1.025)
FDI inflow	0.032	0.051	0.043	0.023	−0.035
FDI inflow	(0.044)	(0.042)	(0.036)	(0.030)	(0.036)
GDP per capita (log)	0.156	−0.111	1.502*	−0.253	2.791*
GDP per capita (log)	(1.156)	(0.997)	(0.765)	(1.498)	(1.165)
GDP per capita (log)²	−1.117*	−1.096**	0.050	−0.251	1.789***
GDP per capita (log)²	(0.474)	(0.418)	(0.323)	(0.936)	(0.470)
Sector dualism	0.009	0.028	−0.073*	-0.092*	−0.194***
Sector dualism	(0.039)	(0.038)	(0.031)	(0.042)	(0.039)
Youth population	0.193	0.190	0.240**	0.289^	0.255*
Youth population	(0.149)	(0.128)	(0.077)	(0.167)	(0.118)
East Asia	−6.417*	−6.278*	−2.571	−2.634	−3.916
East Asia	(2.564)	(2.559)	(3.920)	(3.013)	(4.679)
South-East Asia	7.695*	7.643*	3.851	−0.037	−0.096
South-East Asia	(3.008)	(3.073)	(2.732)	(1.992)	(3.313)
Latin America	8.043***	7.864***	7.622***	3.638	4.542
Latin America	(1.998)	(1.899)	(2.271)	(2.232)	(2.970)
Post-Communist	0.753	−0.377	2.370	−0.568	0.529
Post-Communist	(2.743)	(2.552)	(2.484)	(2.512)	(2.947)
Africa	10.909***	10.133***	10.430***	6.118**	7.589*
Africa	(2.288)	(1.842)	(2.688)	(2.276)	(3.436)
Constant	33.185***	30.766***	32.237***	29.264***	37.343***
Constant	(5.242)	(3.942)	(4.821)	(6.869)	(6.303)
R ²	0.9685	0.9726	0.3918	0.9636	0.2786
N of developing countries	78	78	78	69	69
N of observations	780	780	780	506	506

Note: All explanatory variables are 1-year lagged.

p ≤ .10; *p ≤ .05; **p ≤ .01; ***p ≤ .001.

Table 4.

Summary statistics.

Variables	Obs	Mean	Std. Dev.	Min	Max
Domestic gov. spending	2248	18.10	9.36	−7.99	75.62
Welfare state generosity	978	1.01	0.64	0	2.57
Inequality (Gini)	587	39.35	11.50	18.5	65.8
Democracy	6073	0.20	0.40	0	1
Partial democracy	6073	0.19	0.39	0	1
Log of GDP per capita	5649	8.14	1.04	5.03	11.49
Log of trade	5134	4.02	0.63	−1.18	6.12
FDI	4145	2.77	8.26	−82.89	348.19
Sector dualism	1378	14.39	11.30	0.00	55.13
Log of total population	5850	15.79	1.56	11.62	21.00
Elderly population	6083	4.82	3.22	1.00	18.53
Youth population	6083	38.24	8.89	13.40	51.92
Left totalitarian	6460	0.04	0.19	0	1

The empirical results for the relationships involving welfare state generosity are also reported in Tables 2 and 3 and in Figure 3. Again going back to Figure 1, (partial) democracies were hypothesized to be associated with higher levels of welfare state generosity and welfare state generosity with lower income inequality. In Tables 2 and 3, our findings do not confirm the former hypothesis but do confirm the latter. The results indicate that, in developing countries, regime types have nothing to do with welfare state generosity, but welfare state generosity may be related to more equality. More specifically, the effects of welfare state generosity on inequality are slightly different across regime type in terms of statistical significance and its substantial amount. The interaction variable between welfare state generosity and democracy is statistically significant and has a stronger negative impact in the last two models in Table 3, implying that welfare state generosity in democratic countries, compared with that in other regime types, is more inclined to reduce income inequality.

Figure 3.

Empirical results: regime type, policy, and income inequality.

In sum, the evidence clearly suggests that democracies are likely to increase domestic government spending, but they are not associated with higher levels of welfare state generosity, and that welfare state generosity only, not government spending, is likely to decrease income inequality in the developing world. How can those findings be explained? More specifically, if democracies spend more money, why does this have so little impact on levels of welfare state generosity and income inequality in the developing world? Theoretically, there may be two ways to explain these unexpected empirical findings. The first focuses on how to allocate spending (efforts), and the second whether democracies actually have the capability to achieve what they want (consequences).

