اقتصاد سیاسی شکاف های زبانشناختی

This paper uses a linguistic tree, describing the genealogical relationship between all 6912 world languages, to compute measures of diversity at different levels of linguistic aggregation. By doing so, we let the data inform us on which linguistic cleavages are most relevant for a range of political economy outcomes, rather than making ad hoc choices. We find that deep cleavages, originating thousands of years ago, lead to better predictors of civil conflict and redistribution. The opposite pattern emerges when it comes to the impact of linguistic diversity on growth and public goods provision, where finer distinctions between languages matter.

How does ethnolinguistic diversity affect political and economic outcomes? In recent years, a vast literature has argued that such cultural heterogeneity impacts a wide range of outcomes, fostering civil war, undermining growth, hindering redistribution and the provision of public goods. However, evidence on this point remains subject to some disagreement. For instance, there is a vibrant debate on the role of ethnolinguistic divisions as determinants of civil wars.1 Econometric results on growth, redistribution and public goods provision also vary widely across studies, raising issues of robustness.2 These inconclusive results may stem in part from the inability to convincingly define the ethnolinguistic groups used as primitives to construct measures of heterogeneity. When faced with the issue of how to define groups, researchers have either relied on readily available classifications, such as the ones based on the Atlas Narodov Mira or the Encyclopedia Britannica, or have carefully constructed their own classifications. 3 Both approaches are problematic: the former runs the risk of missing the relevant cleavages, whereas the latter is subject to the criticism that groups are defined based on how important they are expected to be for the problem at hand. In this paper, we propose a methodology that addresses both criticisms, and argue that the degree of coarseness of ethnolinguistic classifications has profound implications for inference on the role of diversity. The methodology we propose computes diversity measures at different levels of aggregation. We do so by exploiting the information of language trees. We refer to this as a phylogenetic approach, since tree diagrams describe the family structure of world languages. Depending on how finely or coarsely groups are defined, the measure of linguistic diversity will be different. For example, if one takes the different dialects of Italian to constitute different groups, then Italy appears to be very diverse. However, if one considers these different dialects to be only minor variations of Italian, then Italy looks homogeneous. Apart from allowing us to classify languages at different levels of aggregation, this approach has the advantage of giving a historical dimension to our analysis. Coarse linguistic divisions, obtained at high levels of aggregation, describe cleavages that go back thousands of years. In contrast, finer divisions, obtained at low levels of aggregation, are the result of more recent cleavages. Since we rely on data that cover the entire set of 6912 world languages, and examine effects of heterogeneity measures computed at all possible levels of aggregation, we are able to capture a wide range of linguistic classifications. Rather than choosing the “correct” classification ourselves, we let the data inform us as to which linguistic cleavages are most relevant for different outcomes of interest.4 Our empirical analysis reveals drastically different effects of linguistic diversity at different levels of aggregation. We also find that the relevant cleavages vary greatly across political economy outcomes. Starting from the data, specifications and estimation methods from major contributions to the literature on the political economy of ethnolinguistic diversity, we substitute our new measures of diversity for those commonly used. For civil conflict and the extent of redistribution, issues that inherently involve conflicts of interest, coarse divisions seem to matter most. While we find only weak evidence that diversity (whether measured by fractionalization or polarization) affects the onset of civil wars at any level of linguistic aggregation, the estimated effects do tend to be larger and more significant when considering a coarse classification. This finding is consistent with existing conflicts in African countries, such as Chad and Sudan, on the border between the Afro-Asiatic family and the Nilo-Saharan family. It may also help explain conflict in certain Latin American countries, such as Mexico and Bolivia, where the Indo-European family coexists with different Amerindian languages. For redistribution, the results are more robust, and suggest once again that measures based on a high level of aggregation matter most. In contrast, for economic growth, where coordination between individuals or groups is essential and market integration is important, we find that finer divisions lead to heterogeneity measures that matter more. The same pattern holds across a wide array of measures of public goods provision. Thus, when the main issue involves conflicts of interest (as for the onset of civil wars and the extent of redistribution), deep differences originating thousands of years ago matter most: different groups' interests differ more when cleavages are more deeply rooted. In contrast, more superficial and recent divisions are negatively related to growth, an outcome related to the ease of coordination. For instance, to the extent that clusters of economic activity form around language lines, linguistic divisions may limit the integration of markets, and prevent economic growth. Even though Hindi and Gujarati are not so different, this linguistic cleavage may hinder the integration of the corresponding regions of India. What matters here is whether two individuals or groups can interact effectively. In fact, finer linguistic classifications deliver heterogeneity measures that matter more for outcomes such as economic growth, which is hindered by lack of coordination and integration. As for public goods, they fall somewhere in between both cases: although they have a redistributive aspect, their effective provision also requires coordination between groups or individuals. Empirically, we find that fine linguistic divisions, based on more superficial cleavages, are correlated with lower public goods provision across a wide array of indicators. This paper is related to a vast literature in political economy. Various authors have studied how ethnolinguistic diversity affects redistribution, growth and civil conflict (Alesina and La Ferrara, 2005, Alesina et al., 1999, Alesina et al., 2003, Easterly and Levine, 1997, Fearon and Laitin, 2003 and La Porta et al., 1999, among many others). Measurement issues are central to recent research on these topics. One issue is that standard indices of diversity do not take into account the distance between groups (Desmet et al., 2009, Fearon, 2003 and Spolaore and Wacziarg, 2009). Another possibility is that for certain issues, such as civil conflict, polarization may be more relevant than fractionalization (Esteban and Ray, 1994 and Montalvo and Reynal-Querol, 2005), an issue we revisit below. A third problem is the difficulty of determining the right level of aggregation when computing heterogeneity measures, i.e., identifying the relevant ethnolinguistic cleavages. This issue has received little attention, and it is the main focus of the present study.5 This paper is organized as follows. Section 2 describes conceptual issues related to the measurement of heterogeneity based on language trees, and describes the data. Section 3 discusses the effects of diversity on civil conflict and redistribution. Section 4 covers the effects on public goods provision and economic growth. Section 5 explores a number of robustness issues, and Section 6 concludes.

