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

被引:11
|
作者
Bazzi, Samuel [1 ]
Blair, Robert A. [2 ]
Blattman, Christopher [3 ]
Dube, Oeindrila [3 ]
Gudgeon, Matthew [4 ]
Peck, Richard [5 ]
机构
[1] Boston Univ, Boston, MA 02215 USA
[2] Brown Univ, Providence, RI 02912 USA
[3] Univ Chicago, Chicago, IL 60637 USA
[4] US Mil Acad, West Point, NY 10996 USA
[5] Northwestern Univ, Evanston, IL 60208 USA
关键词
CIVIL CONFLICT; ARMED CONFLICT; LESSONS; FUTURE; SHOCKS; MODEL;
D O I
10.1162/rest_a_01016
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:764 / 779
页数:16
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