Solving Nonlinear Stochastic Growth Models: a Comparison of Alternative Solution Methods

47 Pages Posted: 18 Apr 2007 Last revised: 13 Jul 2010

See all articles by John B. Taylor

John B. Taylor

Stanford University; National Bureau of Economic Research (NBER)

Harald Uhlig

University of Chicago - Department of Economics

Date Written: September 1989

Abstract

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 out 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 work.

Suggested Citation

Taylor, John B. and Uhlig, Harald, Solving Nonlinear Stochastic Growth Models: a Comparison of Alternative Solution Methods (September 1989). NBER Working Paper No. w3117, Available at SSRN: https://ssrn.com/abstract=980434

John B. Taylor (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Harald Uhlig

University of Chicago - Department of Economics ( email )

1101 East 58th Street
Chicago, IL 60637
United States

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