Analyzing Matching Patterns in Marriage:Theory and Application to Italian Data

WSocial 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 show how a small number of factors can be identified that capture most of the explained variance in matching patterns. We then use rich small-scale survey data to examine sorting among parents of children attending schools in Naples. Our findings show that homogamy is pervasive; not only do men and women sort by age, education, height, and physical characteristics, but they also look for partners that share similar health-related behavioral traits and risk attitude. We also show that marital patterns are well explained by a low number of dimensions, the most important being age and human capital. Moreover, children of parents with a high human capital endowment perform better at school, although they report lower levels of subjective well-being and perceived quality of relationship with their mothers.