First, intuitively, it makes sense for welfare state generosity to have negative effects on income inequality because it can directly influence the actual living conditions of people below median income levels. In our analysis, welfare state generosity measures the amount of real benefits that non-working people (younger than 15 or older than 64) will receive from welfare programs. At the outset, we hypothesized the inequality-reducing effects of welfare state generosity, and empirical results here support this hypothesis. The finding of the lack of a relationship between democracies and welfare state generosity is, however, unexpected. Although the standard explanation of the Meltzer–Richard model is that democracy is likely to increase the size of government for, at least, welfare state generosity, this is not the case in the developing world.

It looks like a puzzle but, strictly speaking, there is no reason to believe that democracies will provide more public goods and services than authoritarian regimes to people below median income levels (see Ross, 2006). Even if one concedes that the politics of redistribution is working as Meltzer and Richard assumed, that is, a democratic government tries to target the median voter, it does not mean that people below median income levels get more benefits from a democratic government. Furthermore, one of their assumptions, a universal flat-rate benefit, is not plausible in reality: “governments are adept at channeling benefits to the constituencies they wish to favor” (Ross, 2006: 870).

As we mentioned previously, this argument is compatible with the logic of the interest group theory. It implies not only the increase in the size of government spending but also the disproportionate allocation of government spending in democracies, which leads to the general phenomenon of concentrated benefits and dispersed costs. It is reasonable to infer that the organized or more powerful groups more frequently receive preferential treatment from democratic government than do unorganized or less powerful groups. Our findings—the increase in government spending but no incremental benefits for the non-working population in democracies—largely confirm this model.

This is also consistent with the results of some empirical studies. The World Bank and the United Nations argue that public spending in developing countries has tended to help people belonging to non-poor households (Human Development Report, 2002; World Development Report, 2001). More specifically, poor democracies usually distribute public spending on education unequally and, thus, relatively fewer poor people get more (Reinikka and Svensson, 2004). Along the same lines, government health spending is also regressive, indicating that the additional health benefit derived from the increase in public spending on health is considerably smaller for the poor than for the non-poor (Bidani and Ravallion, 1997).

The second way to explain these findings concerns democracies’ capacity to achieve what they want. Welfare-friendly policies, such as a generous social policy and higher level of spending, may not automatically produce better outcomes of redistribution. Even if democracies have the good intention to redistribute more and use a variety of policies to decrease income inequality, these policies have a negative impact on inequality only when they actually deliver benefits to people as intended. This implies that social policies will have no impact on income inequality unless democracies have the capacity to function well and efficiently.

Robinson and Torvik (2005) propose a theory of “white elephants”⁷ to explain a particular type of inefficient redistribution. Reviewing many cases of the location of public investment projects in Africa, Bates argues that “governments are often willing to lower the profits of firms in order to secure other objectives – such as a plant location that is politically desirable though economically disadvantageous” (2005: 25). White elephants seem to be politically rational because they can target supporters, but the cost may be inefficient redistribution because these projects are basically chosen to increase the income of a particular constituency.

This argument is also related to a model of the “visibility effect” in government resource allocation (Mani and Mukand, 2007). It implies that the government, maximizing electoral utility, is motivated to distribute relatively more resources to highly visible public goods and neglects the provision of essential public goods, despite their contribution to considerable benefits.⁸ Moreover, and probably most connected with the point of this analysis, they argue that the resource allocation gap between the more visible and less public goods becomes the widest at some intermediate level of democracy. This may be the case particularly in developing countries.

A skeptical view of the effects of social policies in the developing world is consistent with several recent studies. Rudra (2004) finds that social spending has much less favorable impact on income inequality in the developing world. According to Huber (1996), targeted emergency welfare programs increase political elites’ motives for patronage, which leads to a waste of resources in Latin American welfare state programs. All in all, a broad policy and higher level of government spending are probably a necessary, but definitely not a sufficient, condition for an equal society.

Conclusion

This paper attempts to answer the question of how political regime influences income inequality. We argue that the starting point lies in the differentiation between democracy’s efforts (the effect of democracy on policy) and their consequences (the effect of policy on income inequality). The empirical results of our analysis clearly suggest that democracies are likely to increase domestic government spending, but they are not associated with higher levels of welfare state generosity, and that welfare state generosity only, not government spending, is likely to decrease income inequality in the developing world.

