Analyzing matching patterns in marriage: Theory and application to Italian data

Social scientists have long been interested in marital homogamy and its relationship with inequality. However, measuring homogamy is not straightforward, particularly when one is interested in assessing marital sorting based on multiple traits. In this paper, we argue that Separate Extreme Value (SEV) models not only generate a matching function with several desirable theoretical properties, but they are also suited for the study of multidimensional sorting. Specifically, we use rich small‐scale survey data to examine sorting among parents of school‐age children in Naples. We show that homogamy is pervasive; not only do men and women sort by age, education, and physical characteristics, but they also look for partners that share similar health‐related behavior and risk attitude. However, we also show that these marital patterns are well explained by a low number of dimensions, the most important being age cohort and human capital. In particular, human capital relates to various “outcomes” of the post‐matching relationship. Children of parents with a high human capital endowment perform better at school, although they report lower levels of subjective well‐being and of perceived quality of relationship with their mothers.