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In this paper, an explicit micro scenario is developed which yields a well-defined aggregate job matching function. In particular, a stochastic model of job-matching behavior is constructed in which the system steady state is shown to be approximated by an exponential-type matching function, as the population becomes large. This steady-state approximation is first derived for fixed levels of both wages and search intensities, where it is shown (without using a free-entry condition) that there exists a unique equilibrium. It is then shown that if job searchers are allowed to choose their search intensities optimally, this model is again consistent with a unique steady state. Finally, the assumption of a fixed wage is relaxed, and an optimal 'offer wage' is derived for employers.
discrete-time matching function, large population approximation, optimal search intensity, optimal offer wage
Tony E. Smith and Yves Zenou, "A Discrete-Time Stochastic Model of Job Matching", . January 2003.
Date Posted: 21 January 2006
This document has been peer reviewed.