Probabilistic Assortative Matching under Nash Bargaining

This paper re-visits the canonical random search and matching model with Nash bargaining. By introducing pair-specific production shocks, our framework generates meeting-contingent match outcomes that are random. We provide a robust characterization of probabilistic matching patterns for any non-stationary environment, generalizing results by Shimer and Smith (2000). We nd that, although their prediction of single-peaked preferences over meetings is robust, search frictions upset positive assortative matching across well-assorted pairs. As a second contribution, we show that the non-stationary random search matching model is a mean eld game, and admits a representation as a system of forward-backward stochastic differential equations. This representation affords a novel existence and uniqueness result, casting doubt on the robustness of multiple self-fulfilling equilibrium paths frequently reported in the literature.