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

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M. Utku Ünver () (University of Pittsburgh)

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Abstract

This study introduces a computational tool to analyze how a population of decision makers communicates and learns to coordinate to attain an equilibrium or a social convention in a two-sided matching game with incomplete information. Genetic algorithms are used in an environment where agents are heterogeneous and have private information. In the contexts of centralized and decentralized entry-level labor markets, evolution and adjustment paths of "unraveling" are explored using this tool. The situation of the Kagel and Roth (1997) laboratory experiment is generalized under a variety of markets and institutions. Evolution paths of unraveling are investigated, particularly for the historic entry-level British medical labor markets. As one result, it is demonstrated that "stability" need not be required for the success of a matching-mechanism under incomplete information in the long run. Evolutionary evidence is found to support the field success of unstable linear programming mechanisms used in Britain.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 1132.

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Date of creation: 01 Mar 1999
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Handle: RePEc:sce:scecf9:1132

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  1. Alvin E Roth & Muriel Niederle, 2007. "Making Markets Thick: Designing Rules for Offers and Acceptances," Levine's Bibliography 843644000000000142, UCLA Department of Economics. [Downloadable!]
  2. John Duffy, 2004. "Agent-Based Models and Human Subject Experiments," Computational Economics 0412001, EconWPA. [Downloadable!]
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