Inclusive Democracy and Economic Inequality in South Asia: Any Discernible Link?
(Forthcoming in the Review of Social Economy)
Udaya R. Wagle
School of Public Affairs and Administration, Western Michigan University, USA
Abstract
Studies of the relationship between political democracy and economic inequality have produced
diverse findings. This study attempts to mitigate some conceptual and methodological problems
inherent in such studies by using multi-indicator concepts of inclusive democracy and economic
inequality. Data from the five major historically and culturally homogeneous South Asian countries
covering 1980-2003 suggest some bidirectional, positive relationship between inclusive democracy
and economic inequality indicating that democracy and equality may not be fully compatible in this
region. The paper offers contextual explanations and some mechanisms that may have led to these
findings for the region, somewhat deviating from the conventional arguments.
Keywords: Inclusive Democracy, Political and civil liberties, Democratic institutions, Economic
Inequality, Panel data, South Asia
I. Overview
How political democracy and economic inequality interact is hardly a new issue. Much of the
developed world has long embraced political democracy, where as much of the underdeveloped
world has had either insularly authoritarian or other less-than democratic regimes or has switched
back and forth between these. At the same time, much of the western democratic hemisphere
manifests lower levels of economic inequality where as some if not most of the less-democratic
countries in the South and especially in Africa and Latin America are economically more unequal.
This is perhaps an overgeneralization of the breadth and depth of the interface between democracy
1
and inequality as experiences are often uniformly region, if not country, specific. No clear cleavage
exists between the experiences of the democratic and authoritarian countries in their economic
structures and outcomes.
This paper attempts to uncover the relationship between ‘inclusive democracy’ and ‘economic
inequality,’ using data covering 1980-2003 from the five major countries in South Asia—
Bangladesh, India, Nepal, Pakistan, and Sri Lanka.1 This region includes a combination of steadily
democratic polities as well as politically highly volatile countries. On the one hand is India, the
largest democratic polity practicing ‘representative democracy’ the way it is popular in the western
hemisphere. On the other hand is neighboring Pakistan, a notoriously autocratic regime for much of
its history that is as old as India’s. Other countries are in between: Nepal is embracing constitutional
monarchy where as Sri Lanka and Bangladesh have a presidential system. From the religious
standpoint, Nepal is a Hindu state, Pakistan and Bangladesh are Islamic states, and India and Sri
Lanka are secular states. These realities have had enormous implications for the overall political and
economic landscape in each country. Since these countries are witnessing increasingly diverse
economic structures, I intend to test a bidirectional relationship between inclusive democracy and
economic inequality in this region.
This paper is organized as follows. Next section surveys major theoretical discussions. Section
three develops relevant hypothesis and describes the data with section four focusing on the trend on
inclusive democracy and economic inequality in the region. Section five estimates models and
presents results, which are then discussed in section six. Last section concludes with directions for
future research.
II. Democracy-Inequality Nexus
2
The global march for democracy in the post World War II era and a range of country performances
on economic prosperity raised interest in assessing whether a part of the progress made was due to
the development of democratic polities. The fact that many of the less-developed countries could
not sustain democracy and turned back to authoritarianism or communism also served as an impetus
to research the possible contribution of democracy to economic performance and vice versa. Some
scholars, Lipset (1959), for example, saw the role of economic performance on sustaining
democracy by improving the lot of those at the bottom stratum as determined by class struggle
especially through universal adult suffrage. For others such as Dahl (1971), democracy provided
checks and balances to undo some of the inequities produced by capitalism so that the extreme
inequalities would not propagate civil unrest, threatening democracy as happened in parts of Latin
America. Yet others (Lijphart 1977; Rustow 1970) observed the vision and benevolence of the elites
strengthening democratic processes and institutions so that once fully operational they would not be
removed by economic dynamics and misfortunes. Even the issue of how a country embraces a
democratic path has drawn contentious debates with some viewing democracy to be endogenously
dependent on economic development (Lipset 1959, 1994) and others finding no particular role of
economic development on the evolution of democracy (Przeworski and Limongi 1997; Przeworski,
Alvarez, Cheibub, and Limongi 2000).
Due to the centrality of universal adult suffrage in a democratic system, inequality in economic
outcomes is considered to escalate class struggles and threaten democracy (Lipset 1994; Muller
1995; Tilly 2003). While there have been increasing concerns over how worsening economic
conditions of the lower classes may pose a threat to the business of democracy (Doorenspleet 2002;
Lipset 1994; Muller 1988; Zafirovski 2002), democratic regimes are more likely than authoritarian
regimes to introduce redistributive policies to eschew unfavorable political outcomes and survive
3
(Dahl 1971; Lipset 1959; Przeworski 2005). At the same time, many find increasing economic
inequality in many western countries and particularly in the United States highly enigmatic to
explain (Alderson and Nielsen 2002; Galbraith 1998). Although these countries obtain consistently
high rankings on the quality of democracy, political inequalities are intense as manifested in the low
levels of electoral turnout, widespread mistrust of government, and government’s unresponsiveness
to minority needs (Bartels 2006; Zafirovski 2002).
In case of the developing countries, on the other hand, the history of feudal or clique governments
and widespread illiteracy often render regimes politically volatile. Preexisting clientelistic
relationships between government officials and the public make it difficult for the latter to seek
accountability from the former, resulting in massive government inefficiencies and fraud (Jeffrey
2002). As Karl (2000) contends, for example, authoritarian regimes flourish amidst high economic
inequality since those in power distrust political institutions and violate human rights. Because of
the affirmative role of political democracy in providing the political playing field, international
development organizations vigorously promote democracy in the developing world (UNDP 2002;
World Bank 2005a).
Whether democracy or inequality ought to be regarded as the outcome is debatable. But it is also
important to examine the effect of democracy on inequality. Because the central premise of
democracy is political equality to level the playing field, it is also expected to help institute policies
that redistribute resources and reduce economic inequality (Rueschemeyer 2005). Political equality,
among others, guarantees political rights and civil liberties, adheres to the rule of law, and
establishes processes and institutions that are accountable to the public (Beetham 2005; Dahl 1998;
O’Donnell 2005). The role of the media, civil society, and competitive elections is instrumental to
effect the desired policy changes (Dahl 1998; Lipset 1994). The popular median voter hypothesis,
4
for example, is one explanation of how competitive elections can help reduce economic inequality
especially if the median voter’s economic position aligns with those at the lower stratum of the
distribution, a very likely scenario in many countries with high inequality today. By formalizing
class struggle through elections, democracy may lower economic inequality especially as median
voters seek increased redistribution thus benefiting themselves and the less well off. Even in more
democratic countries, however, increasing economic inequality may sometimes prove
counterintuitive to the idea of political equality, class struggle, or median voter hypothesis. In the
United States, for example, there are concerns that the government has been increasingly responsive
to the privileged, perhaps worsening the situation of the less fortunate (APSA Task Force 2004;
Jacobs and Skocpol 2006; Piven 2006; Scholzman 2006).
III. Hypothesis and Data
Previous studies have mostly investigated the relationship by treating either democracy or economic
inequality as the outcome variable. Studies treating democracy as the outcome variable have found
either significant negative effect of economic inequality (Ember, Ember, and Russett 1997; Muller
1995; Przeworski et al 2000) or no effect at all (Bollen and Grandjean 1981) suggesting that low
economic inequality is at least not detrimental to democracy. Studies focusing on the effect of
democracy have also found either significant negative effect (Justman and Gradstein 1999; Mahler
2004; Reuveny and Li 2003; Rodrik 1998) or no effect (Gradstein, Milanovic, and Ying 2001)
suggesting that democracy does not at least inhibit the goal of reducing economic inequality. There
are also suggestions that the relationship is rather curvilinear indicating that a democratic regime
may fully when economic inequality is moderate (Midlarsky 1997) and/or that economic inequality
may be at the pinnacle when a country is moderately democratic (Justman and Gradstein 1999;
5
Simpson 1990).
