摘要 : To understand rising income inequality in the United States, we use data from the March Current Population Survey (CPS) to decompose income inequality into components attributable to five personal traits: sex, race, education, occ... 展开 To understand rising income inequality in the United States, we use data from the March Current Population Survey (CPS) to decompose income inequality into components attributable to five personal traits: sex, race, education, occupation, and industry of work. By quantifying how income differences across these traits contribute to total inequality, and how those contributions have changed over time, we vet competing hypotheses for the rising gap. In performing this analysis, we correct for data censorship ('Top-coding") within the CPS by fitting the upper tail of the income distribution and imputing the hidden observations; this represents an extension to previous studies that instead truncate the top several percentiles of income data. Our findings suggest that changes in the returns to education played an important role in driving the observed rise in inequality. 收起