Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods
John Taylor () and
Harald Uhlig ()
Journal of Business & Economic Statistics, 1990, vol. 8, issue 1, pages 1-17
The purpose of this article 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.
References: Add references at CitEc
Citations View citations in EconPapers (102) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Working Paper: Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods (1989)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: http://EconPapers.repec.org/RePEc:bes:jnlbes:v:8:y:1990:i:1:p:1-17
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano
More articles in Journal of Business & Economic Statistics from American Statistical Association
Series data maintained by Christopher F. Baum ().