Educational Assortative Mating and Household Income Inequality

Abstract

We thank James J. Heckman, three referees, and seminar participants at several universities and conferences for comments and suggestions. We are grateful to Rasmus Landersø for helping us with the analysis of the Danish data. The project received financial support from the Norwegian Research Council. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Accounting for Urban China's Rising Income Inequality: The Roles of Labor Market, Human Capital, and Marriage Market Factors

“…To decompose changes in income inequality into different factors, we follow the methodology of Eika et al (2014), originally due to DiNardo et al (1996). The idea is to hold the distribution of one factor fixed at base period t 0 while we let the distribution of other factors vary over time to obtain the counterfactual distribution of family income.…”

“…The idea is to hold the distribution of one factor fixed at base period t 0 while we let the distribution of other factors vary over time to obtain the counterfactual distribution of family income. Second, while Eika et al (2014) only study married couples, we include unmarried adults as well. We also extend Eika et al (2014) in two aspects.…”

“…P c (e| t) is jointly determined by the marginal distributions of husband's and wife's education (P c (e h | t) and P c (e w | t)) and the degree of educational assortative mating s. In our main analyses, we use sorting parameters s(e| t) in Eika et al (2014) to measure assortative mating. P c (e| t) is the share of married couples where the husband has education level e h and the wife has education level e w in t, subject to ∑ e c ∈E c P c (e|t) = 1.…”

“…Pan et al (2015) conclude that assortative mating has contributed to China's rising income inequality, but their study is plagued by at least two shortcomings. First, their base comparison group is random matching, but the correct comparison should be the matching pattern at the initial year, as discussed in Eika et al (2014). Second, they have not simultaneously considered other factors that also contribute to family income inequality, such as returns to education.…”

“…Methodologically, our approach extends Eika et al (2014) by differentiating labor market factors into employment, returns to education, and within-education-group inequality. On the other hand, marriage market factors accounted for about one-quarter of the increase in Gini.…”