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A Heterogeneous Agent, Indivisible Labor Model Solved By Means Of Genetic Algorithms

Listed author(s):
  • Author James Woods

    (University of California, Davis)

In this paper, I develop an algorithm for solving heterogeneous agent dynamic models in which individual decision rules influence each other. This approach is more general than the other heterogeneous agent solution methods in that it only requires a well formed objective function. The key innovation of the algorithm is to parameterize the policy rules of the individuals and then to find the Nash equilibrium in policy rules by using genetic algorithms to evolve optimal policy responses. To illustrate the algorithm, I solve an indivisible labor model without full unemployment insurance that endogenously induces heterogeneous agents.

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Paper provided by EconWPA in its series Macroeconomics with number 9907007.

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Length: 23 pages
Date of creation: 28 Jul 1999
Handle: RePEc:wpa:wuwpma:9907007
Note: Type of Document - Word97; pages: 23 ; figures: included
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