Identification and Estimation of Empirical Dynamic Matching Models

This paper investigates the identification and parametric estimation of marriagematching models. We first extend the identification result for the empirical dynamicmarriage matching model proposed in Choo (2015) by allowing the unobserved het-erogeneities to be drawn from more general distributions. We then provide a fixedpoint representation of the equilibrium for a wide class of matching models that arefully characterized by an aggregate matching function. The log monotone transformof this fixed point representation is shown to be a contraction, which implies the ex-istence of a unique equilibrium in these models. Using this result, we propose usingthe Nested Fixed Point (NFXP) algorithm to parametrically estimate these models.We also investigate the computational performance of the NFXP estimator throughMonte Carlo exercises. Finally, we illustrate the NFXP estimation approach by inves-tigating the effect of China's One-Child Policy on the marriage distribution in China