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  3. Esteban Peralta, University of Michigan

Esteban Peralta, University of Michigan

“Matching, information, and Wage Dispersion”

Abstract: This paper reveals the structure of stable outcomes in labor markets with transferable utilities in which workers’ types are private information. The presence of incomplete information can enlarge the set of stable outcomes by reducing and/or increasing, respectively, the minimum and maximum wage gap required by stability under complete information, but whether this is so depends on workers’ preferences. When preferences exhibit strict increasing differences, the minimum wage gap is reduced, without changing the maximum, but only when those differences are not too large. Instead, the presence of strict decreasing differences increases the maximum wage gap, without changing the minimum, but only when those differences are not too small. The presence of strict but “unbounded” differences leads to “unraveling” and so the sets of complete- and incomplete-information stable allocations collapse.

15 de Junio de 2021


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