We study marital sorting using a novel dataset from a marriage matching platform, which uniquely records a rich set of pre-marital attributes, including preferences for children and for the division of housework and childcare. Unlike census or post-marital surveys, all characteristics are collected prior to matching and validated using official documents, yielding clean measures of preferences uncontaminated by post-marital coordination. Applying a multidimensional matching framework to twelve attributes, we find strong positive assortative matching across all dimensions. Age is the most salient trait, but preferences for children are the second most important—exceeding education—a pattern largely invisible in standard data. Preference measures play a distinct role in the matching process: they exhibit limited cross-attribute interactions with sociodemographic and anthropometric characteristics, in contrast to the pervasive interactions among those attributes. A low-dimensional factor representation shows that preferences for children constitute a separate and salient margin of sorting. Using the staged structure of the platform, we further show that assortative matching along different dimensions emerges at distinct points in the dating process: sorting by age and income is already present at the initial Application stage, whereas sorting by preferences for children becomes robust only at later stages of relationship formation, reflecting selective continuation rather than sorting at the point of final agreement. A simple theoretical exercise demonstrates that ignoring preference-based sorting and assuming homogeneous preferences across couples leads to biased estimates of policy effects on subsequent household decisions.
Joint with Chihiro Inoue and Suguru Otani.