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Backward Unraveling over Time: The Evolution of Strategic Behavior in the Entry-Level British Medical Labor Markets

Utku Unver

Game Theory and Information from EconWPA

Abstract: This paper studies an adaptive artificial agent model using a genetic algorithm to analyze how a population of decision-makers learns to coordinate on the selection of an equilibrium or a social convention in a two-sided matching game. In the contexts of centralized and decentralized entry-level labor markets, evolution and adjustment paths of unraveling are explored using this model in an environment inspired by the Kagel and Roth (Quarterly Journal of Economics, 2000) experimental study. As an interesting result, it is demonstrated that stability need not be required for the success of a matching mechanism under incomplete information in the long run.

Keywords: Genetic algorithms; linear programming matching; stability; two-sided matching; unraveling (search for similar items in EconPapers)
JEL-codes: C15 C78 D83 (search for similar items in EconPapers)
Date: 1999-07-04, Revised 2004-02-09
Note: This study won one of the two Graduate Student Prizes awarded by the Society for Computational Economics in 1999. This is a revised draft dated June, 2000.
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Journal Article: Backward unraveling over time: The evolution of strategic behavior in the entry level British medical labor markets (2001) Downloads
Working Paper: Backward Unraveling over Time: The Evolution of Strategic Behavior in the Entry-Level British Medical Labor Markets (1999) Downloads
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