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Econometrica Vol. 51 No. 4 1983

Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models

Ray C. Fair1,2; John B. Taylor3,4

1 Yale School of Management - International Center for Finance · 2 Yale University - Cowles Foundation · 3 National Bureau of Economic Research · 4 Stanford University

Abstract

A solution method and an estimation method for nonlinear rational expectations models are presented in this paper.The solution method can be used in forecasting and policy applications and can handle models with serial correlation and multiple viewpoint dates.When applied to linear models, the solution method yields the same results as those obtained from currently available methods that are designed specifically for linear models.It is, however, more flexible and general than these methods.The estimation method is based on the maximum likelihood principal.It is, as far as we know, the only method available for obtaining maximum likelihood estimates for nonlinear rational expectations models.The method has the advantage of being applicable to a wide range of models, including, as a special case, linear models.The method can also handle different assumptions about the expectations of the exogenous variables, something which is not true of currently available approaches to linear models.

DOI
10.2307/1912057
Volume
51
Issue
4
Pages
1169
Sources
bibtex:phds-export.bib openalex crossref

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