While democracy and economic inequality can both be considered outcome variables and
therefore estimating the bidirectional relationships may be appropriate, findings on this have also
diverged. Bollen and Jackman (1995), for example, find no significant relationship where as Chong
and Gradstein (2004) and Muller (1988) find significant negative relationship, further noting that
democratic transformation with high inequality undermines the legitimacy of the regime, causing it
to revert back to authoritarianism.
Part of the reason why findings do not converge might have to do with how democracy and
economic inequality are operationalized. The difference in the concept of democracy used by
Bollen and Jackman (1995) and Muller (1988) is quintessential, as the former captures the
substantive aspects of democracy and the latter refers to its length or stability.2 Chong and
Gradstein (2004), moreover, focus on the relative strength of political institutions. Similar
differences exist between using democracy as a multi-indicator construct and as a single indicator
variable (Bollen 1990). On the economic inequality front, too, where as the dominant practice has
been to use Gini index as its proxy measure, what basis is used to derive this measure can have
profound impact on outcomes. The use of factor income, disposable income, or consumption, for
example, would suggest different magnitudes of inequality, as would using the household or
individual distribution and between- or within-country inequality3 (Firebaugh 2003; Milanovic
2005).
Despite these differences observed mostly at the global scale, there is enough foundation to
hypothesize that inclusive democracy and economic inequality have mutually reinforcing negative
relationship in South Asia. An absence of this relationship would make the global project of
democratization less convincing. Prior to developing other specific hypotheses dealing with how
6
inequality and democracy interact, however, it is important to provide operational definitions of the
two variables. First, in line with Bollen (1990) and Bollen and Paxton (2000), I use an inclusive
concept of democracy defined as ‘a set of political practices aimed at minimizing the power of the
elites and maximizing that of non-elites or ordinary citizens.’ Consistent with Dahl’s (1971, 1998)
nomenclature,4 this approach underscores inclusive democracy as a multi-indicator construct
including development of democratic institutions and the degree of political and civil liberties.5 I
use the democracy variable from the Polity IV Project (2005) dataset for the former and the
aggregate of the political rights and civil liberties variables from the Freedom House (2005a)
dataset for the latter. Operationalized as a composite index of ‘a mature and internally coherent
democracy’ (Marshall and Jaggers 2005), the democratic institutions variable captures the
development of institutions with heavy emphasis on the recruitment and functionings of the chief
executive and some weight on the competitiveness of elections and political participation. As
defined by the Freedom House (2005b), the political and civil liberties variable captures the
political rights and freedom that people enjoy in political processes (including electoral process,
political pluralism and participation) and functioning of governments and the liberties that are the
cornerstones of civil life (including freedom of expression and belief, rights to join associations,
rule of law and personal autonomy, and individual rights). This multi-indicator approach to
measuring inclusive democracy further allows a test of more specific hypotheses involving how
democratic institutions and political and civil liberties interface with economic inequality. Since the
development of democratic institutions gauges the strength of the executive to pursue its own
agendas with proper checks and balances, I expect to find it useful to pursue equality of
opportunities and thus reduce economic inequality. Moreover, I expect the political and civil
liberties variable, representing the extent of freedom people enjoy in their lives, to help level the
7
playing field, thus supporting egalitarian outcomes.
Second, I broaden the concept of economic inequality to capture its different aspects involving
multiple indicators. To keep the analysis theoretically consistent as well as operationally feasible,
however, I use Gini index and the ratio of consumption for the top to bottom quintile as its
indicators. The former indicates the deviation of the entire distribution from perfect equality, where
everyone would hold exactly the same level of economic resources. Because this overall deviation
fails to measure the magnitude of inequality between those on the top and bottom of the
distribution, the consumption differential measuring variations at the two moderate extremes6 would
complement the former. Data on these indicators are drawn from the WIDER (2005) with more
recent comparable data on Nepal and Pakistan extracted from the (World Bank 2006). I expect to
find both indicators of inequality to support the overall hypothesis of negative relationship with
democracy. Depending on the size of the middle class, however, these two indictors may also play
out differently.
Finally, it is important to control for the effects of other relevant factors. The levels of economic
development and globalization (per capita gross domestic product—GDP) and foreign trade are
perhaps the most important of them, with their effects expected to be positive on both democracy
and inequality. Other control variables include electoral participation and poverty incidence at the
international threshold $1/day of income. I hypothesize that the former would negatively affect
economic inequality through people’s active participation in governance and policymaking, where
as the latter manifesting the economic and social vulnerability of those at the bottom of the
distribution would alienate them and undermine democracy. Data on these variables are drawn from
the World Bank (2005b) and IIDEA (2006). In addition, while there are a host of other potentially
relevant variables including education, migration, corruption, labor market dynamics, and civic and
8
cultural activism, they are either highly correlated with the included variables or reliable data are
not available on them.7
IV. A Comparative Picture
Inclusive Democracy: Estimates reported in Table 1 suggest that the countries in South Asia have
undergone considerable swings between democracy and authoritarianism. First, India scores
consistently high on political and civil liberties and especially democratic institutions throughout
the period, with all other countries experiencing major upheavals on at least one of these counts.
These statistics are consistent with the movement of political processes between authoritarian and
democratic regimes, with Pakistan’s movement at the former end and India’s at the latter end.
(Insert Table 1 here)
Statistics on political and civil liberties were comparable between the 1980s and 2000s in much of
the region except in Pakistan where some progress of the 1990s significantly receded by 2000,
immediately after the ascendance of the military government in power. Bangladesh and Sri Lanka
made a positive move during the period, where as the situation in Nepal slightly worsened. Clearly,
the democratic movement appears to have culminated in the early 1990s in Bangladesh, Nepal, and
Pakistan with the formation of governments through multiparty electoral processes and the
constitutional guarantee of political and civil liberties. In India and Sri Lanka, however, the 1990s
registered a slight setback on the fundamental rights of citizenship as a result of escalating political
violence and/or ethnic and religious tensions. In terms of the development of democratic
institutions, on the other hand, surprisingly large variations existed throughout the period in
Bangladesh, Nepal, and Pakistan with Sri Lanka and especially India scoring consistently high.
While Nepal, Pakistan, and especially Bangladesh started out as totally autocratic regimes,
9
Bangladesh recorded a steady progress and the progress made during the 1990s in Nepal and
especially Pakistan was effectively reverted back to the autocratic regime by the end of the period.
Second, although the overall state of political and civil liberties remained largely unchanged
during the period, the region was identifiably better positioned on the development of democratic
institutions. Both country and population averages show no improvement on political and civil
liberties but a remarkably high score of India with its massive population makes the state of
democratic institutions considerably improve for the entire region following the population average.
Overall, while average person from the region experienced well-developed democratic institutions
with appropriate checks and balances, the progress of the 1990s slightly reversed by both country
and population standards.
