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"Solution and Maximum Likelihood Estimation of Dynamic Rational
Expectations Models," (with J. B. Taylor), Econometrica,
July 1983, 1169-1185.
pdf file (940KB).
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 endogenous variables, something
which is not true of currently available approaches to linear models.
The extended path solution method discussed in this paper has
become widely used in macroeconometric modeling. It was first used in
1979#4 to analyze a version of the US model with
rational expectations in the bond and stock markets. This paper also
discusses the maximum likelihood estimation of rational expectations models.
A follow up paper is 1990#2.
Both the solution methods and the estimation methods discussed in this
paper and in 1990#2 are programmed into the
Fair-Parke program. The various commands are presented and
explained in Chapter 13 of the FP User's Guide.