As Good as Married? A Model of Premarital Cohabitation and Learning

This article develops a two-sided search-matching model with imperfectly observed types and sequential learning. We use the metaphor of premarital cohabitation and assume that it is initiated to learn more about one's prospective spouse. We show that couples match within classes and that the classes of cohabiting and married couples partially overlap. Couples are more discriminating about whom they marry than whom they cohabit with. We demonstrate that cohabiting individuals eventually learn each other's true type. We show that sequential learning during cohabitation reduces signaling errors and that the Bayes estimator of true type converges almost surely to true type. As noisy information is filtered over time, the risk of mismatch disappears and the aggregate matching pattern based on true types is restored.