| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP13829 |
| DP13829 The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia | |
| Christopher Blattman; Oeindrila Dube; Samuel Bazzi; Matthew Gudgeon; Richard Peck; Robert Blair | |
| 发表日期 | 2019-06-27 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | 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 of finegrained 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. |
| 主题 | Development Economics |
| 关键词 | Conflict Prediction Indonesia Colombia Civil war Machine learning Forecasting |
| URL | https://cepr.org/publications/dp13829 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/542704 |
| 推荐引用方式 GB/T 7714 | Christopher Blattman,Oeindrila Dube,Samuel Bazzi,et al. DP13829 The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia. 2019. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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