income gap and inequality

Globalization, Government Ideology, and Income Inequality in Developing Countries

Eunyoung Ha Claremont Graduate University

This article examines how globalization, government ideology, and their interaction have shaped income distribution in 59 developing countries from 1975 to 2005. Using pooled time-series data analysis, the results show that globalization, measured by trade flows and foreign direct investment, has significantly expanded income inequality in developing countries. However, countries with leftist government parties and chief executives have experienced significantly smaller income gaps and even moderated the income inequality from increasing world market integration. The results in this article suggest that the traditional role of government ideology for income redistribution, drawn from the experiences of advanced countries, is applicable to the developing world as well. Rather than being diminished by the integration of international markets, the influence of government ideology will continue to play a key role in shaping the outcomes of globalization.

A ccording to standard trade theory (i.e., the Stolper-Samuelson theorem), international market integration should reduce income gaps

in developing countries by raising the relative prices and demand for unskilled labor, which developing countries have in abundance. Contrary to this expectation, however, income inequality in developing countries has significantly increased at the same time that global trade and capital flows have surged. Thus, the impact of globalization on income inequality has become a central question in international and comparative political economy (e.g., Alderson and Nielson 1999; Dixon and Boswell 1996; Lee 2005; Lundberg and Squire 2003; Milanovic and Squire 2005; Reuveny and Li 2003; Rudra 2008).

In contrast to the intensity of the debate about the impact of globalization on income inequality in the developing world, the role of government ideo- logical orientation with respect to income inequality has been comparatively neglected. This is an over- sight, because most governments—rich and poor alike—do redistribute income through taxation and welfare spending programs such as social retirement benefits and unemployment compensation. Thus, income inequality is a variable over which govern- ments manifestly have control, if they choose to use it. The nature of this control is highly influenced by the ideological orientation of the government in

power, however: leftist governments are expected to increase taxes on the rich and redistribute wealth to the less well-off, while rightist governments typically are expected to do the opposite, cutting taxes to maximize the effects of the free market and decreasing the breadth and depth of welfare spending. Power resour- ces theory on advanced industrial countries confirms that leftist power in government plays a systematic and decisive role in determining variations in governmen- tal redistribution and its outcomes (Esping-Andersen 1985; Huber and Stephens 2001; Korpi and Palme 2003). Given the strong theoretical expectation that the ideological orientation of the government is conse- quential for social policymaking, it is notable that the impact of government ideology on redistribution and income inequality has rarely been empirically exam- ined in studies of the developing world.

There are both theoretical and empirical reasons why this might be. Theoretically, political variables were traditionally considered to have lesser effect on income distribution in less developed countries (LDCs), where political institutions are less consolidated and where organizations for the underprivileged, particularly leftist political parties and labor unions, are weaker as compared to advanced industrial societies. Political parties in LDCs are also, in general, deemed to be more personalized than ideologically or programmati- cally oriented, making the pursuit of redistribution a

The Journal of Politics, Vol. 74, No. 2, April 2012, Pp. 541–557 doi:10.1017/S0022381611001757

� Southern Political Science Association, 2012 ISSN 0022-3816

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less consistent and coherent part of their platforms (Mainwaring and Torcal 2006). Indeed, welfare and tax transfers in LDCs have never been consistently distrib- uted toward the middle or lower classes (Kapstein and Milanovic 2002; Rudra 2008). Even when genuinely redistributive policies do exist, their impact might still be minimal compared to that in developed countries, because most developing countries have a compara- tively small proportion of formal sector employment and even have regressive social retirement schemes (Lindert, Skoufias, and Shapiro 2006). Practically speak- ing, there has been no high-quality data produced on government ideology usable for comparative empirical studies on large numbers of developing countries.

Nonetheless, for both theoretical and practical reasons, I am interested in whether and how govern- ment ideology matters for differences in inequality within developing countries. First, contrary to the received wisdom outlined in the paragraph above, policymakers’ party affiliations and ideological orien- tations do strongly affect policies in LDCs (Murillo 2001). Researchers also document that citizens in LDCs consider the left-right dimension, rather than just the politics of personality, when structuring their political preferences (Colomer and Escatel 2004). In addition, although direct social expenditures in LDCs are smaller than those in advanced economies, governments often redistribute wealth to the poor or middle classes through indirect policies such as housing regulations, basic services provision, and labor market regulations. For example, leftist parties in Latin America allocate expenditures to progressive programs such as non- contributory and conditional transfer programs, school feeding programs, and preventive health care.

Second, the absence of high-quality data is a tractable problem. In the present article, for example, the data used originated with the World Bank’s recent Database on Political Institutions (DPI) and covers 59 developing countries from 1975 to 2005. The DPI lists the ideological positions—left, center, or right—of the three largest government parties and chief executives for LDCs. The shortcomings of this approach become apparent when considering coun- tries with governing coalitions comprised of four or more parties. Accordingly, I extended the original dataset to include all government parties, improved the information on government formation, and generated additional measures for the ideological positions of government parties and chief executives.1

The broad goal of this article is to investigate the impact of government ideological orientation on income inequality within LDCs. In particular, I hope to address whether political commitment to redis- tribution brings countries closer to internal economic equality. In so doing, income inequality may serve as a test case with which to judge the overall influence of government ideology in LDCs. More narrowly, I explore how useful an explanatory framework built on the experience of established industrial countries—namely, the premise that ideological preferences of political leadership are an important determinant of income distribution—is for understanding inequality in the very different historical and structural context of LDCs. My second broad goal is to place these results on ideology within the context of the global econ- omy that has emerged over recent decades. In particular, how have the relationships between gov- ernment ideology and income distribution interacted with globalization? Does globalization mute or in- tensify the effects of government ideology?

Accordingly, this article evaluates how global- ization, government ideology, and their interactions have shaped income inequality in LDCs. My empiri- cal results confirm that, contrary to standard trade theory, fast-growing trade flows and foreign direct investment—two measures of globalization—are strongly associated with rising income inequality in developing countries. My results also confirm that the ideological preferences of government parties and chief executives do significantly influence income distribution in developing countries: governments with leftist political leadership are strongly associated with lower inequality than those with rightist leader- ship. Moreover, the role of government ideology has not been eroded by globalization, but rather has been resilient to it: governments with leftist parties and chief executives have moderated the upward pressure of market integration toward inequality.

This article is organized into five parts. First, I review the theoretical and empirical scholarship on the relationship between globalization and income inequality in developing countries. Second, I discuss how government ideology can be an important determinant of income distribution in developing countries. I also review how globalization and gov- ernment ideology may interact with each other to shape income distribution. In the next two sections, I describe the data and empirical models employed, present the findings, and discuss the robustness of different measurements and empirical models used. I conclude by discussing the implications of my results.

1Online appendices are available at http://journals.cambridge.org/ jop. The data will be available on my homepage (http://wfs.cgu.edu/ hae/index.html) upon publication.

