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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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Detalles Bibliográficos
Autores principales: Hodler, Roland, Lechner, Michael, Raschky, Paul A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234542/
https://www.ncbi.nlm.nih.gov/pubmed/37262065
http://dx.doi.org/10.1371/journal.pone.0284968
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author Hodler, Roland
Lechner, Michael
Raschky, Paul A.
author_facet Hodler, Roland
Lechner, Michael
Raschky, Paul A.
author_sort Hodler, Roland
collection PubMed
description 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.
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spelling pubmed-102345422023-06-02 Institutions and the resource curse: New insights from causal machine learning Hodler, Roland Lechner, Michael Raschky, Paul A. PLoS One Research Article 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. Public Library of Science 2023-06-01 /pmc/articles/PMC10234542/ /pubmed/37262065 http://dx.doi.org/10.1371/journal.pone.0284968 Text en © 2023 Hodler et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hodler, Roland
Lechner, Michael
Raschky, Paul A.
Institutions and the resource curse: New insights from causal machine learning
title Institutions and the resource curse: New insights from causal machine learning
title_full Institutions and the resource curse: New insights from causal machine learning
title_fullStr Institutions and the resource curse: New insights from causal machine learning
title_full_unstemmed Institutions and the resource curse: New insights from causal machine learning
title_short Institutions and the resource curse: New insights from causal machine learning
title_sort institutions and the resource curse: new insights from causal machine learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234542/
https://www.ncbi.nlm.nih.gov/pubmed/37262065
http://dx.doi.org/10.1371/journal.pone.0284968
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