Solving the Stochastic Growth Model by Linear-Quadratic Approximation and by Value-Function Iteration
Lawrence Christiano
Journal of Business & Economic Statistics, 1990, vol. 8, issue 1, 23-26
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.
Date: 1990
References: Add references at CitEc
Citations: View citations in EconPapers (40)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:8:y:1990:i:1:p:23-26
Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html
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
Bibliographic data for series maintained by Christopher F. Baum ().