An Equilibrium Theory of Learning, Search and Wages

Francisco M. Gonzalez () and Shouyong Shi ()

Working Papers from University of Toronto, Department of Economics

Abstract: We construct an equilibrium theory of learning from search in the labor market, which addresses the search behavior of workers, the creation of jobs, and the wage distribution as functions of unemployment duration. In the model, each worker has incomplete information about his job-finding ability and learns about it from his search outcomes. The theory formalizes a notion akin to that of discouragement: over the unemployment spell, unemployed workers update their beliefs about their job-finding abilities downward and reduce their desired wages. One contribution of the paper is to integrate learning from search into an equilibrium framework. We show that the equilibrium exhibits wage dispersion among homogeneous workers, and that workers with longer unemployment spells have lower permanent incomes. Another contribution is to apply lattice-theoretic techniques to analyze learning from experience, which is useful because learning generates convex value functions and, in principle, multiple solutions to a worker's optimization problem.

Keywords: Learning; Wages; Unemployment; Directed search; Supermodularity. (search for similar items in EconPapers)
JEL-codes: E24 D83 J64 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-lab and nep-mac
Date: 2008-08-12
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