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Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models
Ray C. Fair and John B. Taylor
Vol. 51, No. 4 (Jul., 1983), pp. 1169-1185
Published by: The Econometric Society
Stable URL: http://www.jstor.org/stable/1912057
Page Count: 17
You can always find the topics here!Topics: Economic expectations, Macroeconomic modeling, Modeling, Rational expectations theory, Expected values, Simulations, Parametric models, Iterative solutions, Economic models, Mathematical independent variables
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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.
Econometrica © 1983 The Econometric Society