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Discussion Paper Details

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Title: Reassessing the Resource Curse using Causal Machine Learning

Author(s): Roland Hodler, Michael Lechner and Paul A. Raschky

Publication Date: September 2020

Keyword(s): Africa, Causal machine learning, conflict, economic development, mining and resource curse

Programme Area(s): Development Economics, International Trade and Regional Economics and Macroeconomics and Growth

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.

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Bibliographic Reference

Hodler, R, Lechner, M and Raschky, P. 2020. 'Reassessing the Resource Curse using Causal Machine Learning'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=15272