  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
millions households across Thailand have been analyzed by using both Gini
coefficient and network densities of income domination networks to get insight
regarding the degrees of general and occupational income inequality issues. The
results show that, in agricultural provinces, there are less issues in both
types of inequality (low Gini coefficients and network densities), while some
non-agricultural provinces face an issue of occupational income inequality
(high network densities) without any symptom of general income inequality (low
Gini coefficients). Moreover, the results also illustrate the gaps of income
inequality using estimation statistics, which not only support whether income
inequality exists, but that we are 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.