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Globalization and Income Inequality

According to standard trade theory, i.e., the Stolper- Samuelson theorem, globalization is expected to narrow income disparities within developing coun- tries (Stolper and Samuelson 1941). This is because free trade increases the demand for goods and services from the sectors which use relatively abun- dant factors in a country, while reducing the demand for goods and services from the sectors with scarce factors. By so doing, free trade also raises the incomes of owners of abundant factors of production and reduces the incomes of owners of scarce factors of production. Because LDCs have proportionally more unskilled labor than developed countries, greater trade openness increases the demand and prices for unskilled labor, relative to that for both their capital and their skilled labor (it also has this effect relative to unskilled labor in developed countries). Accord- ingly, increased trade flows should reduce wage gaps between unskilled labor in LDCs and capital and skilled labor there, reducing overall within-country income inequality.

Similarly, capital openness is also expected to reduce income inequality in LDCs. Foreign direct investment (FDI) increases developing countries’ capital stock, which reduces the marginal product of capital but increases the marginal product of labor. This happens in two ways. First, marginal returns to a resource are inversely related to its level of abun- dance; thus, a small capital stock produces high returns to capital, but a larger capital stock will be associated with smaller (though hardly negative) marginal returns. Second, increased levels of capital make labor more productive. Put simply, a carpenter with a power saw is more productive than a carpenter with a hand saw. Since resource returns are equiv- alent to marginal productivity, by increasing the productivity of labor, FDI should increase the mar- ginal return to labor (which is equivalent to the wage) as well. This would increase labor’s income share and reduce income gaps.

However, contrary to theoretical expectations, income inequality in LDCs has actually risen rapidly alongside increases in market liberalization and FDI. Most explanations for this apparent paradox rely on making a distinction between skilled and unskilled labor, and the notion of a skill premium earned by the former. This collection of explanations can be termed the ‘‘technology-centered globalization-inequality thesis.’’ First, it is observed that trade often shifts the production of intermediate inputs from developed to

developing countries. Although intermediate products are ‘‘unskilled-labor-intensive’’ from a developed country’s perspective (thus making their observed discarding by rich countries consistent with, rather than contradictory to, Stolper-Samuelson and com- parative advantage), they are still relatively ‘‘skilled- labor-intensive’’ from a developing country’s point of view (Feenstra and Hanson 1997). The arrival within LDCs of relatively skilled-labor intensive industries explains the increase in demand for and hence wages of the small pool of local skilled workers, and further widens income inequality vis-à-vis their unskilled counterparts.

A second explanation for this paradox, closely related to the first, is that FDI facilitates technology diffusion from developed countries to developing ones. Although developed countries do not neces- sarily transfer their best technologies to LDCs (they still retain specialization in production pro- cesses that make intensive use of their relatively abundant factors of production, i.e., technologically advanced capital, which again is consistent with Stolper-Samuelson and comparative advantage), the transferred technologies are relatively skill intensive from the perspective of the LDCs, and at least more skill intensive than those previously produced do- mestically. It is also observed that the sectors actually grown and developed by FDI tend in practice, as opposed to in theory (which, as discussed above, would predict the opposite), to be capital intensive, and capital-intensive industries also tend to be skilled-labor intensive (Feenstra and Hanson 1997).

Confirming these observations, several scholars have found that trade has increased the relative demand for skilled labor and produced a rise in skill premia (e.g., Conte and Vivarelli 2007). Similarly, studies have found that multinational corporations in LDCs pay higher wages for skilled workers than local companies (Feenstra and Hanson 1997; Mazumdar and Mazaheri 2000). A number of other empirical studies conducted with a broader scope have also found globalization to be systematically associated with the expansion of income inequality (Alderson and Nielson 1999; Dixon and Boswell 1996; Lee 2005; Lundberg and Squire 2003; Milanovic and Squire 2005; Rudra 2008), while others find mixed results (e.g., Reuveny and Li 2003).

Still, most analysis on globalization and inequal- ity in LDCs has been too narrow, especially compared with work done on advanced industrial economies. For example, most studies have focused only on economic determinants, such as trade, FDI, and/or technology. However, it is impossible to assume that

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middle- or lower-class populations would automati- cally gain or lose from any purely economic develop- ment. The content and effects of government policies often differs, particularly with respect to the distrib- utive effects of market liberalization, and usually varies according to domestic political determinants, even among countries with similar fiscal capacities. Therefore, a more fruitful research approach would identify these important domestic political determi- nants, instead of focusing on trying to find a mech- anistic link between globalization and inequality.

Globalization, Government Ideology, and Income Inequality

In studies of developing countries, the state regime type, i.e., democratic versus authoritarian, has been considered to be a major political determinant of income inequality (e.g., Burkhart 1997; Huber et al. 2006; Lee 2005; Reuveny and Li 2003; Rudra 2008). According to the literature, a more even distribution of political power among the citizenry—especially the enfranchisement of all citizens—necessarily leads to organized political competition which in turn helps spread economic power and reduces income inequal- ity. When there is no competition between political groups (as in authoritarian regimes), the government is more susceptible to individual pressures or favori- tism, benefiting the ‘‘haves’’ at the expense of the ‘‘have-nots.’’ In contrast, when there is competition between political groups (as in democratic regimes), political elites are more likely to respond to the interests of the poor or middle class in the area of redistribution. The idea that political leaders in democratic regimes have a natural incentive to redistribute wealth to appeal to the broad electorate originates in the median voter theorem. The median voter is the decisive voter in an electoral democracy (Downs 1957) and is said to prefer larger redistrib- utive spending when income inequality in a society is upward-skewed, which places his/her median income further below the mean (Meltzer and Richard 1981). Because income inequality is generally upward skewed in most LDCs, politicians under electoral competition there would thus be expected to redis- tribute significantly to satisfy this median voter.

However, increased political equality has not necessarily lead to more income equality in LDCs. Several empirical studies find that regime types have little impact on income inequality (e.g., Bollen and Grandjean 1981; Jackman 1974; Rubinson and

Quinlan 1977), and a few even find positive impacts (Nel 2005). While electoral competition may provide an opportunity for the introduction of the prefer- ences of the broad public into politics, the mere existence of electoral competition does not guarantee greater representation for the poor or middle class. In LDCs, the decisive voter is often not the median income earner (or the median quintile) but the richest quintile, which hence is the one that gains most from the introduction of competitive elections, fiscal redistribution, and economic liberalization in general (Nel 2005).

Even in well-established democracies, leftist par- ties that represent the poor sometimes have limited political power or none at all, and the median income earner is rarely a net beneficiary of taxes and transfers (Milanovic 2000). Why is this? First, political candi- dates often set their policy positions not in order to appeal to the broader electorate but to serve smaller primary constituencies, which provide them with resources for campaigns (Fenno 1978). The poor or underprivileged often lack the connections and funds to effectively influence political candidates in this way. Second, collecting information on the policy positions of multiple political parties and candi- dates is costly for voters in terms of time and effort. These costs are greater for citizens with lower levels of income and education, who thus tend to vote at lower rates and to be underrepresented in the political system (Verba, Schlozman, and Brady 1995).

It has been noted already that redistribution does not flow automatically from the introduction of democracy, but must be targeted and worked for specifically. The chronicle of this effort in advanced countries forms the basis of a literature known as the ‘‘power resources theory’’ or ‘‘political class struggle approach.’’ It argues that ‘‘the distribution of organ- izational power between labor organizations and left parties on the one hand and center and right-wing political forces on the other hand’’ determines the differences in the size and distributive impact of welfare states across countries and over time (Huber and Stephens 2001). According to this scholarship, the upper class occupies a privileged position and has extensive channels to influence political outcomes (Lindblom 1977). Thus, to be successful in contests over redistribution, the working and lower middle classes need organizations that articulate their class interests and can effectively mobilize the troops. Several studies empirically demonstrate that the strength of leftist parties in government, particularly social democratic parties aligned with strong labor

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unions, are strongly associated with progressive taxes and income transfers, and lower income inequality (e.g., Esping-Andersen 1985; Garrett 1998; Huber and Stephens 2001; Korpi and Palme 2003).