In this paper, we have uncovered new evidence on the relationship between ethnolinguistic diversity and a range of political economy outcomes, such as the onset of civil wars, the extent of redistribution, the provision of public goods, and economic growth. We sought to identify the relevant linguistic cleavages to explain variation in these outcomes. We let the data tell us whether deep cleavages, originating at an earlier time in history, are more or less important than more superficial cleavages that have arisen more recently. Doing so, we departed from the common approach relying on arbitrary definitions of what constitutes a relevant ethnolinguistic group. Our results carry several lessons. When it comes to civil conflict and redistribution, deeper cleavages tend to matter more. In contrast, for economic growth and public goods, we found that diversity measured using only deep cleavages is not sufficient to predict significant differences in growth. Instead, measures based on more disaggregated classifications of linguistic groups, capturing finer distinctions between languages, are important correlates of growth and public goods provision both in terms of statistical significance and in terms of economic magnitude. How should we interpret these results? We have shown that the type of cultural diversity that matters for outcomes involving conflicts of interest – civil wars, redistribution – is different from the type of diversity that matters for outcomes that entail issues of efficiency and coordination, such as growth. When it comes to conflict and redistribution, preferences are of the essence. The willingness to settle disputes or to transfer resources across a cultural divide depends on how deep the divide happens to be. Deep cleavages that go back thousands of years appear to be related with more conflicts of interest, compared to more superficial cleavages. In contrast, economic growth requires that groups have the ability to coordinate, interact and organize in networks of production, knowledge and trade. This ability is affected by linguistic divisions. In India, for instance, the degree of integration between regions is likely hindered by linguistic barriers — even linguistic barriers separate relatively similar linguistic groups such as Hindi and Gujarati speakers. Coordination, integration and more generally the ability to form knowledge, production and trading networks is hampered as soon as linguistic differentiation prevents interactions between groups, and this can occur between groups that are relatively similar linguistically. The case of public goods shares characteristics of both types of outcomes: public goods are inherently redistributive in nature, and their provision depends on differences in preferences among participants. At the same time, the provision of public goods requires coordination and interactions, that even superficial cleavages might hamper. We found that, much as in the case of growth, for a wide array of measures of public goods, fine distinctions between linguistic groups matter to hinder their provision. Even when cleavages are shallow, a country may fail to have well-functioning public services, not necessarily because people are unwilling to redistribute, but because of coordination failures. Future work should seek to better understand the theoretical mechanisms that account for the contrasting findings between conflict and redistribution on the one hand, and growth and public goods on the other hand. In particular, clarifying the differing effects of diversity on efficiency and coordination (where fine distinctions seem to matter more) and preferences (where coarse distinctions seem of the essence) may help account for our results. Finally, we have focused on linguistic diversity, as a measure of a broader concept of ethnolinguistic heterogeneity, and even more broadly as a proxy for cultural diversity. One advantage of focusing on languages is that linguistic distinctions are quite objective: it is easier to judge whether two populations speak different languages than to decide whether two populations belong to different ethnicities, a more amorphous concept (precisely for this reason, ethnic categorizations are often based on linguistic divisions, particularly for Africa). Another advantage is that data on linguistic divisions, particularly in the form of trees, is more readily available than data on the genealogical structure of ethnic groups within countries. There are, however, drawbacks to focusing on languages: to the extent that linguistic divisions are imperfect measures of the source of diversity that matters most, this should lead to downward bias on the estimates of the effect of diversity on political economy outcomes. In principle, the methodology we have developed for linguistic trees should be applicable to other kinds of differences between populations. With advances in population genetics, population phylogenies have become more widely available. Although this data is not yet available in a single format such as the Ethnologue for languages, applying our method to genetic data could lead to fruitful advances in the study of the political economy of cultural diversity.