Purpose
The purpose of this paper is to investigate the nonlinear relationship between shadow economy and income inequality and determine whether the size of shadow economy can influence the level of income inequality.
Design/methodology/approach
Both parametric (panel OLS) and nonparametric/semiparametric regression suggested by Robinson (1988) will be used to capture the dynamic nonlinear relationship between these variables using unbalanced panel data of 154 countries from 2000 to 2007. Additionally, the relationship between income inequality and shadow economy on both developed and developing countries will be analyzed and compared.
Findings
First, semiparametric analysis and nonparametric analysis are significantly different than parametric analysis and better in nonlinear analysis between income inequality and shadow economy. Second, income inequality and shadow economy resemble an inverted-N relationship. Third, the relationship between income inequality and shadow economy is different in developed countries (OECD countries) and developing countries, where OECD countries have similar inverted-N relationship as before. However, for developing countries, income inequality and shadow economy show an inverted-U relationship, similar to the original Kuznets hypothesis.
Practical implications
This study suggests that there is a possible trade-off between income inequality and shadow economy and helps policy makers in solving both problems effectively.
Originality/value
Despite the growing importance of income inequality and shadow economy, literature linking the two variables is scarce. To the best of the authors’ knowledge, there is no literature that nonlinearly links these two variables. Furthermore, the dynamics of the relationship between these two variables in developed countries and developing countries will be explored as well.
Does income inequality increase the shadow economy? Empirical evidence from Uganda
