Occupational income inequality of Thailand: a case study of utilizing income dominant-distribution networks to measure inequality beyond Gini coefficient

Abstract

Income inequality is an important issue that has to be solved in order to make progress in our society. The study of income inequality is well received through the Gini coefficient, which is used to measure degrees of inequality in general. While this method is effective in several aspects, the Gini coefficient alone inevitably overlooks minority subpopulations (e.g. occupations) which results in missing undetected patterns of inequality in minority. In this study, the surveys of incomes and occupations from more than 12 million households across Thailand have been analyzed by using both Gini coefficient and network densities of income dominant-distribution network to get insight regarding the degrees of general and occupational income inequality issues. The results shown that there were less issues for both types of inequality in agricultural provinces (low Gini coefficients and network densities), while some non-agricultural provinces faced an issue of occupational income inequality (high network densities) without any issue of general income inequality (low Gini coefficients). Moreover, the results also illustrated the gaps of income inequality using an estimation statistics, which not only supports whether income inequality existed, but we were also able to tell the magnitudes of income gaps among occupations. These results cannot be obtained via Gini coefficients alone. This work serves as a use case of analyzing income inequality from both general population and subpopulations perspectives that can be utilized in studies of other countries.