Economic Uncertainty and Corruption
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Economic Uncertainty and Corruption: Evidence from a Large
Cross-Country Data Set
Rajeev Goel is Professor of Economics at Illinois State University. He is the author of Economic Models of Technological Change and Global Efforts to Combat Smoking.
Abstract
Substantial 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 paper 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
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 robust across measures of
uncertainty and corruption. Second, quantile regression estimates
indicate considerable parametric heterogeneity across the distribution
of corruption. Third, 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.