TY  - JOUR
AU  - Fair,Ray C.
AU  - Taylor,John B.
TI  - Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models
JF  - National Bureau of Economic Research Technical Working Paper Series
VL  - No. 5
PY  - 1980
Y2  - October 1980
UR  - http://www.nber.org/papers/t0005
L1  - http://www.nber.org/papers/t0005.pdf
N1  - Author contact info:
Ray C. Fair
Cowles Foundation
P.O. Box 208281
Yale University
New Haven, CT  06520-8281
E-Mail: ray.fair@yale.edu

John B. Taylor
Herbert Hoover Memorial Building
Stanford University
Stanford, CA 94305-6010
Tel: 650/723-9677
Fax: 650-723-1687
E-Mail: John.Taylor@stanford.edu
AB  - 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. For large nonlinear models the results in this paper indicate that the method works quite well. 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.
ER  -