Reassessing the Resource Curse using Causal Machine Learning

Roland Hodler, Michael Lechner and Paul Raschky

No 15272, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: 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.

Keywords: Resource curse; Mining; Economic development; Conflict; Causal machine learning; Africa (search for similar items in EconPapers)
JEL-codes: C21 O13 O55 Q34 R12 (search for similar items in EconPapers)
Date: 2020-09
New Economics Papers: this item is included in nep-afr, nep-big, nep-cmp and nep-gro
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Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Reassessing the Resource Curse using Causal Machine Learning (2020)
Working Paper: Reassessing the Resource Curse using Causal Machine Learning (2020)
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