In light of the above, who governs (specifically, the ideological orientation of the government) should be considered as an important political determinant of income inequality, above and beyond merely how a government is established (the regime type of the government). If so, the critical matter may not simply be whether the mass electorate has the franchise, but more importantly, what it does with it once gained. Above all, the diversity of income distributions among authoritarian regimes and democratic re- gimes alike is better explained by the ideology of the particular state in which it is found than by the process through which governing is carried out. The lower strata of societies are likely to be better protected by a government which assigns relatively high priority to the protection of their interests—a leftist government—than by a government which favors growth without regard for its redistributive consequences—a rightist government. This might be true regardless of regime type. Authoritarian coun- tries (provided their leadership is committed to leftist ideology) may actually be more likely to redistribute wealth to the poor or public than their rightist counterparts in democratic regimes. For example, socialist governments in Eastern Europe prior to the fall of the Berlin Wall which were ideologically committed to ‘‘socialist contracts’’ provided universal social protections to their populations, despite their authoritarian nature (Haggard and Kaufman 2008). Recent empirical studies have in fact found that the ideological orientation of government is strongly associated with the welfare of the poor (Moon and Dixon 1985) and with income inequality in Latin American and Caribbean countries (Huber et al. 2006). Consistent with this, I would expect countries with political leadership committed to redistribution and economic equality to have less income inequality, and this is one of the things I set out to test in this article.

Yet this necessarily leads to a further question: can the ideological preference of government parties or chief executives survive under the pressure of globalization? Several scholars have recently argued that the separate and distinct policy preferences of leftist (and rightist) governments have tended to converge to conservative/liberal consensus under the competitive pressure of economic integration (e.g., Huber and Stephens 2001; Strange 1996). According to them, generous welfare expenditures

and higher tax burdens prevent domestic producers and investors from competing effectively with their counterparts in the integrated world market. With international capital mobility, mobile asset holders can also move their assets to other countries with lower taxes and a higher rate of return on investment. To facilitate the price competitiveness of domestic producers and maintain a business-friendly environ- ment, leftist governments may cut tax burdens and social programs even if otherwise inclined toward pursuing their partisan objectives and progressive redistribution policies. However, several other studies on advanced economies demonstrate that govern- ment partisanship has still remained an important determinant of social policies in the integrated world market (Garrett 1998; Korpi and Palme 2003). This research tests whether the policy impact of distinct government ideological preferences on LDC income distribution diminishes as market liberalization increases.2

Data and Models for Analysis

Income inequality. The dependent variable, income inequality, is measured by the Gini coefficient (hereafter, Gini), which ranges from 0 (perfect equal- ity) to 100 (perfect inequality). Gini data was retrieved from the UNU-WIDER World Income Inequality Database (WIID). The WIID is based on

2This article focuses on if and how the impact of government ideology on income distribution is constrained by globalization. However, the redistributive policy of leftist/rightist governments can also be significantly constrained by either internal or external institutional constraints. Constitutional structure (i.e., veto points) is considered to be an important determinant of redis- tributive policies and outcomes in advanced economies (Ha 2008; Huber and Stephens 2001; Tsebelis 2002). Although leftist (or rightist) governments obviously wish to pursue their ideo- logically preferred redistribution policies, they are likely to be particularly constrained when there are a relatively large number of veto players in a country’s governing structure whose agree- ment is necessary to enact such policies. To test this possibility, I created an interaction term between government ideology and veto players, using Henisz’ (2002) veto points data (POLCON) and DPI (2010)’s checks and balances data, but I obtained no significant results for the interaction terms.

Ties to international financial institutions, such as participat- ing in IMF structural adjustment programs, might also signifi- cantly constrain LDC government welfare programs and enlarge income inequality (Vreeland 2007). I extended Vreeland’s (2007) data on IMF program participation to year 2005 and tested if the impact of government ideology is constrained by IMF program participation. None of these interaction terms were statistically significant, nor do they have the expected positive signs. So, I report only the interaction terms between government ideology and globalization.

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the ‘‘high quality’’ filtering of Deininger and Squire (1996), which allows comparative studies for rela- tively large numbers of countries and years. (Online Appendix 1 contains more information on the chal- lenges of using Gini coefficients to compare income inequality between countries.)

Globalization. To measure the degree of inter- national market integration, I use two key measures of contemporary globalization: trade flows (the sum of imports and exports) as a share of GDP, and foreign direct investment (FDI) as a share of GDP. According to standard trade theory discussed above, these globalization indicators are expected to be negatively related with inequality in LDCs. On the other hand, according to the ‘‘technology-centered globalization-inequality thesis,’’ increased trade flows and FDI are expected to increase skill premia, and thus increase inequality.

Ideological orientation. The World Bank’s Da- tabase of Political Institutions (DPI) tallies the ideol- ogy of the three largest government parties and the chief executive. It categorizes parties and chief exec- utives by placing their preferences regarding state control of the economy on a standard left-right scale, and then assigning one of three values: Left, Center, or Right.3 Parties and chief executives are coded ‘‘Right’’ when the terms ‘‘conservative’’ or ‘‘Christian democratic’’ appear in their names or the label ‘‘right-wing’’ was found in the cross-check sources. Similarly, parties are classified as ‘‘Left’’ if their names show them to be ‘‘communist, socialist, or social democratic’’ or if they are labeled as ‘‘left-wing’’ in the cross-check sources. Parties are coded as ‘‘Cen- ter’’ when their names assert centrist affiliation or if their position can be described as centrist, emphasiz- ing the strengthening of private enterprise within a social-liberal context but also supporting a redistrib- utive role for government. All the cases which do not fit into the categories above are treated as missing

(see Beck et al. 2001 and DPI 2010 for detailed coding rules).4

The author compiled data on government ideo- logical orientation following the coding rules of DPI, but improved upon in three ways. First, the number of government parties was increased from the three largest parties to all of the parties in government. Because many countries have more than three gov- ernment parties that significantly affect government policies, excluding the fourth or fifth largest govern- ment party, which may have only two or three seats fewer than the third largest party, is likely to produce significant measurement errors on government ideol- ogy scores. Second, I redefined government parties as those with cabinet portfolios only and excluded any parties that did not fit these criteria in the dataset. While most government parties from DPI fit within these criteria, the DPI sometimes includes indispu- tably nongovernment parties and contains missing values in its cataloging of the partisan composition of governments. For example, the DPI codes the Taiwan Solidarity Union as a government party from 2002 to 2004 although it does not have any cabinet portfolios. Last, to rectify the lack of government formation dates in the DPI, I weighted the ideology data by the duration of time each government spent in power. This is a valuable added dimension because two or three governments with different ideologi- cal preferences can coexist in the same year. The dates of government formation are coded using cabinet-formation dates or election dates when the cabinet-formation dates are unavailable. (See online Appendix 2 for the resources used for the data expansion.)

