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This paper theoretically analyzes and empirically investigates the importance of local interaction between individuals of different linguistic groups for the provision of public goods at the national level. Depending on whether local interaction mitigates or reinforces antagonism towards other groups, the micro-founded theory we develop predicts that a country's provision of public goods (i) decreases in its overall linguistic fractionalization, and (ii) either increases or decreases in how much individuals locally learn about other groups. After constructing a 5 km by 5 km geographic dataset on language use for 223 countries, we compute measures of overall fractionalization and local learning, and investigate their relation to public good provision at the country level. While overall fractionalization worsens outcomes, we find a positive causal relation between local learning and public goods. Local mixing therefore mitigates the negative impact of a country's overall linguistic fractionalization. An IV strategy shows that this result is not driven by the possible endogenous spatial distribution of language speakers within countries.

This paper contributes to a burgeoning literature that uses sub-national micro data to identify the causes of civil conflicts. In particular, we study the Maoist/Naxalite conflict in India by constructing a comprehensive district level database using conflict data from four different terrorism databases and combining it with socioeconomic and geography data from myriad sources. In addition to exploiting the within country regional heterogeneity, we use the micro structure of the data to construct group-level characteristics. Using data on 360 districts for 3 time periods, we find evidence on how land inequality and lower incomes are important for the Maoist conflict. Moreover, making use of the micro structure of the data we are able to ask whether exclusion of the low castes and tribes from the growth story of India is important. We find that while the income levels of the different ethnic groups are not important, the growth of incomes of Scheduled Tribes significantly decreases the intensity of the conflict. Finally, we show how historical property rights institutions from colonial times that go back centuries can affect present day conflict outcomes through their impact on economic outcomes, social relations and the political environment in the district.

We show that ethnic distances lead to worse child health outcomes by impeding access to health-related information. We combine individual level micro data from DHS surveys for fourteen sub-Saharan African countries, with a high-resolution dataset on the spatial distribution of ethnic groups at the 1 × 1 sq. km level constructed using an Iterative Proportional Fitting algorithm. We show that children whose mothers are linguistically more distant to their neighbours face higher mortality rates and are shorter in size. Linguistically distant mothers are also less likely to know about the oral rehydration product for treating children with diarrhoea.