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|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
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.:
- Cuthbertson, Keith, 1988. "Expectations, Learning and the Kalman Filter," The Manchester School of Economic & Social Studies, University of Manchester, vol. 56(3), pages 223-246, September.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
Oxford University Press,
edition 2, number 9780199641178, April.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- H. Theil & S. Wage, 1964. "Some Observations on Adaptive Forecasting," Management Science, INFORMS, vol. 10(2), pages 198-206, January.
- M. Nerlove & S. Wage, 1964. "On the Optimality of Adaptive Forecasting," Management Science, INFORMS, vol. 10(2), pages 207-224, January.
- repec:adr:anecst:y:2002:i:67-68:p:05 is not listed on IDEAS Full references (including those not matched with items on IDEAS)