This paper argues that redrawing subnational political boundaries can transform ethnic divisions. We use a natural policy experiment in Indonesia to show how the effects of ethnic diversity on conflict depend on the political units within which groups are organized. Redistricting along group lines can reduce conflict, but these gains are undone or even reversed when the new borders introduce greater polarization. These adverse effects of polarization are further amplified around majoritarian elections, consistent with strong incentives to capture new local governments in settings with ethnic favoritism. Overall, our findings illustrate the promise and pitfalls of redistricting in diverse countries.
Policymakers can take actions to prevent local conflict before it begins, if such violence can be accurately predicted. We examine the two countries with the richest available sub-national data: Colombia and Indonesia. We assemble two decades one fine- grained violence data by type, alongside hundreds of annual risk factors. We predict violence one year ahead with a range of machine learning techniques. Models reliably identify persistent, high-violence hot spots. Violence is not simply autoregressive, as detailed histories of disaggregated violence perform best. Rich socio-economic data also substitute well for these histories. Even with such unusually rich data, however, the models poorly predict new outbreaks or escalations of violence. \Best case" scenarios with panel data fall short of workable early-warning systems.
How feasible is violence early-warning prediction? Columbia and Indonesia have unusually fine-grained data. We assemble two decades of local violent events alongside hundreds of annual risk factors. We attempt to predict violence one year ahead with a range of machine learning techniques. Our models reliably identify persistent, high-violence hot spots. Violence is not simply autoregressive, as detailed histories of disaggregated violence perform best, but socioeconomic data substitute well for these histories. Even with unusually rich data, however, our models poorly predict new outbreaks or escalations of violence. These “best case” scenarios with annual data fall short of workable early-warning systems.
We use a policy experiment in Indonesia to show how local political boundaries affect ethnic tension. Redrawing district borders along group lines reduces conflict. However, the gains in stability are undone or even reversed when new boundaries increase ethnic polarization. Greater polarization leads to more violence around majoritarian elections but has little effect around lower-stakes, proportional representation elections. These results point to distinct incentives for violence in winner-take-all settings with contestable public resources. Overall, our findings illustrate the promise and pitfalls of redrawing borders in diverse countries where it is infeasible for each group to have its own administrative unit. (JEL D72, D74, J15, O15, O17, O18)
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