Next, presented at the bottom of Table 1 are the overall inclusive democracy scores for each
country and time period. These are predicted scores using a principle component factor analysis,
which showed a strong commonality between political and civil liberties and democratic institutions
with a large proportion of the variance being accounted for.8 These factor score estimates indicate
that South Asia did not make much progress in promoting inclusive democracy from both country
and population standpoints.9 The country averages show, instead, that the region on average
experienced a relatively better condition of inclusive democracy in the 1990s, which receded
afterwards. While Sri Lanka’s and especially India’s setback led to no net improvement in the
1990s, India is again the country that led the democratic institutionalization in the entire region. Sri
Lanka’s progress was impressive during 2000-2003, where as the progress during the 1990s was
impressive in Nepal, Pakistan, and especially Bangladesh. Pakistan’s progress of the 1990s,
however, was dramatically undone at the turn of the century.
Economic Inequality: Table 2 reports widely varying degrees of economic inequality in South
10
Asia both across countries and over time. First, Gini index based on the distribution of consumption
expenditures shows that while the estimates for most of the countries and time periods were
moderate, countries diverged in trend over time. Gini index was highly comparable in India, Nepal,
and Pakistan in the 1980s, with Bangladesh recording the lowest estimate and Sri Lanka the highest.
By 2000-2003, it slightly declined in Pakistan, moderately declined in Sri Lanka, and moderately
increased in Bangladesh and India. In Nepal, by contrast, Gini index drastically soared to the levels
of some highly unequal countries in the world.10 Gini index increased in South Asia between 1980s
and 1990s from both country and population standpoints.
(Insert Table 2 here)
Second, the consumption differentials for the top and bottom quintiles slightly increased in the
region between the 1980s and 1990s from the country and population standpoints with wide
variations across countries. Using both country and population averages, those at the top 20 percent
witnessed increased share of consumption relative to those at the bottom 20 percent by at least 33
percent. While the disparity slightly increased in India and Bangladesh during this period, it rapidly
escalated in Nepal11 and yet considerably decreased in Sri Lanka and especially Pakistan.
As with inclusive democracy, I used a principal component factor analysis to estimate the
commonality between the two inequality indicators and predict factor scores. This process,
however, was complicated due to missing values on both indicators, thus invoking some valid
strategy with a delicate attention to leave the observed trend unchanged. The factor analysis
conducted after imputing the relevant missing values12 indicated that the two indicators together
formed economic inequality with a large commonality.13 Results summarized in Table 2 indicate a
relatively wide variation in economic inequality in the region.14 The values for Nepal characterizing
the highest degree of inequality in South Asia are starkly different from those in Sri Lanka during
11
2000-2003. These estimates capture the commendable stride that Pakistan and especially Sri Lanka
made in reducing inequality during the period. Where as Sri Lanka and especially Pakistan started
with moderate degrees of inequality in the 1980s, they both progressively reduced inequality by the
end of the period. Bangladesh with a very low level of inequality to begin with managed to maintain
it throughout the period even though at a slightly higher level. India and especially Nepal manifest a
rampant increase in inequality.
V. Models and Results
Since disentangling the interrelationships between democracy and economic inequality is complex,
I use various techniques to efficiently handle this complexity. The use of fixed effects regressions is
justified given the balanced panel data in which it is important to control for the country specific
effects. The use of the three-stage least squares (3SLS) regression is also relevant given its ability to
account for any endogeneity and simultaneous causality bias. Because regression models sometimes
produce estimates due to random chance, I conduct sensitivity analysis by estimating alternative
specifications of the models with the aggregate scores on democracy and inequality as well as with
their indicators as the dependent variables.15
Panel Data Models: I estimate fixed effects regressions with the following specification:
y it = α + β x it + γwit + u i + ε it
Where, y is the dependent variable democracy or economic inequality; x is the independent variable
economic inequality or democracy; w is the vector of control variables; and u is the country specific
error. I estimate four alternative specifications of this model with the first two including democracy
scores as the dependent variable and other two including the indicators of democracy as the
dependent variables. I also estimate two sets of alternative specifications of the model, of which the
first includes inequality scores as the dependent variable and the next includes the indicators of
12
inequality as the dependent variables.
First, estimates from the fixed effects regressions of democracy included in Table 316 indicate that
the models with the aggregate economic inequality scores as the independent variable demonstrate
relatively small explanatory power compared with those with their indicators.17 Results from the
Democracy I model suggest that the effect of inequality is positive on inclusive democracy. While
this effect is not statistically highly significant due perhaps to the composite nature of the
independent variable, the more unequal countries in South Asia tend to develop more inclusive
democracy. Providing highly consistent sets of estimates, results from the Democracy II, Liberties,
and Institutions models with the indicators of inequality as the independent variables suggest that
the role of inequality in determining inclusive democracy bifurcates into the positive effect of Gini
index and the negative effect of the 80/20 consumption differential. The effects of Gini index on
inclusive democracy as well as political and civil liberties and democratic institutions are all
positive suggesting that more unequal countries tend to institute more inclusive democracy. The
negative association of the consumption ratio, however, suggests that larger consumption
differentials would be detrimental to inclusive democracy in aggregate as well as to the specific
indicators.
(Insert Table 3 here)
The coefficients on the control variables are partly consistent with my expectations. The GDP per
capita, for example, has a consistently positive relationship with democracy indicating that South
Asian countries with higher levels of economic development tend to be more democratic (Lipset
1959; Przeworski and Limongi 1997). Contrary to my expectation, the effect of poverty incidence is
also consistently positive. Although the moderate correlation of poverty incidence with GDP (–
0.70) rules out a severe multicollinearity problem, these coefficients indicate something related but
13
beyond the effect of GDP. Since GDP positively affects democracy, some of this effect tends to be
negated especially when a country has a high poverty incidence. The curvilinear nature of the
relationship that studies have shown elsewhere (e.g., Bollen and Jackman 1995; Muller 1995) also
appears to be operational in this region once the positive effect of poverty incidence is incorporated.
While the finding that democracy flourishes amidst high degrees of absolute poverty is hard to
accept, this does not support the argument that a high degree of absolute poverty induces people to
get organized and pressure for more political equality. Because poverty concentration correlates
(0.82) highly with illiteracy, the argument for articulating organized voices for more freedom as
well as for further development of democratic institutions is also not supported.
Second, estimates from the fixed effects regressions presented in Table 4 suggest that the effects
on the aggregate measure of inequality are not significant in case of both the aggregate measure of
democracy (Inequality I) and individual indicators (Inequality II). Results from the 80/20 and Gini
models, however, demonstrate that the indicators of democracy systematically affect the two
aspects of economic inequality captured by the respective indictors. Interestingly, findings are quite
different between using the aggregate measures of inequality and democracy and using their
indicators. But, consistent with the effects of inequality on democracy, the effect of democracy on
inequality also bifurcates, suggesting that while political and civil liberties are negatively related
with the inequality indicators, democratic institutions are positively related with them. There is an
indication that countries with more freedom have maintained lower levels of inequality, where as
those with more established democratic institutions tolerate more inequality. What may be different,
however, is the interaction of the democracy indicators in affecting the aggregate measure of
inequality resulting in an insignificant coefficient.
