| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15272 |
| DP15272 Reassessing the Resource Curse using Causal Machine Learning | |
| Roland Hodler; Michael Lechner; Paul Raschky | |
| 发表日期 | 2020-09-10 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | We reassess the effects of natural resources on economic development and conflict, applying a causal forest estimator and data from 3,800 Sub-Saharan African districts. We find that, on average, mining activities and higher world market prices of locally mined minerals both increase economic development and conflict. Consistent with the previous literature, mining activities have more positive effects on economic development and weaker effects on conflict in places with low ethnic diversity and high institutional quality. In contrast, the effects of changes in mineral prices vary little in ethnic diversity and institutional quality, but are non-linear and largest at relatively high prices. |
| 主题 | Development Economics ; International Trade and Regional Economics ; Macroeconomics and Growth |
| 关键词 | Resource curse Mining Economic development Conflict Causal machine learning Africa |
| URL | https://cepr.org/publications/dp15272 |
| 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/544247 |
| 推荐引用方式 GB/T 7714 | Roland Hodler,Michael Lechner,Paul Raschky. DP15272 Reassessing the Resource Curse using Causal Machine Learning. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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