The analysis may be expanded to develop a more sophisticated model by including one potential determinant of levels of income inequality, good or efficient governance, which has been rarely addressed in the literature on the politics of inequality. This factor may be critical for redistributive demands to be completely reflected in the process of decision making and policy implementation. This is particularly the case in the developing world because, in the context of relatively higher levels of clientelism and corruption, more generous social policies may not work as mechanisms to help people below median income levels even when government spending is increasing. Answering the question of whether good governance actually reduces income inequality in developing countries can provide practical suggestions for advocates of pantisocracy.

Footnotes

Appendix

Countries and years in the empirical analysis for which the observation was available in Model 1 in Table 3.

Africa

Botswana (1986, 1999, 2001, 2002, 2004), Burkina Faso (1995), Cameroon (1991), Ethiopia (1995), Gambia (1994), Kenya (1981, 1991, 1992, 1996, 1999, 2000), Lesotho (1997, 1998, 2000), Mauritius (1991, 1993, 1995–2006), Namibia (1998, 2001), Rwanda (1990), Sierra Leone (2005), South Africa (2001–2005), Tanzania (1992), Uganda (2004), Zambia (1991, 1997, 1999)

East Asia

China (1988–2003), Mongolia (2002–2006), South Korea (1981–2000, 2002–2008)

South-East Asia

Bangladesh (2004, 2006), Cambodia (1999, 2001, 2002), India (1991–1996), Indonesia (2005–2008), Malaysia (1981–1994, 1996–2004), Nepal (1991, 1992, 2000, 2002), Pakistan (1991–2005), Singapore (1981–2000, 2002–2005, 2007, 2008), Sri Lanka (1991–1999, 2002), Thailand (1981–2004)

Latin America

Argentina (1997–2005), Bolivia (1983, 1984, 1986, 1987, 1989, 1994–1998, 2001–2003), Brazil (1982–1991, 1993, 1994, 1996–2007), Chile (1996–1998, 2000–2008), Colombia (1981, 1986–1993, 1995–2007), Costa Rica (1981–2007), Dominican Republic (1992–2001, 2003, 2005, 2006, 2008), Ecuador (1989–1999, 2002–2007), El Salvador (1992, 1993, 1995–2007), Guatemala (1982, 1983, 1988, 1990–1992, 1995, 1999, 2003), Guyana (1993, 1998), Haiti (2000), Honduras (1983, 1984, 1991–2000, 2002–2006), Mexico (1981, 1989, 1991, 1992, 1994, 1996–2008), Nicaragua (1995–2002, 2004, 2005), Panama (1984–1986, 1989, 1990, 1992–2006), Paraguay (1996, 1998–2004, 2008), Peru (1987–2008), Trinidad (1985–1987, 1995, 1996), Uruguay (2001–2008), Venezuela (1981–2004)

Post-Communist

Armenia (2004–2007), Bulgaria (1991–2008), Croatia (1997–2006), Czech Republic (1994–2007), Estonia (1994, 1995, 1997–2002), Georgia (2005, 2006), Hungary (1991–2006, 2008, 2009), Kazakhstan (2000, 2002–2006), Kyrgyzstan (1994–2007), Latvia (1997–2009), Lithuania (2000–2008), Moldova (1997–2008), Poland (1998–2008), Romania (2003–2009), Russia (1996–2008), Slovak Republic (2007, 2008), Slovenia (1994–2007), Ukraine (2000–2007)

Reference

Algeria (2002, 2004, 2005), Cyprus (1990–1996, 2000–2004), Egypt (2003–2005, 2007), Greece (1982–1997), Iran (1983, 1991, 1994–1997), Jordan (1984, 1987, 1988, 2001, 2002), Papua New Guinea (2001), Portugal (1991), Spain (1981–1999), Turkey (1991–2002), Yemen (1992, 1995, 1999, 2000)

Acknowledgements

The authors wish to thank Evelyne Huber, Lynne Lampe, and anonymous reviewers for their help in preparing this article.

Funding

This work was supported by Hankuk University of Foreign Studies Research Fund of 2014.

Notes

Author biographies

Dae Jin Yi is Assistant Professor in the Department of Political Science at Hankuk University of Foreign Studies, Seoul, Korea (ROK). His research interests focus on redistribution, welfare state, economic growth, governance, and democratization. He has published articles in New Political Economy, Asian Survey, and Journal of Economic Policy Reform.

Jun Hee Woo is Lecturer at Hankuk University of Foreign Studies, Seoul, Korea (ROK). Her research interests focus on comparative political economy and Japanese politics. She has published articles in Korean Political Science Review and The Korean Journal of Area Studies.

