Ethnic diversity and economic development

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Abstract

This paper analyzes the role that different indices and dimensions of ethnicity play in the process of economic development. Firstly, we discuss the advantages and disadvantages of alternative data sources for the construction of indices of religious and ethnic heterogeneity. Secondly, we compare the index of fractionalization and the index of polarization. We argue that an index of the family of discrete polarization measures is the adequate indicator to measure potential conflict. We find that ethnic (religious) polarization has a large and negative effect on economic development through the reduction of investment and the increase of government consumption and the probability of a civil conflict.

Introduction

In recent years, there has been increasing interest in the economic consequences of ethnic heterogeneity. In many situations, ethnic polarization generates conflicts that could eventually lead to political instability and civil wars (CW), with long-lasting economic effects. In other cases, the potential conflict represented by an ethnically polarized society can affect negatively the rate of investment and induce rent-seeking behavior that increases public consumption. These situations—armed conflicts, reduced investment, or higher government consumption—have been shown to have a negative effect on economic development (Barro, 1991, Tavares and Wacziarg, 2001).

This paper analyzes the effects of ethnic heterogeneity on economic development. For this purpose, we compare the empirical performance of different dimensions of ethnicity as well as alternative indices to measure diversity and potential conflict. There is a growing body of literature on the relationship between ethnic diversity, the quality of institutions, and economic growth. Mauro (1995) shows that a high level of ethnolinguistic diversity implies a lower level of investment. Easterly and Levine (1997) show that ethnic diversity has a direct negative effect on economic growth. La Porta et al. (1999) suggest that ethnic diversity is one of the factors explaining the quality of government. Bluedorn (2001), based on the study of Easterly and Levine (1997), presents empirical evidence of democracy's positive role in ameliorating the negative growth effects of ethnic diversity. All these studies use the index of ethnolinguistic fractionalization (ELF), also called ELF, calculated using the data of the Atlas Narodov Mira (Taylor and Hudson, 1972).

More recently, the economic research agenda on ethnic diversity has studied the relationship between religious diversity, democracy, and economic development. Barro, 1997a, Barro, 1997b includes the proportion of population affiliated to each religious group as explanatory variables for the level of democracy. Tavares and Wacziarg (2001) use the index of ethnolinguistic fractionalization and religious dummies to examine the indirect channels for the effect of democracy on growth. With a few exceptions, they find that the religious dummies have no effect on the basic channels. Collier and Hoeffler (2002) find that religious fractionalization has no effect on the risk of conflict. Alesina et al. (2003) argue that while ethnic and linguistic fractionalization have a negative effect on the quality of government, religious fractionalization has no effect. They also find that religious diversity has no effect on growth, using the basic regression of Easterly and Levine (1997). Therefore, the general result is that religious diversity, measured as a fractionalization index, has no effect on economic growth or quality of government.

However, both ethnolinguistic and religious diversity can potentially have a strong conflict dimension. For this reason, we propose a new measure of potential conflict in heterogeneous societies based on an index of polarization instead of the traditional fractionalization index. Several authors have argued theoretically in terms of “polarization” but used as an empirical proxy the index of fractionalization. We argue that polarization and fractionalization are two different, and on occasion, conflicting concepts. We also show how to derive our polarization index as the representation of the total resources devoted to lobbying in a simple rent-seeking model.

Given the importance of the conflict dimension of ethnic and religious diversity, we explore empirically the indirect effects of ethnolinguistic and religious polarization on growth through their impact on civil wars, investment, and government consumption. Civil wars are tragic events for economic development having a long-run impact on income per capita. Consistent with previous research, we find that religious fractionalization has no direct effect on economic growth, while ethnolinguistic fractionalization does. However, we find no strong empirical evidence to argue that the negative effect of fractionalization on growth is due to its impact on the indirect channels above mentioned. By contrast, we do find an important effect of polarization in the explanation of economic development, through its impact on civil wars, the rate of investment, and the proportion of government consumption over GDP. In fact, the indirect effect of polarization on economic growth is as large as the direct effect of fractionalization.

The paper is organized as follows. Section 2 describes the sources for the data on ethnolinguistic and religious diversity. Section 3 introduces the indices of fractionalization and polarization and compares their basic properties. Section 3 also shows how to derive the discrete polarization index from a simple rent-seeking model. Section 4 reports the empirical results obtained by using the alternative indices and dimensions of ethnicity. Section 5 concludes.

Section snippets

The measurement of religious and ethnic diversity

In this section, we present the criteria for the selection of the basic data on religious and ethnic diversity for a large sample of countries. We describe the alternative sources available as well as their differences and relative strengths and weaknesses. We should initially notice that the measurement of ethnic diversity is a very difficult task. Characteristics like “race” or “color” are, to some extent, socially constructed. For instance, Williamson (1984)1

Measuring ethnic diversity: polarization versus fractionalization

We have identified different dimensions or concepts of ethnicity and sources of data. Once a researcher has decided what dimension, or dimensions, of ethnicity to analyze, the next step is to decide what kind of indicator to use. One way to summarize the information is to construct a dummy that captures the largest ethnic group in each country, or the percentage of the largest ethnic group or the percentage of the largest ethnic minority in the country. However, if we are interested in

The empirics of ethnic diversity, conflict and growth

In this section, we discuss the empirical performance of indices of ethnic fractionalization and polarization. Most of the empirical applications have used the index of fractionalization as a measure of ethnic and religious diversity. In particular, the use of ELF is widespread in recent empirical studies on the relationship between ethnic diversity and growth. Mauro (1995) finds a negative and significant correlation between ELF and institutional efficiency and, in particular, corruption.

Conclusions

This paper presents a measurement of religious and ethnic diversity and their effects on economic development. The first part of the paper discusses the construction of a database of religious and ethnic diversity for a large sample of countries. We consider the impact of different data sources and indicators on the measurement of heterogeneity. We also analyze the effect of alternative synthetic indices for religious and ethnic diversity. We argue that the index of polarization is better

Acknowledgement

We would like to thank Tim Besley, Robin Burgess, Debraj Ray, Joan Esteban and, specially, two anonymous referees for many valuable comments. Jose G. Montalvo thanks the hospitality of the Public Services Group of the Research Department (DECRG) of the World Bank where most of the revision of this paper was done. Financial support by the Spanish Ministerio de Ciencia y Tecnologia (projects SEC2001-0792 and SEC2003-04429) is kindly acknowledged. We would like to thank also seminar participants

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