(Insert Table 4 here)
14
The effects of control variables on inequality partly support the hypotheses posed earlier. The
models indicate that electoral participation does not directly affect inequality in South Asia, where
as a higher GDP significantly reduces it. Electoral participation typically entails that people are
knowledgeable of, as well as interested in, their own governance or influencing policy outcomes, an
assumption that may not hold in this region with mass illiteracy. In the same vein, while the
negative coefficient on GDP partly contradicts the popular findings (Barro 2000; Reuveny and Li
2003), a little over two decades may not be adequate to realistically capture the time series
relationships. Also, South Asian countries with larger GDP estimates have been able to curb
economic inequality perhaps suggesting that it is not necessarily the economic growth that increases
inequality. What matters more, for example, may be the policy prescriptions on labor market and
income redistribution, which have not been fully captured in the analysis. This is further supported
by the positive coefficient on international trade, which is consistent with the hypothesis posed
earlier. It may be natural to expect that more open or liberalized economies tend to be more
unequal. This result, just like those from other more systematic investigations in South Asia (Wagle
2007a), does not support the oft-cited Stolper-Samuelson (1941) hypothesis that countries with
increasing foreign trade would witness declining economic inequality through migration of the
abundant unskilled and skilled workers. As expected, economic expansion triggered by the
liberalization policies of the 1980s and especially 1990s may have increased the demand for the
unskilled labor. But their real compensation may not have increased in South Asia, where the
unskilled labor is abundant, relative to the skilled labor that is in short supply. Yet, the fact that
GDP linearly decreases inequality where as foreign trade increases it may indicate that the effects of
economic development and openness greatly interact each other, making inequality a nonlinear
outcome.
15
3SLS Models: To correct for any endogeneity and simultaneity bias, I estimate the following
simultaneous system of equations:18
yit = β 0 + β 1 xit + β 2 wit + u it
xit = γ 0 + γ 1 y it + γ 2 wit + vit
Where, y is the inclusive democracy, x is the economic inequality, and w is the vector of control
variables. Note that just like in fixed effects regressions, there will be two separate specifications
with the first including the composite measures of inclusive democracy and economic inequality
and the second replacing them with the respective indicators. Unlike with panel data techniques,
however, I estimate models with the composite scores of democracy and inequality as the dependent
variables. Also, I estimate both unweighted and weighted versions of the model given the potential
effects of the population size.
(Insert Table 5 here)
Results reported in Table 5 suggest two noteworthy points. First, where as the Unweighted I
model provides significant coefficients on the composite scores as the independent variables, the
estimates from the Weighted I model are less significant. The country level analysis, therefore,
shows largely positive relationships between the two sets of composite scores signifying
bidirectional relationships. Different from the panel data technique, however, the nonlinear effect of
democracy is significant suggesting that its positive effect on inequality sustains in a bidirectional
environment, which tends to attenuate after a country attains certain level of democracy. The
relationships between the composite scores of democracy and inequality and relevant indicators are
partly consistent between both the 3SLS models and the panel data models. In case of the weighted
models, however, the coefficients on the aggregate measure of democracy and its indicators are not
significant. Partly, this predicates the relevance of the unweighted models in the 3SLS environment
together with the fixed effects regressions of inequality.
16
Second, the roles of control variables in determining democracy and inequality are mostly
consistent with those suggested earlier. Unlike in the panel data regressions, the coefficient on
electoral participation is significant only in the Unweighted I model. This mostly significant and
positive effect of electoral participation contradicts the median voter hypothesis suggesting that
wider participation does not always result in more redistributive policies. Given that elections are
not always held within a multiparty, competitive framework in South Asia, however, their meaning
as well as the meaning of participation are not consistent. The role of GDP too appears to be
insignificant in the Weighted I model. The massive population in India with low GDP, stable
electoral participation, high democracy scores, and yet already high and rising inequality may have
caused some vulnerability of the weighted models. The coefficients on country specific dummies
are also interesting and yet mostly unsurprising.
VI. Discussions
This analysis supports that inclusive democracy and economic inequality may have mutually
reinforcing relationships with each affecting the other in South Asia. It instructs to reject the
hypothesis that the aggregate relationship is negative and indicates that while it may be nonlinear
and perhaps marginal especially in terms of the effect of democracy on inequality, it is positive both
ways. These relationships are not fully consistent with the effects of their underlying indicators that
have opposite signs. But the aggregate net relationship appears to be positive, after accounting for
any relevant dynamics involved in collectively determining them.
Here, the story that the models with individual indicators help craft will be useful to understand
the mechanisms specific to this region. First, while the net effect of economic inequality on
inclusive democracy is positive, one can see interesting dynamics with regard to the effects of the
17
individual inequality indicators. The model estimates consistently show that a large Gini index
characterizing a relatively high degree of economic inequality increases the chance of having
inclusive democracy. At the same time, however, having large resource differences for those at the
top and bottom quintile can be detrimental to democratization.
While there are disagreements over the central role of different classes in democratization with
some focusing on the bourgeoisie, others on the middle class, and yet others on the working class,
all arguments point that democratization transforms the social stratification system (Bollen and
Jackman 1995). Research largely supports, however, that a powerful middle class is needed to effect
and sustain democracy, as it can effectively pressure for democratic outcomes affecting the masses
(Dahl 1971; Easterly 2005; Lipset 1959). In South Asia, too, the middle class with a large student
and working population has provided a strong impetus to bring about democratic changes. As many
countries have switched between democratic and authoritarian governments in this region, the main
sticking point has been a constant struggle between the land-owning, bureaucratic elites and the
working, middle class. The findings with the negative role of 80/20 consumption differential and
positive role of Gini index subtly substantiate this tension.
The negative role of the consumption differential, for example, captures the power of the elites to
maneuver the rulers so that the demand for the political rights and civil liberties can be suppressed
and their influence in policy decisions can be sustained (Benhabib and Przeworski 2006; Easterly
2005). The rulers also find collusion with the elites rewarding as it avoids institutional constraints to
their recruitment and functioning (Przeworski 2004). The mostly agrarian and illiterate setting
especially in rural villages in many countries with clientelistic relationships between government
and the public makes it highly likely that the real separation of economic and political powers is
only a myth.
18
No doubt, more democratic countries like India have been able to strengthen individual rights and
liberties and electoral participation as a result of more inclusionary policies. Despite this, however,
the underrepresentation of the lower classes in important political, policy, and bureaucratic
processes continues to persist in South Asia. Jeffrey (2000, 2002) shows, for example, that the elites
dominate the political and bureaucratic machinery in north India, systematically excluding and
marginalizing the lower classes. India as a whole also continues to witness a disproportionately
lower representation of the different minorities including the Christians, Muslims, and Dalits in
political leaderships and administrative services (Manchanda 2006). More important than the
quantity of representation is its quality, however, with any increase in representation of these groups
in less crucial places not having significant influence in the actual policy decisions. In Nepal, in
particular, the upper caste Hindus comprising slightly greater than 30 percent of the total population
occupy almost two thirds of the major public sector positions with indigenous groups, Muslims, and
Dalits disproportionately far behind (Lawoti 2005; Manchanda 2006). Similar observations hold for
the Tamils and Christians in Sri Lanka and, perhaps at a smaller scale, the Hindus and Christians in
Bangladesh and Pakistan not only in political and bureaucratic representation but, more importantly,
in maintaining various aspects of individual liberty.
The positive role of Gini index, on the other hand, manifests the power of the middle class to
organize and pressure for democratic outcomes. While Gini index does not readily measure the
power or the size of the middle class, it does so after accounting for the extreme degrees of
inequality manifested by the consumption differential.19 And when the middle class is large,
especially experiencing more intense inequality, it looks for ways to establish democracy thus
protecting political and civil liberties and institutionalizing governments. The middle class may be
economically disadvantaged thus contributing to larger Gini indexes but its use of pluralistic
19
mechanisms such as labor unions, farmers’ cooperatives, and women’s associations that are
operational in both democratic and authoritarian countries to various degrees increases the chance
of democratic outcomes (Dahl 1971, 1998; Lipset 1959, 1994).
