When are adaptive expectations rational? A generalization
This note presents a simple generalization of the adaptive expectations mechanism in which the learning parameter is time variant. It is shown that expectations generated in this way are rational in the sense of producing minimum mean squared forecast errors for a broad class of time series models, namely any process that can be written in linear state space form.
|Date of creation:||25 Oct 2011|
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- H. Theil & S. Wage, 1964. "Some Observations on Adaptive Forecasting," Management Science, INFORMS, vol. 10(2), pages 198-206, January.
- Durbin, James & Koopman, Siem Jan, 2001.
"Time Series Analysis by State Space Methods,"
Oxford University Press, number 9780198523543.
- Tom Doan, . "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Roger E. A. FARMER, 2002. "Why Does Data Reject the Lucas Critique," Annales d'Economie et de Statistique, ENSAE, issue 67-68, pages 111-129.
- M. Nerlove & S. Wage, 1964. "On the Optimality of Adaptive Forecasting," Management Science, INFORMS, vol. 10(2), pages 207-224, January.
- Cuthbertson, Keith, 1988. "Expectations, Learning and the Kalman Filter," The Manchester School of Economic & Social Studies, University of Manchester, vol. 56(3), pages 223-46, September.
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