Optimization Using Genetic Algorithms: An Application to the Real Business Cycle Model

Christian Johnson ()

Working Papers Central Bank of Chile from Central Bank of Chile

Abstract: This paper uses genetic algorithms (GAs) to find the optimal parameter values in the solution of the Real Business Cycle model. To generate the policy functions of the individual, we approximate the conditional expectation of the Euler equation using an exponential polynomial function, based on the method proposed by Marcet (1991). The ambiguity in the selection of the starting values for the proposed algorithm allows the application of the GAs methodology to improve the macroeconomic simulations.

Date: 1997-03
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Persistent link: https://EconPapers.repec.org/RePEc:chb:bcchwp:10

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