Solving the Stochastic Growth Model by Linear-Quadratic Approximation and by Value-Function Iteration

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Solving the Stochastic Growth Model by Linear-Quadratic Approximation and by Value-Function Iteration

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Christiano, Lawrence J

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Lawrence Christiano

Abstract

This article describes three approximation methods I used to solve the growth model (Model 1) studied by the National Bureau of Economic Research's nonlinear rational-expectations-modeling group project, the results of which are summarized by Taylor and Uhling (1990). The methods involve computing exact solutions to models that approximate Model 1 in different ways. The first two methods approximate Model 1 about its nonstochastic steady state. The third method works with a version of the model in which the state space has been discretized. A value-function iteration method is used to solve that model.

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Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 8 (1990)
Issue (Month): 1 (January)
Pages: 23-26
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Handle: RePEc:bes:jnlbes:v:8:y:1990:i:1:p:23-26

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