The analysis of the effect of real interests on income distribution with ardl model approach

Abstract

The Gini coefficient which measures the unfair distribution of income is a value between 0 and 1. As the index value approaches to 1, unfairness increases and as it approaches to 0, income distribution becomes fairer. The aim of this study is to examine the effect of real interest on income distribution in 5 developing countries which are close to each other in terms of real per capita income with panel data analysis. In this context, since the data of 2000-2016 include cross sectional dependency, second generation panel root tests were used. Since the series are stable on different levels, ARDL model was utilized. Then, the coefficient between the variables were determined by using the PMG estimator and causality analysis was conducted. According to the result of the study, although there isn’t a short-term relationship between the variables, there is a cointegrated relationship in long-term. Furthermore, according to the PMG estimator, an increase of 1 unit, increases the Gini coefficient by 0.007. Since the conducted causality analysis was resulted in accordance with the Gini coefficient from real interests, it verifies this result. Since the increase in real interests increases the Gini coefficient, real interests should be decreased for a more fair income distribution, according to the result of this study.