Corruption in US states: the effects of socio-economic factors
İsmail Şahin, Bahadır Şahin
Abstract
İsmail Şahin, Bahadır Şahin
Abstract
This study is an empirical examination of socio-economic determinants of corruption in US states. Using the data on state-by-state number of corruption convictions from the US Department of Justice as the dependent variable, socio-economic factors such as income inequality, education level and ethnic diversity are investigated. First, we find that US states with higher education level are generally less corrupt when corruption is defined on the basis of convictions. Second, the hypothesis arguing that greater income inequality is associated with higher levels of corruption is supported by our empirical findings. Third, the study shows some evidence that high levels of ethnic diversity positively affect corruption rates. Finally, the study provides strong evidence that the states with greater populations have lesser corruption. Using corruption convictions data, these results echo the findings of the many cross-national studies relying on the data on corruption perception.
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This study is an empirical examination of socio-economic determinants of corruption in US states. Using the data on state-by-state number of corruption convictions from the US Department of Justice as the dependent variable, socio-economic factors such as income inequality, education level and ethnic diversity are investigated. First, we find that US states with higher education level are generally less corrupt when corruption is defined on the basis of convictions. Second, the hypothesis arguing that greater income inequality is associated with higher levels of corruption is supported by our empirical findings. Third, the study shows some evidence that high levels of ethnic diversity positively affect corruption rates. Finally, the study provides strong evidence that the states with greater populations have lesser corruption. Using corruption convictions data, these results echo the findings of the many cross-national studies relying on the data on corruption perception.
Key concepts: Language change, Ethnic group, Inequality, Affect (linguistics), Diversity (politics), Demographic economics, Economic inequality, State (computer science)