Using the revised dataset, two separate measure- ments were created to capture the ideological ori- entation of LDC political leadership: government ideology and chief executive ideology. When calculating government ideology in coalition democracies, I trea- ted multiple government parties as veto players. The idea is that participation in a coalition government

3Coding party ideology to three categories may be too coarse a mesh to accurately capture reality. Unfortunately, alternative party ideology data are not available for most LDCs. To check the quality of the government-ideology data, I compared them with the same measure based on two expert survey data; the left-right party spectrum for advanced industrial countries (Castles and Mair 1984) and five party classifications—left, center-left, center, center-right, and right—in Latin American countries (Coppedge 1997). I found that both measures are strongly correlated with government-ideology data (r . 0.90 for Coppedge’s data and r . 0.60 for Castles and Mair’s data). I also compared government- ideology data with the ‘‘legislative partisan balance’’ and ‘‘exec- utive partisan balance’’ data of Huber et al.(2006). They are also strongly correlated (r . 0.60).

4Although the religious-secular dimension is an important partisan distinction (Huber and Stephens 2001), religious parties are weaker and more heterogeneous in LDCs (Mainwaring and Scully 2003). Therefore, unless their ideological preferences are clear in available resources, religious parties are coded as missing. Regional and personalist parties are also treated as missing unless their preferences for state control of the economy are available in the resources.

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‘‘grants parties the right to veto legislation and provoke a government crisis if they so wish,’’ mean- ing all parties in a coalition government have ‘‘oppor- tunity to exercise veto power’’ on policy decisions (Tsebelis 2002:87). If the parties in the coalition government have ideological differences, the govern- ment policy position will typically revert to the common denominator among them. If a common denominator cannot be found, the government coali- tion will dissolve, and a new government will be formed.

The veto-player designation is important, be- cause if all parties in a coalition government are veto players, they should influence policy equally, irre- spective of the number of seats they hold in the legislature or government. This avoids any need for the measure of government ideology to be weighted according to seats held or other criteria and allows for simple arithmetic averaging instead. For example, if the coalition government is composed of one leftist and one rightist party, government ideology becomes ‘‘center,’’ regardless of the number of seats held by the respective parties. If the coalition government is composed of two leftist parties and one rightist party, government ideology becomes more ‘‘center-left.’’ Operationally, I first code the ideological positions of the parties in government (left 5 1, center 5 0, and right 5 –1), sum them, and then divide by the number of parties.

For authoritarian countries, government ideology is measured in two ways. Such governments can largely be divided into two categories, autocracies with party systems and autocracies without party systems (i.e., no parties are legally allowed). In the first instance, government parties are used to calcu- late government ideology in the same way as with democratic governments. When there are no parties, the dictator is assumed to be the only veto player in the system, and his/her ideology is used to cal- culate the government ideology.

Chief executive ideology is measured separately from government ideology. Chief executive is defined as a president in a presidential system, a prime minister in a parliamentary system, and a dictator in an autocratic regime. I constructed a separate measure for chief executive ideology because execu- tive leadership often plays a stronger role in shaping government policies in LDCs: it might not be the ideology of government parties but that of the chief executive that matters for government distributive policies. For example, while a president (or prime minister) with rightist ideology may cooperate with a center party in the business of governing, he/she may

still be able to employ rightist government policies rather than center-right ones.5

Controls. To isolate the effects of globalization and government ideology, I also include several important control variables that are likely to affect income inequality. First, the presence of democratic processes may channel the preferences of mass publics to more equal distributive policies. Democ- racy is measured by a dichotomous classification of the political regime, coding 1 for democracies and 0 for the residual category of authoritarian regimes. The measure and classification are drawn from Cheibub (Cheibub, Gandhi, and Vreeland 2010), who use a ‘‘minimalist’’ definition of democratic regimes which defines them as regimes in which citizens are periodically given the opportunity to choose their leaders in electoral contests, they are presented with more than one alternative, and the winners become the country’s leaders. This minimal- ist concept of democracy avoids most of the theoret- ical issues that animate empirical research on political regimes, particularly those questions about the level or length of a country’s democratic experience (Cheibub, Gandhi, and Vreeland 2010).

Second, the relationship between development and inequality is likely to be curvilinear with an inverted U-shape: inequality is expected to increase when development is in an early stage, i.e., when GDP per capita is low, but then decrease when the economy is fully developed (Kuznets 1955). Thus, GDP per capita and (GDP per capita)2 are included and expected to have positive and negative coeffi- cients, respectively.6 Third, short-term economic

5Because the ideological positions of nongovernment parties (except the largest opposition party) are not available in DPI, the organized power of the left is measured only with the ideological positions of ‘‘government parties.’’ Because previous studies (e.g., Huber, Ragin, and Stephens 1993) have consistently found that the ‘‘long-run partisan character of government’’ is a better predictor of welfare state generosity than left voters, left seats in parliament, or union organization, government ideology is a good proxy for the political power of the left. However, this article measures the ‘‘current’’ partisan character of government instead of its ‘‘long-run’’ counterpart. This is because it seeks to contribute to the current globalization debate by testing if the ideological preference of ‘‘current’’ incumbent government par- ties/chief executives shapes current income distribution in LDCs, and if this impact has declined under the constraint of market liberalization.

6(GDP per capita)2 is highly correlated with GDP per capita (r . 0.90). Yet, the main results in this article are robust even when the squared term is excluded from the model.

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growth, measured by annual percentage in change of real GDP may reduce income inequality, because growth is likely to reduce poverty (Ross 2006). Fourth, population growth is expected to increase income inequality in LDCs. An increase in the population leads to an increase in the population of younger (relatively unskilled) workers, which creates a surplus of unskilled labor and widens the wage gap between skilled and unskilled workers in LDCs (Alderson and Nielsen 1999). Fifth, education, meas- ured by secondary-school enrollment as a share of the secondary-school age population, is expected to reduce inequality by increasing the supply of more skilled (educated) workers and thereby reducing their received wage premium in response. Finally, if a society is fractionalized according to language, race, and religion, it is likely to be more averse to redistributive politics (Alesina, Baquir, and Easterly 1999). Accordingly, ethnic diversity, the sum of three indices, racial division, national language division, and religious division (Vanhanen 1999), is expected to be negatively associated with income inequality.

Models. In this article, I build a series of regres- sion estimates of income inequality between 1975 and 2005 for 59 developing countries in order to explain cross-national and longitudinal variation in income inequality. As in other large-N studies involving LDCs, annual data are available only for a few variables, countries, and years, and those missing are often authoritarian countries with favorable economic performance (Ross 2006). Therefore, the observations in my analysis are for five-year country averages (1975–79, 1980–84, 1985–89, 1990–94, 1995–99, and 2000–05). While a lagged dependent variable has popularly been used in studies of inequality (e.g., Reuveny and Li 2003), other authors such as Achen (2000) and Plümper, Troger, and Manow (2005) have argued that a lagged dependent variable biases significant independent variables downward, and instead they recommend adjusting for serial autocorrelation using an AR(1) process. Following Beck and Katz’s (1995) recommendation, I use panel-corrected standard errors to correct panel- level heteroskedasticity and contemporaneous spatial correlation, and I use an AR(1) process to adjust for serial correlation. Decadal dummies are included to control unmeasured period-specific effects such as global economic fluctuations, like the oil crisis in the 1970s. Country dummies are also included to control for unmeasured country-specific effects, such as long- term political history and the size of population and territory. In all, the model to be tested can be written as follows:

Income inequalityi;t ¼b1 Tradeþ b2 FDI

þ b3 Ideological orientation

þ b4 Democracy

þ b5 GDP per capita

þ b6 GDP per capitað Þ2

þ b7 GDP growth

þ b8 Population growth

þ b9 Secondary education

þ b10 Ethnic diversity

þ Sj bj Decade

þ Sk bk Country

þ mi;t

The model is used to analyze the effects of global- ization and government ideology on income inequality. As discussed above, globalization is represented by trade and FDI, and ideological orientation is the ideological position of the government parties or chief executives. In each equation, income inequality is measured via Gini coefficients. The subscripts i and t denote, respectively, the country and 5-year average of the observations. The j and k indicate, respectively, the decadal dummies and country dummies. In identifying the model, the intercept is suppressed.