Second, results consistently support that higher levels of individual freedom help make
governments accountable to the public, thus favoring equality in opportunity and outcomes. This
offers a rich understanding of the mechanism through which democracy affects inequality. The
findings suggest a constant juxtaposition of the positive effect of democratic institutions with the
negative effect of freedom, yielding a positive but sometimes insignificant net effect. Political and
civil liberties enable one to use not just the means such as elections or other political activities
including protests, rallies, and demonstrations to effect desired policy changes. They also provide
other means especially through the rule of law, freedom of expression, and freedom to practice civic
and cultural life that can help shape the public opinion and pressure the government for appropriate
policy measures. While the performance of South Asian countries on securing political and civil
liberties has not been highly variable—all ranging from two to 5.5 out of the highest possible score
of seven—its negative effect on inequality captures the strength of freedom that people are able to
enjoy. This supports the thesis that political equality tends to level the playing field and promote
equality in economic outcomes (Justman and Gradstein 1999; Rueschemeyer 2005). At the same
time, the negative effect of political and civil liberties on both measures of inequality is interesting.
The effect on Gini coefficient may predicate the role of redistribution benefiting the middle class,
the lower class, or both. While similar dynamics may hold, the effect on the 80/20 consumption
differential may also imply that the lower class has become worse off, a possibility with
redistribution from the upper class to the middle class.
The positive role of political institutions is also quite interesting because of its power to drive the
20
net effect of democracy on inequality. The democratic institutions variable captures the institutional
aspect of democracy including development of proper checks and balances, competitive recruitment
of the chief executive, and public support needed to lead the institutions. In South Asia where
economic growth is always a top priority, however, this notion of democratic institutionalization
may provide a license to pursue one’s growth agendas without much operational constraint. The
notion of social hierarchy and clientelism is embedded in the culture with caste, ethnicity, and other
hierarchies determining the social order and outcomes (Bista 1991; Jeffrey 2002; Przeworski 2004;
Przeworski et al 2000). In countries with no formal checks and balances, on the other hand, the
chief executive constantly feels a need to legitimize authority and actions from citizens and
international actors. While the ruler ascends to power using some political justifications, the
possibility of mass uprising and the legitimization problem may force the autocratic ruler to
introduce populist programs (Benhabib and Przeworski 2006; Gandhi and Przeworski 2006). It may
not veritably redistribute resources but it does help boost consumption among the poor thus
reducing inequality. Unlike with political and civil liberties, however, the consistently positive
effect of democratic institutions suggests that the upper class tends to benefit as a result of greater
democracy, a finding consistent with the ability of the upper class to influence the making and
implementation of policies.
VII. Conclusion
If empirical data are any guide, democracy in this region appears to fuel economic inequality, which
in turn may promote democracy. While the relationship may not be perfectly linear especially in
case of the effect of democracy on inequality and while it is not highly consistent across different
modeling environments, there is evidence for a bidirectional positive relationship. There are
21
interesting observations on how these relationships come about. The positive effect of Gini index
and the negative effect of the 80/20 consumption differential on democracy, for example, contradict
each other, as do the positive effect of democratic institutions and negative effect of political and
civil liberties. After controlling for the negative effect of the consumption differential suggesting
that the existence of super elites (together with ultra poor) drags the efforts to democratize, the
positive effect of Gini index indicates that the large, economically less-advantaged middle class
pressures for democratic institutions and political equality. Moreover, political institutions
embracing clientelistic culture and pursuing the overall economic growth policies undermine their
economic redistribution agenda, where as the political and civil liberties adhere to the rule of law,
free media, and vibrant civil society which can effectively pressure the state to equalize
opportunities and reduce extreme inequalities.
There may be several reasons for the seemingly unusual findings, which this study has uncovered
for South Asia, with two most important being contextual and methodological. Using extensive
comparative data, Gradstein et al (2001) found a strong intervening role of religion or culture when
it comes to determining the effect of democracy on inequality. For Muslim and Buddhist/Hindu
dominant societies, they note, “democracy has either hardly discernible, or even a positive, effect on
inequality” (Gradstein et al 2001). While the attempt to control for these religious differences was
not fruitful perhaps because of the small sample size, what is at play is clearly the culture that
values economic inequality perhaps even more than it values democracy. There may be social
processes and institutions in this region that constantly look after the disadvantaged or hold the rich
morally obligated to support the poor in ways without extensive state involvement.
It is not the policy context or democratic governance per se that produces the economic outcomes
affecting the fate of the masses in these countries. Where as the policy priorities and operational
22
modalities change in western democracies following changes in the government, this may tend to be
highly invariant in South Asia regardless of whether the ‘democratic framework’ is operational.
Bureaucracies in these countries tend to be relatively strong and resistant to political influence and
therefore political parties in power might not have as much a sway over the redistributive nature of
policies. Party politics, from this standpoint, may only obstruct the process by which governments
are expected to favor certain constituencies. Authoritarian governments may even get increasing
pressure to legitimize their regimes, thus giving continuity to their populist, redistributive policies
benefiting the lower classes.
From the methodological standpoint, comparative analyses like this invoke enormous data issues
especially on inequality measures. In this analysis, I use consumption rather than income or
expenditure data to maintain consistency across countries and over time. While the WIDER (2005)
does an excellent job at adding consistency and reliability to the data, inequality estimates were
unavailable for many years. Because these inequality estimates have to come from nationally
representative surveys, they are simply hard to come by. Despite a meticulous handling of the
missing values, the outcomes may not have reflected the actual country experiences. Also, the
degrees of inequality examined here using consumption estimates may have been smaller than what
they actually are as inequality in market incomes tends to run much higher.
More comprehensive and consistent data are needed to derive more conclusive findings. The
dynamic nature of the concepts of democracy and inequality in this region may necessitate
incorporation of the time as well as country specific effects in the analysis. Researchers need to pay
appropriate attention to the effects of globalization and other international political economy factors
as well as to the horizontal and spatial forms of inequality that have enormous implications for the
participation of different groups in the political processes and for the quality of democracy.
23
Endnotes
1
While the South Asian Association for Regional Cooperation (SAARC) includes seven official member-countries,
Bhutan and Maldives are not included in this analysis for lack data.
2
This also applies to others examining various dimensions of democracy (Benhabib and Przeworski 2006; Przeworski
et al 2000; Przeworski and Limongi 1997).
3
It is important to distinguish between vertical and horizontal inequality within a country. The horizontal or between-
group inequality is important for a discussion of democracy as it partly shapes various political processes, institutions,
and outcomes. The various forms of ethno-political conflicts and instability facing many countries in South Asia, for
example, may have to do with growing inter-group economic disparities along caste, ethnic, religious, and spatial lines
(Deshpande 2000; Manchanda 2006; Wagle 2007b). Despite this, however, this paper exclusively focuses on the
vertical or inter-individual inequality for consistent data on horizontal inequality are not available.
4
In his most recent treatise, for example, Dahl (1998) outlines basic ingredients of political democracy as effective
participation, voting equality, enlightened understanding, control of the agenda, and inclusion of adults in democratic
processes.
5
Included here are the institutional factors mainly used by political scientists. Alternative approaches increasingly used
by political economists underscore individual factors such as human development and other positive freedoms
(O’Donnell 2004; Sen 1999).
6
The 90/10 ratio is another variation of the percentile distribution with a more radical tone as one is likely to find larger
differences from this approach than from the 80/20 approach (Sutcliffe 2004).
7
See Appendix for a description of the variables used.
