Income Inequality and the Labor Market

Abstract

Income inequality is a major problem in labor economics, especially in a rapidly developing economy like China. With China‘s remarkable economic growth in the past few decades, the issue of income distribution has attracted more and more attention from scholars and decision-makers. This article investigates the Simpson paradox, a statistical phenomenon in which the trend of aggregated data conflicts with the subgroup pattern and explores how this paradox distorts the interpretation of the income gap. This paradox is particularly relevant in the context of China. Regional differences and departmental subdivisions create complex data structures that need to be carefully analyzed. By integrating set theory with labor economics, we construct an analytical framework to examine earnings distribution across gender and industry segments within China‘s labor market. Our methodological approach involves defining the labor market as a universal set composed of multiple mutually exclusive subsets based on demographic and economic characteristics. Through this framework, we systematically analyze how income distribution patterns vary across different population strata and how these variations might be masked in aggregate data. The analysis of large-scale data sets including China‘s household income items shows that relying entirely on comprehensive indicators such as the Gini coefficient may mask significant inequality within the subgroup. The research process includes collecting data from multiple sources, stratifying samples, and comparative analysis between and within subgroups. These findings highlight the need to implement layered data analysis in economic research and policy formulation, and also provide actionable suggestions to mitigate deviations in inequality measurement.