Results of Pooled Time-Series Regression Analysis

My results are summarized in Tables 1, 2, and 3. Table 1 shows that both trade flows and FDI (the two global- ization variables) are strongly associated with higher income inequality. On the other hand, leftward move- ment of both government ideology and chief executive ideology are significantly associated with lower income inequality. The results are substantively meaningful. According to the result in regression (1), if a developing country enlarges trade flows (% GDP) by 38.31 (one standard deviation), then it is likely to increase income inequality by 1.15 (2.71% of the average Gini in the sample countries). If a developing country’s FDI (% GDP) increases by 2.31% (one standard deviation), then it is likely to enlarge income inequality by 1.08 (2.55% of the average Gini in the sample countries). When a government shifts its ideological position from rightist to leftist, it is likely to enhance income inequal- ity by almost 3.25 (7.66% of the average Gini).

The control variables show that the level of income inequality is driven not only by deliberate

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change in government policy, but also by adjustments resulting from changes in economic conditions and ethnic diversity. The control variables strongly sup- port the idea of the Kuznets curve: GDP per capita and (GDP per capita)2 have a positive and negative relationship with income inequality, respectively, meaning that income gaps increase in early stages of LDC development but decrease as the economy fully develops. While inconsistent, short-term eco- nomic growth shows some positive association with income inequality. Rapid economic growth in LDCs seems to benefit the rich proportionally more than the poor. Ethnic heterogeneity is consistently and positively associated with inequality, implying that larger income gaps exist alongside larger racial, linguistic, and religious divisions. On the other hand, the existence of democratic processes, population growth, and secondary education has little associa- tion with income inequality in LDCs.

Not only does government ideology directly affect income inequality, but it may also indirectly

mediate the impact of external pressures on income distribution: leftist governments may moderate the enlarged income gaps produced by market inte- gration compared to rightist counterparts. Table 2 reports the interactive effects of globalization and government ideology (trade3government ideology, FDI3government ideology, trade3chief executive ideology, and FDI3chief executive ideology) on income inequality. In regressions (5) and (6), trade flows are strongly and positively related with income inequal- ity, but the interaction term between trade and government ideology (trade3government ideology) is strongly and negatively associated with inequality. The results suggest again that trade flows have significantly enlarged income inequality in LDCs, but that the enlarged income gaps narrow when the government in power is more left-oriented.

While the coefficient and standard error esti- mates presented in the table give us a first look at the interactive impact of globalization and government ideology on inequality, the appropriate test for an

TABLE 1 The Impact of Globalization and Government Ideology on Income Inequality in LDCs, 1975–2005

Ideological Orientation Measured by

Government Ideology Chief Executive Ideology

[1] [2] [3] [4]

Globalization Trade flows (% GDP) 0.030* (0.022) 0.026* (0.021) 0.049** (0.025) 0.047** (0.023) FDI (% GDP) 0.467** (0.213) 0.476** (0.208) 0.496*** (0.192) 0.523*** (0.173)

Ideological Orientation Government ideology

–1 (right) to 1 (left) -1.623** (0.838) -1.856** (0.958)

Chief executive ideology –1 (right) to 1 (left)

-1.455*** (0.365) -1.419*** (0.540)

Controls Democracy 0.446 (1.187) 0.388 (1.102) 0.711 (1.264) 0.650 (1.163) GDP per Capita 0.001*** (0.0003) 0.001*** (0.0003) 0.001*** (0.0004) 0.001*** (0.0004) (GDP per Capita)2 -7.71e–08*** (1.46e–08) -8.08e–08*** (2.23e–08) -7.56e–08*** (2.33e–08) -8.31e–08*** (3.17e–08) Economic growth 0.126*** (0.050) 0.270** (0.135) -0.004 (0.037) 0.087 (0.105) Secondary education 0.005 (0.041) -0.005 (0.045) Population growth -0.600 (0.795) -0.559 (1.063) Ethnic diversity 0.266*** (0.026) 0.236*** (0.044) No. of observations 165 159 152 148 R-squared 0.995 0.995 0.996 0.996 Prob. . Chi-squared 0.000 0.000 0.000 0.000

Note: (1) The dependent variable is the Gini coefficient. The Gini coefficient ranges from 18.64 to 72.02 with a mean 5 42.38 and a standard deviation 5 12.42. See Appendix 1 for detailed variable descriptions. (2) The estimation is by least squares with standard errors corrected for panel heteroskedasticity. (3) The parentheses denote a panel-corrected standard error (adjusted for heteroskedasticity and contemporaneous correlation). Each regression also includes decadal dummies and country dummies (not shown for space), and the constant variable is suppressed. (4) Statistical significance is based on one-tailed tests. *** p , 0.01; ** p , 0.05; * p , 0.10.

globalization, ideology, and inequality 549

interactive model is to look at the specific shape of the 95% confidence interval (Brambor, Clark, and Golder 2006). Figure 1(a) depicts the conditional effect of trade flows on inequality. The figure graphi- cally illustrates the finding that trade has an increas- ing effect on inequality, but that as government ideology moves from rightist to leftist, the income gaps produced by trade flows decline. The size and significance of the income gaps increased by trade are largest under fully rightist government, but be- come insignificant under centrist/leftist government. Although the interaction terms between the global- ization variables and chief executive ideology are statistically insignificant, Figure 1(b) demonstrates that chief executive ideology also can significantly mitigate the expansionary pressure of trade flows on income inequality in LDCs. As chief executive ideology moves from rightist to leftist, the increasing

income gaps generated by trade flows decline and become insignificant.

