Reassessing the Resource Curse using Causal Machine Learning

Roland Hodler, Michael Lechner and Paul Raschky

No 2016, Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science

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)
Pages: 37 pages
Date: 2020-09
New Economics Papers: this item is included in nep-big, nep-dev, nep-env and nep-gro
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://ux-tauri.unisg.ch/RePEc/usg/econwp/EWP-2016.pdf (application/pdf)

Related works:
Working Paper: Reassessing the Resource Curse using Causal Machine Learning (2020)
Working Paper: Reassessing the Resource Curse using Causal Machine Learning (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:usg:econwp:2020:16

Access Statistics for this paper

More papers in Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science Contact information at EDIRC.
Bibliographic data for series maintained by ().