8
Factor analysis finds commonality among the variables supplied and empirically determines the weights useful in
predicting factor scores. Although this approach provides equivalent loading weights when two variables are used,
results indicated that the first common factor with an Eigenvalue of 1.6505 accounted for over 82 percent of the total
variation thus rendering the predicted scores highly accurate.
24
9
There is a caveat in terms of making absolute comparisons with these estimates, however. Because these factor scores
have a range of 0-1, the variations between countries and over years may have been slightly magnified. As a result, the
values are only relative to the estimates in this distribution and cannot be compared with any other estimates. The value
of one, for example, indicates its highest ranking in the distribution, not a perfect case for inclusive democracy, where
as the value of zero indicates the lowest in the distribution, not a case with absolutely no democracy.
10
Its Gini index of 0.47 compares well to those of the most unequal countries including Argentina (0.528), Mexico
(0.495), the Philippines (0.46), and South Africa (0.578) (World Bank 2006).
11
Looking at the distribution of income, Guha-Khasnobis and Bari (2003) found similar patterns in South Asia with
Nepal manifesting the highest ratio of income for the top to bottom deciles followed by Pakistan.
12
Because these inequality data come from nationally representative surveys, estimates are available only for some
years. To derive reliable estimates for the years in a given country, I linearly interpolated the data thus leaving the
overall trend intact. In many cases, however, estimates were not available for a few years in or after 1980 and /or in or
prior to 2003. Specifically, Bangladesh lacked estimates prior to 1983 and after 2000, India after 2000, Nepal prior to
1984, Pakistan prior to 1984 and after 2002, and Sri Lanka prior to 1986 and after 2000. In these cases, I extrapolated
the data by extending the actual value of the closest estimate to the beginning or to the end. While this does not capture
the true state of inequality for the given year, it systematically inputs values that are highly probable. Because values in
the time series data can change from one year to next only by marginal percentage points, this process still leads to
outcomes that are justifiably realistic.
13
The process was akin to the case of inclusive democracy discussed earlier. In this case, however, the proportion of the
commonality accounted for was 96 percent with an eigenvalue of 1.918 indicating even greater confidence on the
accuracy of the predicted scores.
14
Such variations, however, may have been greatly magnified precisely because of the relative comparison among the
cases involved. See footnote 9 for details.
15
This is to examine the potential multicollinearity problems likely in these types of aggregate data. The use of
multiple, correlated democracy or inequality indicators in the same model, for example, increases the chance of
multicollinearity, which can be corrected, among other things, by using their aggregate estimates.
25
16
I estimated random effects counterparts of the models presented in Tables 3 and 4 to see whether they produce
equally consistent estimates. Coefficient estimates were mostly similar and the associated Hausman test results
indicated that in most cases the differences in coefficients were systematic between the fixed and random effects
regressions (results available from the author).
17
The use of specific indicators increases the explanatory power of the model, because of the aggregate nature of
democracy as well as the inclusion of more independent variables.
18
Although the equations include panel data notations, the model itself does not represent a panel data technique. But
the inclusion of country specific dummy variables makes the model equivalent to a fixed effects regression.
19
Consumption differential, which captures the disparities between the rich and the poor, is an integral part of Gini
index. Once the model controls for the effect of consumption differential, the value added of using Gini index becomes
the degree of inequality experienced by the middle class. Here, middle class is defined as the group whose consumption
is close to the mean. Since the typical distribution of income or consumption has positive skewness with long upper tail,
a higher degree of consumption differential would render a smaller middle class, as the mean would center somewhere
in the upper half of the distribution, away from the median. Since those on the top manifest high consumption, this
would also be consistent with the more intense inequality experienced by the middle class.
References
Alderson, A.S. and Nielsen, F. (2002). Globalization and the Great U-Turn: Income Inequality
Trends in 16 OECD Countries. American Journal of Sociology, 107(5), 1244-99.
APSA Task Force on Inequality and American Democracy. (2004). American Democracy in an Age
of Rising Inequality. Perspectives on Politics, 2(4), 651-66.
Barro, R.J. (2000). Inequality and Growth in a Panel of Countries. Journal of Economic Growth, 5,
5-32.
Bartels, L.M. (2006). Is the Water Rising? Reflections on Inequality and American Democracy. PS,
Political Science & Politics, 39(1), 39-42.
Beetham, D. (2005). Freedom and the Foundation. In L. Diamond and L. Morlino (Eds.), Assessing
the Quality of Democracy, pp. 32-46. Baltimore, MD: Johns Hopkins University Press.
26
Benhabib, J. and Przeworski, A. (2006). The Political Economy of Redistribution Under
Democracy. Economic Theory, 29, 271-90.
Bista, D.B. (1991). Fatalism and Development: Nepal’s Struggle for Modernization. Calcutta,
India: Orient Longman.
Bollen, K.A. (1990). Political Democracy: Conceptual and Measurement Traps. Studies in
Comparative International Development, 25(1), 7-24.
Bollen, K.A. and Grandjean, B. (1981). Dimension(s) of Democracy: Further Issues in the
Measurement and effects of Political Democracy. American Sociological Review, 46, 651-59.
Bollen, K.A. and Jackman, R.W. (1995). Income Inequality and Democratization Revisited:
Comment on Muller. American Sociological Review, 60, 983-89.
Bollen, K.A. and Paxton, P.M. (2000). Subjective Measures of Liberal Democracy. Comparative
Political Studies, 33(1), 58-86.
Chong, A. and Gradstein, M. (2004). Inequality and Institutions. CEPR Discussion Paper No. 4739.
Dahl, R.A. (1998). On Democracy. New Haven, CT: Yale University Press.
Dahl. R.A. (1971). Polyarchy: Participation and Opposition. New Haven, CT: Yale University
Press.
Deshpande, A. (2000). Recasting Economic Inequality. Review of Social Economy, LVIII(3), 38199.
Doorenspleet, R. (2002). Development, Class, and Democracy: Is there a Relationship? In O.
Elgstrom and G. Hayden (Eds.), Development and Democracy: What Have We Learned and
How?, pp. 48-64. New York, NY: Routledge.
Easterly, W. (2005). Inequality Does Cause Underdevelopment. New York University, New York
(Mimeo).
Ember, M., Ember, C.R., and Russett, B. (1997). Inequality and Democracy in the Anthropological
Record. In M.I. Midlarsky (Ed.), Inequality, Democracy, and Economic Development, pp. 110-30.
New York, NY: Cambridge University Press.
Firebaugh, G. (2003). The New Geography of Global Income Inequality. Cambridge, MA: Harvard
University Press.
Freedom House. (2005a). Freedom in the World Country Rankings: 1972-2004. Washington, DC:
Freedom House.
Freedom House. (2005b). Freedom in the World: Methodology. Washington, DC: Freedom House.
27
Galbraith, J.K. (1998). Created Unequal: The Crisis in American Pay. New York, NY: Free Press.
Gandhi, J. and Przeworski, A. (2006). Cooperation, Cooptation, and Rebellion Under Dictatorships.
Economics and Politics, 18(1), 1-26.
Gradstein, M., Milanovic, B., and Ying, Y. (2001). Democracy and Income Inequality: An
Empirical Analysis. World Bank DRG Policy Research Working Paper 2561.
Guha-Khasnobis, B. and Bari, F. (2003). Sources of Growth in South Asian Countries. In I.
Ahluwalia and J. Williamson (Eds.), The South Asian Experience with Growth, pp. 13-79. New
York: Oxford University Press.
IIDEA. (2006). Online Voter Turnout Database. International Institute for Democracy and Electoral
Assistance, Stockholm, Sweden.
