Economic uncertainty and corruption: evidence from a large cross-country data set |
| |
Authors: | Rajeev K. Goel |
| |
Affiliation: | Department of Economics , Illinois State University , Campus Box 4200, Normal 61790-4200 , USA |
| |
Abstract: | A vast amount of research has considered numerous causes and correlates of corruption. Also, there have been many studies of the consequences of various forms of uncertainty. However, exploration of the nexus between economic uncertainty and corruption appears scarce. After providing an intuitive and heuristic linkage between general economic uncertainty and corruption, this article uses a large cross-country data set to augment a fairly standard model with simple proxies for uncertainty and to investigate how economic uncertainty might affect the prevalence of corruption. In addition, a quantile-regression framework is used to judge how the strength of various covariates may differ with the level of corruption. Seven main points emerge from the estimates. First, economic uncertainty is associated positively with corruption, and the relation seems to be robust across measures of uncertainty and corruption. Second, quantile-regression estimates indicate considerable parametric heterogeneity across the distribution of corruption. Third, Gross Domestic Product (GDP) per capita has the expected corruption-mitigating role. Fourth, increased political rights and civil liberties also appear to lower corruption. Fifth, greater government consumption is associated with lower corruption. Sixth, while the hyperinflation dummy lacks significance in most OLS regressions, its significance varies across the distribution of corruption. Seventh, neither police force nor government subsidies shows significance, but transition economies have more corruption. |
| |
Keywords: | corruption uncertainty government quantile regression transition economies |
|
|