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The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia

Samuel Bazzi1; Robert Blair2; Christopher Blattman3; Oeindrila Dube3; Matthew Gudgeon4; Richard Peck5

1 Boston University · 2 Brown University · 3 University of Chicago · 4 U.S. Military Academy · 5 Northwestern University

The Review of Economics and Statistics 2022

How feasible is violence early-warning prediction? Colombia 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.

DOI
10.1162/rest_a_01016
Volume
104 (4)
Pages
764-779
Language
en
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