Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods
John B. Taylor
The purpose of this paper is to report on a comparison of several alternative numerical
solution techniques for nonlinear rational expectations models. The comparison was made by
asking individual researchers to apply their different solution techniques to a simple
representative agent, optimal, stochastic growth model. Decision rules as well as simulated
time series are compared. The differences among the methods turned ou t to be quite
substantial for certain aspects of the growth model. Therefore, researchers might want to be
careful not to rely blindly on the results of any chosen numerical solution method in applied
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