Table 3 reports robustness tests of the main empirical results. Regressions (9) and (10) test the results with an alternative measure of government ideology: left%. This measure assumes that parties with more seats exercise more power in the govern- ment in terms of policy outcomes. For example, if leftist parties in a coalition government have 90% of the seats, it is assumed that the government will steer 90% leftist on policy decisions. In general, the leftist share of government would ideally be measured by leftist parties’ share in government (i.e., share of total government portfolios) or in the legislature (i.e., share of total seats in the legislature). Unfortunately, such data for government portfolios and opposition parties’ ideology is unavailable for most LDCs. Therefore, I employ an alternative measure: leftist

TABLE 2 The Interactive Impact of Globalization and Government Ideology on Income Inequality in LDCs, 1975–2005

Ideological Orientation Measured by

Government Ideology Chief Executive Ideology

[5] [6] [7] [8]

Globalization Trade flows (% GDP) 0.034** (0.018) 0.030* (0.019) 0.050*** (0.019) 0.049*** (0.017) FDI (% GDP) 0.465** (0.211) 0.479*** (0.204) 0.546** (0.267) 0.598** (0.261)

Ideological Orientation Government ideology

–1 (right) to 1 (left) -0.600 (0.900) -0.646 (0.959)

Trade3government ideology -0.018*** (0.006) -0.020*** (0.005) FDI3government ideology 0.137 (0.256) 0.112 (0.281) Chief executive ideology

–1 (right) to 1 (left) -0.483 (0.997) -0.272 (0.849)

Trade3chief executive ideology

-0.012 (0.015) -0.012 (0.014)

FDI3chief executive ideology

-0.081 (0.347) -0.149 (0.372)

Controls Democracy 0.162 (1.141) 0.064 (1.056) 0.492 (1.157) 0.465 (1.063) GDP per Capita 0.001*** (0.0002) 0.001*** (0.0003) 0.001*** (0.0004) 0.001*** (0.0004) (GDP per Capita)2 -7.61e–08*** (1.40e–08) -7.69e–08*** (2.58e–08) -6.61e–08*** (2.27e–08) -7.11e–08 *** (3.07e–08) Economic growth 0.116** (0.058) 0.256** (0.130) -0.014 (0.044) 0.073 (0.092) Secondary education 0.004 (0.036) -0.012 (0.034) Population growth -0.612 (0.801) -0.513 (1.040) Ethnic diversity 0.273*** (0.023) 0.261*** (0.028)

No. of observations 165 159 152 148 R2 0.995 0.995 0.996 0.996 Prob. . Chi-squared 0.000 0.000 0.000 0.000

Note: (1) The dependent variable is the Gini coefficient. The Gini coefficient ranges from 18.64 to 72.02 with a mean 5 42.38 and a standard deviation 5 12.42. See Appendix 1 for detailed variable descriptions. (2) The estimation is by least squares with standard errors corrected for panel heteroskedasticity. (3) The parentheses denote a panel-corrected standard error (adjusted for heteroskedasticity and contemporaneous correlation). Each regression also includes decadal dummies and country dummies (not shown for space), and the constant variable is suppressed. (4) Statistical significance is based on one-tailed tests. *** p , 0.01; ** p , 0.05; * p , 0.10.

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government parties’ seats in the legislature as a share of all government parties’ seats in the legislature. The results support my substantive conclusions: stronger leftist power in government is associated with lower inequality, and it moderates the inequality otherwise enlarged by globalization.

Regressions (11)–(14) test the results using two alternative measures of democracy: the level of the democracy and the age of the democracy. First, following the precedent of many other studies on democracy and income inequality, the level of de- mocracy, here called polity, was measured as the difference between the democracy index and the autocracy index in the dataset Polity IV and ranged from –10 (representing the most autocratic regimes)

to 10 (the most democratic regimes; Marshall and Jaggers 2008). Contrary to the general expectation, polity is strongly and positively associated with income inequality (regressions [11] and [12]). This result suggests that the richest quintile of the pop- ulation often gains the most from the introduction of competitive elections in LDCs, which is consistent with the work of other scholars (e.g., Nel 2005). Regressions (13) and (14) also shows that the length of democratic history—the age of democracy—has no significant impacts on inequality. While not reported, I checked if democracy has a parabolic relationship to income inequality (following Burkhart 1997 and Rudra 2008) by including a democracy measure (democracy dummy, polity, or age of democracy)

TABLE 3 Robustness Tests

Left % Polity Age of Democracy Lagged Dependent

Variable

[9] [10] [11] [12] [13] [14] [15] [16]

Globalization Trade flows

(% GDP) 0.024

(0.020) 0.033**

(0.018) 0.026

(0.022) 0.028*

(0.021) 0.025

(0.023) 0.028*

(0.021) 0.045***

(0.015) 0.038*

(0.024) FDI (% GDP) 0.461**

(0.214) 0.659***

(0.245) 0.329*

(0.257) 0.344*

(0.266) 0.481***

(0.198) 0.479***

(0.195) 0.509***

(0.179) 0.831***

(0.168)

Political Conditions Government

ideology –1 (right) to 1 (left)

-1.676** (0.952)

-1.043 (1.155)

-1.819** (1.028)

-0.666 (0.957)

-1.724** (0.853)

1.018 (1.882)

Trade3government ideology

-0.012** (0.007)

-0.020*** (0.005)

-0.018 (0.026)

FDI3government ideology

0.110 (0.270)

0.117 (0.309)

-1.046*** (0.370)

Left% 0 to 100

-0.029*** (0.012)

0.0001 (0.014)

Trade3Left% -0.0003** (0.0001)

FDI3Left% -0.004 (0.005)

Democracy dummy 0.402 (1.122)

0.258 (1.087)

1.497* (0.962)

1.519* (1.043)

Polity 0.267*** (0.084)

0.233*** (0.096)

Age of democracy -0.011 (0.024)

-0.006 (0.027)

Past inequality 0.148* (0.107)

0.130 (0.118)

No. of observations 159 159 157 157 159 159 108 108 R-squared 0.995 0.995 0.995 0.995 0.995 0.995 0.994 0.995 Prob. .

Chi-squared 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Note: See note in Table 1. Control variables, decadal dummies, and country dummies are not shown due to space constraints. The constant variable is suppressed. Statistical significance is based on one-tailed tests. *** p , 0.01; ** p , 0.05; * p , 0.10.

globalization, ideology, and inequality 551

and its squared term in my regressions. However, the results did not follow the expectation, and the squared terms did not have any statistical signifi- cance. I also checked for any endogeneity problems between the democracy and inequality variables, but a Durvin-Wu-Hausman test did not indicate any.

Income inequality may depend on the level of past inequality rather than contemporary govern- ment ideology. However, even when past inequality is considered, government ideology is still strongly and negatively associated with income inequality, and its interactions with globalization variables are negatively related with inequality (see regressions [15] and [16]). Based on previous literature, I also tested the results with a large number of other control variables, includ- ing terms of trade, budget deficits, inflation, population size, unemployment rate, potential labor power (Rudra 2008), urbanization, economic structure (i.e., size of agricultural sector), and oil exports. Most of these controls were excluded from the final model to avoid problems of multicollinearity and to enhance the completeness of data coverage and clarity of presenta- tion. It should be emphasized that none of the controls excluded from the final reports altered any of my basic substantive findings.

Discussion and Conclusion

This article theoretically and empirically evaluates the impact of globalization and government ideology on

income inequality in LDCs and yields the following conclusions. First of all, the findings are in accord with ‘‘technology-centered globalization-inequality thesis,’’ i.e., that increased trade flows and FDI have expanded income inequality in LDCs. On the other hand, governments with leftist parties and chief executives have significantly mitigated income gaps and have in fact moderated the expansionary pressure of the integrated world market on income inequality, compared to their rightist counterparts. These find- ings lend support to the notion that redistribution from rich to poor is a more explicit concern of the left than of the right, since left-leaning governments are more successful in mitigating income inequality.