Jacobs, L.R. and Skocpol, T. (2006). Restoring the Tradition of Rigor and Relevance to Political
Science. PS, Political Science & Politics, 39(1), 27-31.
Jeffrey, C. (2000). Democratization without Representation? The Power and Political Strategies of a
Rural Elite in North India. Political Geography, 19, 1013-36.
Jeffrey, C. (2002). Caste, class, and Clientelism: A Political Economy of Everyday Corruption in
Rural North India. Economic Geography, 78(1), 21-41.
Justman, M. and Gradstein, M. (1999). The Industrial Revolution, Political Transition, and the
Subsequent Decline in Inequality in 19th–Century Britain. Explorations in Economic History, 36,
109-27.
Karl, T.L. (2000). Economic Inequality and Democratic Instability. Journal of Democracy, 11(1),
149-156.
Lawoti, M. (2005). Towards A Democratic Nepal: Inclusive Political Institutions for a
Multicultural Society. New Delhi: Sage.
Lijphart, A. (1977). Democracy in Plural Societies. A Comparative Exploration. New Haven, CT:
Yale University Press.
Lipset, S.M. (1959). Some Social Requisites of Democracy: Economic Development and Political
Development. American Political Science Review, 53, 69-105.
Lipset, S.M. (1994). The Social Requisites of Democracy Revisited. American Sociological Review,
59, 1-22.
Mahler, V.A. (2004). Economic Globalization, Domestic Politics, and Income Inequality in the
Developed Countries: A Cross-National Study. Comparative Political Studies, 37(9), 1025-53.
28
Manchanda, R. (Ed.). (2006). The No-Nonsense Guide to Minority Rights in South Asia.
Kathmandu, Nepal: South Asian Forum for Human Rights.
Marshall, M.G. and Jaggers, K. (2005). Polity IV Project: Political Regime Characteristics and
Transitions: 1800-2002. Polity IV Project (INCSR).
Midlarsky, M.I. (1997). Conclusion: Paradoxes of Democracy. In M.I. Midlarsky (Ed.), Inequality,
Democracy, and Economic Development, pp. 319-26. New York, NY: Cambridge University
Press.
Milanovic, B. (2005). Worlds Apart: Measuring International and Global Inequality. Princeton, NJ:
Princeton University Press.
Muller, E.N. (1988). Democracy, Economic Development, and Income Inequality. American
Sociological Review, 53, 50-68.
Muller, E.N. (1995). Economic Determinants of Democracy. American Sociological Review, 60,
966-82.
O’Donnell, G. (2004). Human Development, Human Rights, and Democracy. In G. O’Donnell, J.V.
Cullell, and O.M Iazzetta (Eds.), The Quality of Democracy: Theory and Applications, pp. 9-92.
Notre Dame, IN: University of Notre Dame Press.
O’Donnell, G. (2005). Why the Rule of Law Matters. In L. Diamond and L. Morlino (Eds.),
Assessing the Quality of Democracy, pp. 3-17. Baltimore, MD: Johns Hopkins University Press.
Piven, F.F. (2006). Response to “American Democracy in an Age of Inequality.” PS, Political
Science & Politics, 39(1), 43-46.
Polity IV Project. (2005). Polity IV Annual Time Series Dataset. INCSR, University of Maryland,
College Park, MD.
Przeworski, A. (2004). Institutions Matter? Government and Opposition, 39(4), 527-40.
Przeworski, A. (2005). Democracy as an Equilibrium. Public Choice, 123, 253-73.
Przeworski, A. and Limongi, F. (1997). Modernization: Theories and Facts. World Politics, 49(2),
155-83.
Przeworski, A., Alvarez, M.E., Cheibub, J.A., and Limongi, F. (2000). Democracy and
Development. New York, NY: Cambridge University Press.
Reuveny, R. and Li, Q. (2003). Economic Openness, Democracy, and Income Inequality: An
Empirical Analysis. Comparative Political Studies, 36(5), 575-601.
Rodrik, D. (1998). Symposium on Globalization in Perspective: And Introduction. Journal of
29
Economic Perspectives, 12(4), 3-8.
Rueschemeyer, D. (2005). Addressing Inequality. In L. Diamond and L. Morlino (Eds.), Assessing
the Quality of Democracy, pp. 47-61. Baltimore, MD: Johns Hopkins University Press.
Rustow, D.A. (1970). Transitions to Democracy: Toward a Dynamic Model. Comparative Politics,
2, 337-63.
Scholzman, K.L. (2006). On Inequality and Political Voice: Response to Stephen Earl Bennett’s
Critique. PS, Political Science & Politics, 39(1), 55-57.
Sen, A.K. (1999). Development as Freedom. New York, NY: Alfred A. Knoff.
Simpson, M. (1990). Political Rights and Income Inequality: A Cross-National Test. American
Sociological Review, 55, 682-693.
Stolper, W.F. and Samuelson, P.A. (1941). Protection and Real Wages. Review of Economic Studies, 9, 5873.
Sutcliffe, B. (2004). World Inequality and Globalization. Oxford Review of Economic Policy, 20(1),
15-37.
Tilly, C. (2003). Inequality, Democratization, and De-Democratization. Sociological Theory, 21(1),
37-43.
UNDP. (2002). Human Development Report 2002. New York, NY: Oxford University Press.
Wagle, U. (2007a). Are Economic Liberalization and Equality Compatible? Evidence from South Asia.
World Development, 35(11), 1836-57.
Wagle, U. (2007b). Economic Inequality in the ‘Democratic’ Nepal: Scale, Sources, and
Implications. Himalayan Policy Research Conference, October, Madison, WI.
WIDER. (2005). World Income Inequality Database (V 2.0a). World Institute for Development
Economics Research (United Nations University).
World Bank. (2005a). World Development Report 2005. Washington, DC: The World Bank.
World Bank. (2005b). World Development Indicators 1960-2005 (CD-ROM). Washington, DC:
The World Bank.
World Bank. (2006). World Development Report 2006. Washington, DC: The World Bank.
Zafirovski, M. (2002). Income Inequality and Social Institutions: Beyond the Kuznets Curve and
Economic Determinism. International Journal of Sociology and Social Policy, 22(11/12), 89-131.
30
Appendix. Description of Variables
Variables
Economic Inequality
Gini Index
Definition
Composite scores predicted from Gini Index and 80/20 Consumption, using weights empirically
determined by factor analysis.
ab
Gini coefficient of the distribution of per capita consumpotion expenditures. Possible values are between
0.25
zerotoand
0.47one with, zero indicating perfect equality an
ab
80/20 Consumption
Inclusive Democracy
c
Political and Civil Liberties
d
Democratic Institutions
Ratio of the share of consumption expenditures of the top to bottom quintile.
Composite scores predicted from Political and Civil Liberties and Democratic Institutions, using the
weights empirically determined by factor analysis.
Simple average of the scores of political rights and civil liberites, each ranging from one to zeven.
While the original data were in descending order, the reconstructed scales have positive order with
one signifying the lowest score and seven signifying the highest or ideal score.
Scores on democratic institutions ranging from zero to 10 with zero indicating the absolute
dictatorship and 10 indicating the ideal form of democracy.
e
Electoral Participation
ab
Poverty Incidence
b
Real GDP Per Capita
2.00 to 5.50
Voter turnout as indicated by the percentage of the voting age population who actually voted.
