Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models
AbstractA 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.
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 564.
Length: 41 pages
Date of creation: 1980
Date of revision:
Publication status: Published in Econometrica (July 1983), 51(4): 1169-1183
Note: CFP 575.
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Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
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Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
Other versions of this item:
- Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-85, July.
- Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models," NBER Technical Working Papers 0005, National Bureau of Economic Research, Inc.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lars Peter Hansen & Thomas J. Sargent, 1979.
"Formulating and estimating dynamic linear rational expectations models,"
127, Federal Reserve Bank of Minneapolis.
- Hansen, Lars Peter & Sargent, Thomas J., 1980. "Formulating and estimating dynamic linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 7-46, May.
- Taylor, John B, 1977. "Conditions for Unique Solutions in Stochastic Macroeconomic Models with Rational Expectations," Econometrica, Econometric Society, vol. 45(6), pages 1377-85, September.
- Thomas J. Sargent, 1980.
"Interpreting economic time series,"
58, Federal Reserve Bank of Minneapolis.
- Lucas, Robert E, Jr & Prescott, Edward C, 1971. "Investment Under Uncertainty," Econometrica, Econometric Society, vol. 39(5), pages 659-81, September.
- Chow, Gregory C., 1980. "Estimation of rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 241-255, May.
- Wallis, Kenneth F, 1980. "Econometric Implications of the Rational Expectations Hypothesis," Econometrica, Econometric Society, vol. 48(1), pages 49-73, January.
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