Still, these results raise questions, particularly given that several leftist governments in LDCs have recently liberalized their domestic markets, privatizing state-owned enterprises and deregulating industries. Can leftist governments continue to pursue redistrib- utive policies under the competitive pressures of an integrated world market? Perhaps some answers can be gleaned from the political economy of advanced industrial countries. In the liberal international order after World War II, the advanced countries had to liberalize their markets to promote economic growth, but provided social services to compensate those who were harmed and dislocated by the process (Ruggie 1982). The strength of leftist parties in government played a critical role in determining the extent and depth of this redistribution.

Most governments in LDCs are now confronting similar situations. Increased trade and FDI are

FIGURE 1 Marginal Effects of Trade on Income Inequality (Gini)

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pursued to promote economic growth and improve national welfare (Makki and Somwaru 2004). Citi- zens in LDCs also strongly support free trade, multinational corporations, and free markets (PRC 2007). In this political environment, protectionism is not a viable option for governments to pursue. Nonetheless, the rise of inequality under the com- petitive international market leaves us wondering whether LDC governments are willing and able to provide the same quality of redistribution their wealthy counterparts did to smooth the process along. This question is a prominent one in the minds of citizens in LDCs, who are concerned about increasing inequality despite their general support for globalization (PRC 2007).

Ironically, rising inequality coupled with this concern about globalization provides fertile grounds for leftist governments to maneuver. In fact, it seems that leftist parties in LDCs have been strengthened electorally to the extent they can effectively articulate concerns about the social deficits of market liberal- ization. Recent leftist electoral victories in Latin America have been attributed to the electorates’ search for a refuge in left-leaning governments from widespread insecurity. In keeping with the results of this article, recent studies on LDCs also show that voters support leftist governments more under con- ditions of market liberalization, as leftist governments are demonstrably more inclined to respond to de- mands for redistribution and expanded public ex- penditures (Kim 2010; Stokes 2009).

If leftist governments’ redistributive policies can only achieve equality at the cost of hampered eco- nomic growth, they will eventually be forced to return to conservative/liberal policies and accept greater inequality in return for growth. On the other hand, inequality in itself is a significant barrier to economic growth. Increasing income gaps between rich and poor produce social tension, conflict, and instability, all of which hinder economic growth (Alesina and Perotti 1996). In this regard, it is leftist governments that (somewhat ironically) may ultimately be more suitable for fostering successful globalization, despite their constraints by growth concerns. Although outwardly more compatible with economic liberalization, the evidence suggests rightist governments do so at the cost of inequality-enhancing outcomes, which may be ultimately counterproductive to continued eco- nomic liberalization. However, leftist government policies require the fiscal capacity to maneuver, which requires growth, which requires liberalization. This leads to the final conclusion that, in the global era, the distinct policies and preferences of leftists, centrists,

and rightists alike will continue to be closely interre- lated with each other.

Acknowledgments

For help with various aspects of this article, I am grateful to Acir Almeida, Puspa Amri, Rachelle Andrus, Richard Baum, Lisa Blaydes, José Antonio Cheibub, Seung-whan Choi, Geoffrey Garrett, Barbara Geddes, Tasos Kalandrakis, Brett Kocher, Edward Leamer, Dong-wook Lee, Melissa Rogers, Ronald Rogowski, Jae Hyeok Shin, George Tsebelis, the editors, and three anonymous reviewers.

Appendix 1. How Income Inequality was Measured

While the Gini coefficient (hereafter, Gini) is prob- ably the most used measure of income inequality, it is difficult to compare one Gini with another, because the methods used to compute Gini can differ in various ways, including the concept being measured (income inequality versus consumption inequality), the measure of income (gross versus net), the unit of observation (individual versus household), and the coverage of the survey (national versus subnational).

First of all, income-based measures are bound to show higher inequality than consumption-based measures. Even when income is unusually low for some households and high for others, consumption will be more equal because of the consumption- smoothing opportunities provided by saving or bor- rowing. Second, gross income-based measures should yield higher inequality than net income-based meas- ures due to the potential for redistribution through the tax system. Welfare will differ prior to or following the individual’s payment of taxes and receipt of benefits. Therefore, the difference between the gross and net income can be significant in progressive tax systems. Third, individual-level measures may report higher inequality than household-level measures, because households may contain more than one wage-earning member (and are more likely to do so when individual incomes are lower). Household-level measures are thus considered the better measure of welfare, but the household-level measures need also be weighted by aggregate household size. Finally, the quality of the survey varies across countries because some countries conduct their survey only on the subnational level (Deininger and Squire 1996).

globalization, ideology, and inequality 553

To overcome these problems, Deininger and Squire (1996) compiled master statistics on house- hold income inequality. They first assembled as many income distribution variables as possible, and then filtered out the observations that did not satisfy three minimum standards for ‘‘high-quality’’: (1) the data must be based on household surveys; (2) the pop- ulation covered must be representative of the entire country; and (3) the measurement of income/con- sumption must be comprehensive, including income from self-employment, nonwage earnings, and non- monetary income. To adjust for the differences between income-based and consumption-based measures, they also systematically increased all consumption-based measures by 6.6 points, the average difference between income-based and consumption-based Ginis.

The recent Standardized World Income Inequal- ity Database (SWIID) assembled by Stolt (2009) covers the largest possible number of countries (n 5 153) and years (t 5 45). SWIID uses a five- year weighted moving average of inequality to gen- erate its data; it is premised on the assumption that near-time estimates of inequality will vary only moderately from each other; and it reports counter- instances as errors. By so doing, however, the SWIID generates overestimates of inequality before major political transitions and underestimates inequality after them. For this reason Solt (2009) does not use this moving average during the transition period of Eastern Europe and the Soviet Union.

Because the present study tries to capture the changes of inequality associated with political tran- sitions, this paper measures inequality with WIID, which does not treat the dramatic yearly differences in inequality as errors. When SWIID is used, the results for chief executive ideology still hold (p , 0.01), while those for government ideology become statistically insignificant, though with the same negative signs (p , 0.15).

Appendix 2. Resources Used to Code the Ideology of Governments and

Chief Executives

To obtain data on government party composition and distribution of legislature seats, I used two resources. First, I generally coded the partisan com- position of government using the Database of Polit- ical Institutions (DPI) from the World Bank (2010). I also used the Political Handbook of the World (various

years), Europa World Year Book (various years), Keesing’s Contemporary Archives (various years), the Global Database of Political Institutions and Economic Performance by Cheibub and Tasos (not publicly available at present), Party Government in 48 Democ- racies (1945–1998) by Woldendorp, Keman and Budge (2000), the ZPC collection World Political Leaders 1945–2011 (available at http://www.terra.es/ personal2/monolith/00index.htm), Regional Surveys of the World by Europa (various years), and the Election Results Archive from the Center on Democratic Performance (available at http://cdp.binghamton. edu/era/countries). Second, I coded the partisan composition of European countries using the Polit- ical Data Yearbook in the European Journal of Political Research (various years), the ZPC collection European Governments (available at http://www. terra.es/personal2/monolith/00europa.htm), and the Handbook of Political Change in Eastern Europe by Berglund, Ekman, and Aarebrot (2004). The partisan composition of Latin American countries was cross- checked with Latin American coalition government data by Acir Almeida (not publicly available at present).