31.5 to 83.7
Percentage of the population that was poor using the international poverty line of $1/day purchasing
power parity
3.82 to 49.63
146 to 921
Trade including import and export as a percentage of GDP.
b
12.50 to 88.64
Total population.
a
3.69 to 9.10
0 to 1
0 to 9
Gross domestic product per capita in 2000 US$.
b
International Trade
Population
Value range
0 to 1
b
14.6 to 1064.4
c
d
e
Sources: WIDER (2005); World Bank (2006); Freedom House (2005a); Polity IV Project (2005); IIDEA (2006)
Tables
Table 1. Measures of Democracy
Period
Political and Civil Liberties
1980s
1990s
2000-2003
Democratic Institutions
1980s
1990s
2000-2003
Inclusive Democracy
1980s
1990s
2000-2003
Bangladesh
Pakistan
Sri Lanka
Country
a
Average
Population
b
Average
India
Nepal
3.35
4.80
4.25
5.50
4.75
5.50
4.30
4.65
4.13
3.35
3.55
2.50
4.40
3.85
4.63
4.18
4.32
4.20
5.06
4.63
5.02
0.00
5.40
6.00
8.00
8.50
9.00
1.80
5.20
4.00
1.60
7.00
0.00
6.00
6.00
6.75
3.48
6.42
5.15
6.49
7.96
7.64
0.217
0.713
0.653
0.951
0.855
1.000
0.457
0.687
0.536
0.295
0.589
0.080
0.677
0.589
0.750
0.520
0.685
0.604
0.807
0.809
0.857
Note: a Simple (unweighted) average across five countries
b
Average weighted by the pouplation in different countries
31
Table 2. Measures of Inequality
Period
Bangladesh
Gini Index (Coefficient)
1980s
1990s
2000-2003
80/20 Consumption Ratio
1980s
1990s
2000-2003
Economic Inequality
1980s
1990s
2000-2003
India
Nepal
Pakistan
Sri Lanka
Country
Averagea
Population
Averageb
0.268
0.321
0.319
0.312
0.311
0.360
0.300
0.426
0.472
0.326
0.320
0.306
0.341
0.332
0.276
0.305
0.327
0.347
0.309
0.325
0.351
3.78
4.83
4.60
4.60
4.45
5.78
4.34
7.63
9.10
6.33
5.58
4.33
5.35
5.07
4.05
4.73
5.26
5.57
4.62
4.70
5.55
0.024
0.238
0.228
0.222
0.292
0.433
0.233
0.673
0.948
0.443
0.302
0.176
0.336
0.271
0.073
0.251
0.355
0.372
0.225
0.297
0.389
Note: a Simple (unweighted) average across five countries
b
Average weighted by the pouplation in different countries
Table 3. Fixed Effects Regressions of Democracy
(N=120)
Variables
Economic inequality
Democracy
I
0.226
Democracy
II
Liberties
Institutions
*
(0.108)
Gini
80/20 consumption
10.126 **
28.848 **
112.978 **
(1.413)
(5.303)
(16.269)
-0.321 **
(0.050)
Poverty incidence
0.008 **
(0.003)
Real GDP PC
0.001 **
(0.000)
Constant
-0.041
0.018 **
(0.003)
0.001 **
(0.000)
-1.861 **
-1.002 **
(0.189)
(0.580)
0.065 **
(0.011)
0.002
0.147 **
(0.032)
*
(0.001)
-2.636
-3.292 **
0.009 **
(0.002)
*
-22.979 **
(0.156)
(0.290)
(1.090)
(3.342)
R
0.057
Note: 1) Values in parentheses are standard errors
2) * p<0.05, ** p<0.01
0.408
0.310
0.443
2
32
Table 4. Fixed Effects Regressions of Inequality
(N=120)
Variables
Inequality
I
Inclusive democracy squared
Inequality
II
80/20
Gini
0.109
(0.162)
Political and civil liberties
-0.088
(0.119)
0.026
0.076
(0.017)
(0.037)
(0.001)
0.001
0.006
0.051
0.001
(0.006)
(0.006)
(0.015)
(0.001)
Electoral participation
-0.001
*
(0.000)
Trade
Constant
R
-0.009
(0.077)
Democratic Institutions
Real GDP PC
-0.361 **
0.020 **
-0.001
0.015
(0.004)
*
-0.006 **
(0.000)
(0.001)
*
0.081 **
(0.012)
0.004 **
<-0.001 **
(0.000)
0.003 **
(0.005)
(.006)
-0.037
0.079
(0.266)
(0.287)
(0.741)
(0.026)
0.347
0.384
0.191
0.274
2
*
2.598 **
(0.000)
0.258 **
Note: 1) Values in parentheses are standard errors
2) * p<0.05, ** p<0.01
33
Table 5. Three Stage Least Square Regressions of Democracy and Inequality
(N=120)
Unweighted I
Variables
Economic inequality
Democracy
Inequality
0.476 **
Weighted I
Democracy
0.428
(0.150)
Inequality
Unweighted II
Democracy
Weighted II
Inequality
Democracy Inequality
*
(0.212)
Inclusive democracy squared
0.185 **
0.031
(0.060)
(0.039)
Gini
10.111 **
8.613 **
(1.358)
80/20 consumption
(1.755)
-0.315 **
-0.250 **
(0.048)
(0.059)
Political and civil liberties
-0.050 **
-0.018
(0.019)
Democratic Institutions
(0.012)
0.018 **
0.002
(0.006)
Electoral participation
0.002
0.010 **
(0.002)
Poverty incidence
0.007
*
0.009 **
(0.003)
Real GDP PC
0.001 **
(0.000)
Trade
(0.000)
0.001
(0.000)
0.016 **
<-0.001 **
(0.000)
0.012 **
(0.004)
0.017 **
(0.003)
(0.003)
0.001 **
(0.000)
-0.001 **
(0.000)
0.016 **
(0.002)
*
(0.002)
0.017 **
(0.004)
-0.001 **
0.006
(0.002)
(0.004)
0.001 * <-0.001 **
(0.000)
0.015 **
(0.002)
(0.000)
0.015 **
(0.002)
(0.002)
Countries (Ref. = Bangladesh):
India
0.242 **
(0.071)
Nepal
Pakistan
0.190 **
(0.028)
0.087
-0.031
-0.125
-0.088
-0.125
(0.063)
(0.152)
(0.067)
(0.062)
-0.375 **
-0.015
0.218 **
(0.086)
-0.378 **
(0.086)
-0.334 **
(0.077)
0.100
(0.135)
0.280 **
(0.056)
-0.648 **
(0.071)
-0.149
(0.046)
*
*
(0.069)
0.234 **
(0.088)
-1.887 **
0.098
(0.061)
0.203 **
(0.031)
-0.074
-0.151
-0.106
(0.060)
(0.126)
(0.067)
0.259 **
(0.072)
-0.370 **
(0.084)
-0.110
-0.174 *
(0.080)
0.252 *
(0.127)
-1.666 **
0.319 **
(0.053)
-0.650 **
(0.072)
-0.013
-0.148
0.005
(0.137)
(0.122)
(0.183)
(0.114)
(0.272)
(0.122)
(0.338)
(0.096)
0.494
0.649
0.662
R
Note: 1) Values in parentheses are standard errors
2) * p<0.05, ** p<0.01
3) For weighted models: Weighting variable = Total populaiton
0.770
0.662
0.694
0.720
0.780
2
-0.718 **
0.202 **
(0.062)
-0.086
(0.102)
Constant
0.213 **
(0.062)
(0.084)
(0.079)
Sri Lanka
0.159 **
(0.049)
-0.759 **
34