Macro Level Determinants of Corruption and their Economic Effects: A Cross-Country Quantile Regression Analysis

Abstract

The analysis relied on secondary quantitative data for 112 countries for 2023, using the Corruption Perceptions Index as the dependent variable and three explanatory indices: the Human Development Index, the Index of Economic Freedom, and the Human Flight and Brain Drain indicator. Firstly I estimated multiple linear regression models to identify average relationships between these variables. In the second step, I applied quantile regression in order to explore how these relationships differ across the corruption distribution, distinguishing between highly corrupt and relatively clean country groups. A second model reverses the set up and uses GDP per capita as the dependent variable with corruption and economic freedom as key predictors to test the grease versus sand the wheels hypothesis.