References

Acemoglu

Daron

Robinson

James A

(2006) Economic Origins of Dictatorship and Democracy. New York: Cambridge University Press.

Adsera

Alicia

Boix

Carles

(2002) Trade, democracy, and the size of the public sector: The political underpinnings of openness. International Organization 56(2): 229–262.

Alderson

Arthur

Nielsen

Francois

(2002) Globalization and the Great U-Turn: Income inequality trends in 16 OECD countries. American Journal of Sociology 107(5): 1–56.

Alesina

Alberto

Wacziarg

Romain

(1998) Openness, country size and government. Journal of Public Economics 69: 305–321.

Bates

Robert

(2005) Markets and States in Tropical Africa: The Political Basis of Agricultural Policies. Berkeley: University of California Press.

Beck

Nathaniel

Katz

Jonathan K.

(1995) What to do (and not to do) with time-series-cross-section data in comparative politics. American Political Science Review 89(3): 634–647.

Becker

Gary

(1983) A theory of competition among pressure groups for political influence. Quarterly Journal of Economics 98(3): 371–400.

Bidani

Benu

Ravallion

Martin

(1997) Decomposing social indicators using distributional data. Journal of Econometrics 77(1): 125–139.

Boix

Carles

(2001) Democracy, development and the public sector. American Journal of Political Science 45(1): 1–17.

10.

Boix

Carles

(2003) Democracy and Redistribution. Cambridge: Cambridge University Press.

11.

Bueno de Mesquita

Bruce

Smith

Alastair

Siverson

Randolph M

Morrow

James

(2003) The Logic of Political Survival. Cambridge: MIT Press.

12.

Castles

Francis

(2002) Developing new measures of welfare state change and reform. European Journal of Political Research 41: 613–641.

13.

Clayton

Richard

Pontusson

Jonas

(1998) Welfare-state retrenchment revisited: Entitlement cuts, public sector restructuring, and inegalitarian trends in advanced capitalist societies. World Politics 51(1):67–98.

14.

Drazen

Allan

(2000) Political Economy in Macroeconomics. Princeton: Princeton University Press.

15.

Ferreira

Francisco

Ferranti

David de

Perry

Guillermo

Walton

Michael

(2004) Inequality in Latin America: Breaking with History? Washington, DC: The World Bank.

16.

Gasiorowski

Mark

(1997) Political Regimes and Industrial Wages: A Cross-National Analysis. In Midlarsky

Manus

(ed) Inequality, Democracy and Economic Development. Cambridge: Cambridge University Press, pp. 244–268.

17.

Gerring

John

Thacker

Strom

Alfaro

Rodrigo

(2012) Democracy and human development. Journal of Politics 74(1): 1–17.

18.

Grossman

Gene

Helpman

Elhanan

(2001) Special Interest Politics. Cambridge: MIT Press.

19.

Huber

Evelyne

(1996) Options for Social Policy in Latin America: Neoliberal versus Social Democratic Models. In Esping-Andersen

Gosta

(ed) Welfare States in Transition: National Adaptations in Global Economies. London: Sage, pp.141–191.

20.

Huber

Evelyne

Nielsen

Francois

Pribble

Jenny

Stephens

John

(2006) Politics and inequality in Latin America and the Caribbean. American Sociological Review 71(6): 943–963.

21.

Huber

Evelyne

Stephens

John

(2012) Democracy and the Left: Social Policy and Inequality in Latin America. Chicago: University of Chicago Press.

22.

Human Development Report (2002) Deepening Democracy in a Fragmented World. New York: Oxford University Press.

23.

Husted

Thomas

Kenny

Lawrence

(1997) The effect of the expansion of the voting franchise on the size of government. Journal of Political Economy 105(1): 54–82.

24.

Iversen

Torben

Cusack

Thomas

(2000) The causes of welfare state expansion: Deindustrialization or globalization? World Politics 52(April): 313–349.

25.

Jackman

Robert

(1975) Politics and Social Equality: A Comparative Analysis. New York: Wiley-Interscience.

26.

Lenski

Gerhard

(1966) Power and Privilege: A Theory of Social Stratification. New York: McGraw-Hill.

27.

Lindert

Peter

(1994) The rise of social spending, 1880–1930. Explorations in Economic History 31(1): 1–37.

28.

Lipset

Seymour

(1959) Some social requisites of democracy: Economic development and political legitimacy. American Political Science Review 53(1): 69–105.