DPI determines ‘‘whether the orientation of a party was immediately obvious from its name or its description in the Political Handbook of the World.’’ Then, the data was cross-checked with the European website Agora Telematica, edited by Wilfried Derksen, as well as with the findings of several other publications: Political Parties of Africa and the Middle East by East and Joseph (1993), Political Parties of Eastern Europe and the Successor States by Szajkowski (1994), and ‘‘Expert Interpretations of Party Space and Party Locations in 42 Societies’’ by Inglehart and Huber (1995).

To code governing parties not described in the DPI, I incorporated coverage of Latin American party ideology using codes from Coppedge’s (1997) ‘‘A Classification of Latin American Political Parties.’’ For this dataset, 53 country specialists code parties in 11 Latin American countries from the early 1900s to the mid-1990s. Second, the ideological positions of parties in central and east European countries were based on Klingemann et al.’s (2006) party manifesto dataset. Because this dataset covers elections only in the early 2000s for 24 Central and East European countries, few changes were introduced by the com- parison. Finally, the data was cross-checked and additionally expanded with Leftist Parties of the World (available at http://www.broadleft.org), Wikipedia (available at http://en.wikipedia.org/wiki/List_of_ political_parties), the Hutchinson Encylopaedia’s

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‘‘Country Facts’’ (available at http://www.talktalk.co. uk/reference/encyclopaedia/hutchinson/index_a.html), Armingeon and Careja’s (2004) ‘‘Comparative Data Set for 28 Post-Communist Countries, 1989–2004,’’ the Handbook of Political Change in Eastern Europe and BBC news (available at http://news.bbc.co.uk/2/hi/ middle_east).

While most of the sources code leftist/rightist parties in similar ways, the codes are sometimes mixed for center parties (i.e., center-left, center, and center-right). In my dataset, I code center-left and center-right parties as left and right parties, respec- tively. This means that if the ideological positions of center-left and center-right parties are actually closer to the center, this coding may create some measure- ment errors. To check the robustness of the results using this government ideology classification, I cre- ated a conservative measure of government ideology which excludes governments with these problems.

This conservative ideology measure was also strongly and negatively associated with income inequality.

References for Appendices:

Armingeon, Klaus, Philipp Leimgruber, Michelle Beyeler, and Sarah Menegale. 2008. Comparative Political Dataset 1960– 2005. Institute of Political Science, University of Berne.

Berglund, Sten, Joakim Ekman, and Frank H. Aarebrot. eds. 2004. The Handbook of Political Change in Eastern Europe. Cheltenham, UK: Edward Elgar.

Cheibub, José Antonio, and Tasos Kalandrakis. (not publicly available at present). Global Database of Political Institutions and Economic Performance. Globalization and Self- determination Project: Yale Center for International and Area Studies (YCIAS).

Coppedge, Michael. 1997. ‘‘A Classification of Latin American Political Parties.’’ Working Paper #244. The Helen Kellogg Institute for International Studies. University of Notre Dame.

Appendix 3 Average Income Inequality (Gini), 1975–2005

Country Name Average

(1975-2005) Average

(1975-1989) Average

(1990-2005) Country Name Average

(1975-2005) Average

(1975-1989) Average

(1990-2005)

Bahamas 45.33 46.51 42.99 Malaysia 48.71 49.13 48.08 Bangladesh 33.41 33.35 33.50 Mali 64.56 n.a. 64.56 Bolivia 54.14 n.a. 54.14 Mauritania 63.00 72.02 53.99 Brazil 58.72 58.36 59.08 Mauritius 40.67 42.67 36.69 Bulgaria 31.87 23.13 40.60 Mexico 52.67 50.67 54.68 Burkina Faso 69.19 n.a. 69.19 Mongolia 33.20 n.a. 33.20 Cambodia 39.78 n.a. 39.78 Morocco 38.00 39.19 37.40 C. African Rep. 63.20 n.a. 63.20 Nicaragua 50.30 n.a. 50.30 Chile 56.12 53.28 57.07 Niger 42.95 n.a. 42.95 China 32.92 31.28 36.20 Pakistan 33.64 34.05 33.02 Colombia 54.37 52.85 55.38 Panama 54.59 52.04 56.29 Costa Rica 47.02 46.91 47.14 Peru 46.96 46.05 47.87 Czech Rep. 21.90 20.70 23.70 Philippines 46.94 45.24 48.64 Ecuador 57.93 n.a. 57.93 Poland 27.47 24.66 31.70 Egypt 42.89 n.a. 42.89 Romania 26.93 23.38 28.71 Estonia 37.55 n.a. 37.55 Russian Fed. 29.75 25.72 35.79 Gambia 67.90 n.a. 67.90 Senegal 48.15 n.a. 48.15 Ghana 42.74 44.06 42.09 Slovak Rep. 20.92 20.26 21.86 Guinea 60.56 n.a. 60.56 Slovenia 23.65 n.a. 23.65 Guinea-Bissau 48.07 n.a. 48.07 South Africa 57.66 n.a. 57.66 Guyana 53.64 n.a. 53.64 Sri Lanka 43.55 40.13 48.97 Honduras 55.45 58.13 54.11 Taiwan 29.93 28.95 31.40 Hungary 23.49 21.93 25.84 Tanzania 45.58 n.a. 45.58 India 31.55 31.68 31.34 Thailand 50.28 47.29 53.28 Indonesia 35.79 34.88 37.16 Turkey 46.58 44.16 49.00 Jamaica 47.86 46.83 48.20 Uganda 43.75 33.00 49.12 Jordan 39.64 38.45 42.03 Venezuela 44.06 43.45 44.67 Kenya 56.66 n.a. 56.66 Yemen, Rep. 39.50 n.a. 39.50 Lao PDR 30.40 n.a. 30.40 Zambia 55.96 51.00 58.45 Madagascar 46.13 n.a. 46.13

globalization, ideology, and inequality 555

East, Roger, and Tanya Joseph, eds. 1993. Political Parties of Africa and the Middle East. Harlow, UK: Gale Group Publishers.

Europa World Yearbook, various years. London: Europa.

European Journal of Political Research, Political Data Yearbook, various issues. Dordrecht, The Netherlands: Boston.

Huber, John, and Ronald Inglehart. 1995. ‘‘Expert Judgments of Party Space and Party Locations in 42 Societies.’’ Party Politics 1 (1): 73–111.

Keesing’s Contemporary Archives, various years. London: Kees- ing’s Limited

Klingemann, Hans-Dieter, Andrea Volkens, Judith Bara, Ian Budge, and Michael Macdonald. 2006. Mapping Policy Pref- erence II: Estimates for Parties, Electors and Governments in Eastern Europe, the European Union and the OECD, 1990– 2003. Oxford: Oxford University Press.

Regional Surveys of the World, various years. London: Europa.

Solt, Frederick. 2009. ‘‘Standardizing the World Income Inequal- ity Database.’’ Social Science Quarterly 90 (2): 231–42.

Szajkowski, Bogdan. 1994. Political Parties of Eastern Europe, Russia and the Successor States. Harlow Essex, UK: Longman.

The Political Handbook of the World, various years. Binghamton: State University of New York.

Woldendorp, Jaap, Hans Keman, and Ian Budge. 2000. Party Government in 48 Democracies (1945–1998). Dordrecht, The Netherlands: Kluwer Academic Publishers.

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Eunyoung Ha is an Assistant Professor at Clar- emont Graduate University, Claremont, CA, 91711.

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