Probabilistic Assortative Matching under Nash Bargaining

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Abstract/Contents

Abstract: 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.

Type of resource	text
Date created	August 18, 2021

DOI	https://doi.org/10.25740/vr276bb1732
Location	https://purl.stanford.edu/vr276bb1732

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License: This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).

Preferred citation: Bonneton, N. and Sandmann, C. (2022). Probabilistic Assortative Matching under Nash Bargaining. Stanford Digital Repository. Available at https://purl.stanford.edu/vr276bb1732

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