29.

Mahler

Vincent

(2004) Economic globalization, domestic politics, and income inequality in the developed countries. Comparative Political Studies 37(9): 1025–1053.

30.

Mani

Anandi

Mukand

Sharun

(2007) Democracy, visibility and public good provision. Journal of Development Economics 83: 506–529.

31.

Marshall

Monty

Jaggers

Keith

(2010) Polity IV Dataset. College Park: University of Maryland, Center for International Development and Conflict Management.

32.

McGuire

Martin

Olson

Mancur

(1996) The economics of autocracy and majority rule: The invisible hand and the use of force. Journal of Economics Literature 34(1): 72–96.

33.

Meltzer

Allan

Richard

Scott

(1981) A rational theory of the size of government. The Journal of Political Economy 89(5): 914–927.

34.

Mueller

Dennis

Murrell

Peter

(1986) Interest groups and the size of government. Public Choice 48: 125–145.

35.

Mulligan

Casey

Gil

Richard

Sala-i-Martin

Xavier

(2004) Do democracies have different public policies than nondemocracies? Journal of Economic Perspectives 18(1): 1–26.

36.

Nel

Philip

(2008) The Politics of Economic Inequality in Developing Countries. New York: Palgrave Macmillan.

37.

Nielsen

Francois

Alderson

Arthur

(1997) The Kuznets Curve and the Great U-Turn: Income inequality in U.S. counties, 1970 to 1990. American Sociological Review 62(1): 12–33.

38.

Nooruddin

Irfan

Simmons

Joel W

(2009) Openness, uncertainty, and social spending: Implications for the globalization–welfare state debate. International Studies Quarterly 53(3): 841–866.

39.

Olson

Mancur

(1965) The Logic of Collective Action: Public Goods and the Theory of Groups. Cambridge: Harvard University Press.

40.

Peltzman

Sam

(1980) The growth of government. Journal of Law and Economics 23(2): 209–287.

41.

Persson

Torsten

Tabellini

Guido

(2000) Political Economics: Explaining Economic Policy. Cambridge: MIT Press.

42.

Plumper

Thomas

Troeger

Vera

Manow

Philip

(2005) Panel data analysis in comparative politics: Linking method to theory. European Journal of Political Research 44: 327–354.

43.

Reinikka

Ritva

Svensson

Jakob

(2004) Local capture: Evidence from a central government transfer program in Uganda. The Quarterly Journal of Economics. 119(2): 679–705.

44.

Reuveny

Rafael

Quan

(2003) Economic openness, democracy, and income inequality: An empirical analysis. Comparative Political Studies 36(5): 575–601.

45.

Robinson

James

Torvik

Ragnar

(2005) White elephants. Journal of Public Econometrics 89: 197–210.

46.

Ross

Michael

(2006) Is democracy good for the poor? American Journal of Political Science 50(4): 860–874.

47.

Rudra

Nita

(2004) Openness, welfare spending, and inequality in the developing world. International Studies Quarterly 48: 683–709.

48.

Rudra

Nita

Haggard

Stephan

(2005) Globalization, democracy, and effective welfare spending in the developing world. Comparative Political Studies 38(9): 1015–1049.

49.

Rueda

David

(2008) Left government, policy, and corporatism: Explaining the influence of partisanship on inequality. World Politics 60(3): 349–389.

50.

Scruggs

Lyle

(2008) Social Rights, Welfare Generosity, and Inequality. In Beramendi

Pablo

Anderson

Christopher

(eds) Democracy, Inequality, and Representation: A Comparative Perspective. New York: Russell Sage Foundation, pp. 62–90.

51.

Scruggs

Lyle

Allan

James

(2006) The material consequences of welfare states: Benefit generosity and absolute poverty in 16 OECD countries. Comparative Political Studies 39(7): 880–904.

52.

Sirowy

Larry

Inkeles

Alex

(1990) The effects of democracy on economic growth and inequality: A review. Studies in Comparative International Development 25(1): 126–157.

53.

Solt

Frederick

(2009) Standardizing the World Income Inequality Database. Social Science Quarterly 90(2): 231–242.

54.

Stasavage

David

(2005) Democracy and education spending in Africa. American Journal of Political Science 49(2): 343–358.

55.

World Development Report (2001) Attacking Poverty. Oxford: Oxford University Press.

56.

Dae Jin

(2013) Politics and income inequality: Does politics still matter in new democracies? New Political Economy 18(5): 653–679.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.07 MB

0.01 MB