Impact factors and space‐time characteristics of income inequality in a global sample

Inequality has been of growing interest in the political debate and in theoretical and empirical studies for some decades. Therefore, the study of regional inequality raises some relevant questions related to the spatial nature of the data. In fact, adopting a regional point of view implies the opportunity to consider spatial interactions, which traditional studies do not include in their analyses. Therefore, the study aims to analyze income inequality before (GINI1) and after (GINI2) income and transfers, using a data set of 116 countries during a time period from 1985 to 2018. Spatial Durbin and Spatial Lag Models are applied to address spatial interactions and the spillover effect between countries and regions. First, the estimation results verify the existence of spatial correlations in income inequality for both GINI1 and GINI2. Second, both GINI1 and GINI2 produce relatively similar scenarios, which implies that the effects of the independent variables do not differ in both scenarios. Third, globalization widens the income differences of neighboring regions significantly. Fourth, urbanization has a negative and significant effect, which generates a spillover effect and reduces the inequality of neighboring economies. Finally, there is evidence that an inverted Kuznets U is rejected both for economic and financial development. Thus, inequality at the regional level provides useful insights for policy makers, as it facilitates the assessment of the effectiveness of strategies aimed at reducing regional disparities and helps to develop actions based on the location and its environment.