Institutions and the resource curse: New insights from causal machine learning

There is a widely held belief that natural resource rents are a blessing if institutions are strong, but a curse if institutions are weak. We use data from 3,800 Sub-Saharan African districts and apply a causal forest estimator to reassess the relationship between institutions and the effects of res...

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Bibliographic Details
Published in:PloS one 2023-06, Vol.18 (6), p.e0284968-e0284968
Main Authors: Hodler, Roland, Lechner, Michael, Raschky, Paul A
Format: Article
Language:English
Subjects:
Analysis
Biology and Life Sciences
Causality
Computer and Information Sciences
Earth Sciences
Ecology and Environmental Sciences
Economic Development
Environmental aspects
Forecasts and trends
GDP
Geospatial data
Gross Domestic Product
Health aspects
Hypotheses
Institutions
Lead
Machine Learning
Market prices
Methods
Mineral industry
Minerals
Mining
Mining industry
Natural Resources
Physical Sciences
Political systems
Social Sciences
Sub-Saharan Africa
Violence
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Summary:There is a widely held belief that natural resource rents are a blessing if institutions are strong, but a curse if institutions are weak. We use data from 3,800 Sub-Saharan African districts and apply a causal forest estimator to reassess the relationship between institutions and the effects of resource rents. Consistent with this belief, we document that stronger institutions increase the positive effect of the presence of mining activities on economic development and dampen the negative effect of mining activities on conflict. In contrast, we find that the effects of higher world mineral prices on economic development and conflict in mining districts are non-linear and vary little in institutional quality.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0284968