Institutional dynamics produce resource curse traps

Communities reliant on extractive industries face a paradox: Despite the promise of economic growth from lucrative, well-paying industries, they often experience poor socioeconomic outcomes. While the so-called "resource curse" has been debated and studied extensively in a variety of disciplines, understanding when and why the resource curse occurs, and whether it is possible to escape it, remains a challenge. This study examines these questions through a dynamical systems model that incorporates theories from the literature about how extractive industries interact with institutions and the communities in which they are based. The model reveals that both the resource curse and a more diversified economy are possible, depending on the initial level of human and social capital. It also reveals how various factors, such as declining commodity prices, can trigger an abrupt and irreversible transition from the diversified equilibrium to the resource curse. A generalized version of the model further reveals that the feedback between extractive industries and institutional strength are critical in determining the occurrence of this type of transition. The results illustrate the difficulty of escaping the resource curse, identify potential leverage points or change, and highlight the critical role of institutional dynamics in producing and perpetuating extractive dynamics in these regions.

Authors

Institutions

Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2026-04-22
DOI
https://doi.org/10.1073/pnas.2520474123
Primary Topic
Natural Resources and Economic Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Institutional dynamics produce resource curse traps

Elke U. Weber, Nusrat Molla, Simon A. Levin
Proceedings of the National Academy of Sciences
Natural Resources and Economic Development
article

Institutional dynamics produce resource curse traps

Elke U. Weber, Nusrat Molla, Simon A. Levin
article en

Abstract

Communities reliant on extractive industries face a paradox: Despite the promise of economic growth from lucrative, well-paying industries, they often experience poor socioeconomic outcomes. While the so-called "resource curse" has been debated and studied extensively in a variety of disciplines, understanding when and why the resource curse occurs, and whether it is possible to escape it, remains a challenge. This study examines these questions through a dynamical systems model that incorporates theories from the literature about how extractive industries interact with institutions and the communities in which they are based. The model reveals that both the resource curse and a more diversified economy are possible, depending on the initial level of human and social capital. It also reveals how various factors, such as declining commodity prices, can trigger an abrupt and irreversible transition from the diversified equilibrium to the resource curse. A generalized version of the model further reveals that the feedback between extractive industries and institutional strength are critical in determining the occurrence of this type of transition. The results illustrate the difficulty of escaping the resource curse, identify potential leverage points or change, and highlight the critical role of institutional dynamics in producing and perpetuating extractive dynamics in these regions.

Proceedings of the National Academy of SciencesVol. 123(17)
Princeton University (US)
No poverty
Openalex Percentile: Top 10%
Natural Resources and Economic Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.