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Economic Freedom and Income Inequality: Evidence from a Panel of Global Economies— A Linear and a Non‐Linear Long‐Run AnalysisThis study employs panel data from 138 countries (with unbalanced time frameworks) to investigate the relationship between economic freedom and income inequality. Both linear and non‐linear cointegration methodologies are used to identify a long‐run equilibrium relationship between: (i) the overall Economic Freedom of the World index and income inequality, and (ii) the major areas of the index and income inequality. The linear long‐run parameter estimates document that the association turns out to be negative, while the non‐linear long‐run parameter estimates illustrate that above a threshold point the association between economic freedom and income inequality is negative, while below this threshold point, the association turns out to be positive. The empirical findings survive a number of robustness tests, such as alternative measures of income inequality.
The relationship between corruption and income inequality in U.S. states: evidence from a panel cointegration and error correction modelWe investigate the causality between corruption and income inequality within a multivariate framework using a panel data set of all 50 U.S. states over the period 1980 to 2004. The heterogeneous panel cointegration test by Pedroni (Oxf. Bull. Econ. Stat. 61:653–670, 1999; Econom. Theory 20:597–627, 2004) indicates that in the long run corruption and the unemployment rate have a positive and statistically significant impact on income inequality while a negative impact is found for real personal income per capita, education, and unionization rate. The Granger-causality results associated with a panel vector error correction model indicate both short-run and long-run bidirectional causality between corruption and income inequality.