Deep Determinants of Corruption? A Subnational Analysis of Resource Curse Dynamics in American States
Datos Bibliográficos
| ID | 6340441 |
|---|---|
| Autores | Michael D Tyburski (0000-0001-6487-4039, Kansas State University), Michael Tyburski (Kansas State University, Manhattan, USA), Patrick Egan (0000-0002-5238-0629, Tulane University, New Orleans, LA, USA, autor de correspondencia), Aaron Schneider (0000-0001-9609-7115, University of Denver, CO, USA) |
| Año | 2020 |
| Volumen | 73 |
| Número | 1 |
| Páginas | 111-125 |
| Fecha de publicación | 2020-03-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Political Research Quarterly (JOURNAL) |
| Identificadores de la revista | ISSN: 1065-9129 • E-ISSN: 1938-274X |
| Editorial | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/1065912919878264 |
| OpenAlex | W2979339118 |
| Idioma | EN |
| Citas recibidas | 6 |
| Referencias citadas | 70 |
Drawing on comparative resource curse literature and American literature on the determinants of corruption, we argue that the impact of natural resource extraction on corruption outcomes is state-dependent. That is, in environments where corruption is already high, natural resource windfalls allow political actors and economic elites to take advantage of state brokerage, further increasing corruption. However, in previously less-corrupt states, increased natural resource extraction will not induce corruption. We rely on hierarchical linear models to interpret federal corruption convictions data for the fifty American states between 1976 and 2012 and employ generalized method of moments estimators to account for potential endogeneity. The findings are robust to alternative specifications and have implications for the management of new resource extraction opportunities
Curse · Development economics · Econometrics · Economic system · Economics · Endogeneity · Language change · Natural resource · Political corruption · Political economy · Political science · Politics · Public economics · Resource (disambiguation · Resource curse · Sociology · State (computer science · Computer Science · Corruption and Economic Development · Law · Mining and Resource Management · Natural Resources and Economic Development
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| Obras citantes distintas | 6 |
|---|---|
| Citas por año | 1,2 |
| Intervalo de citas | 2021 - 2026 (6) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 6 |