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Expectations, Learning and the Kalman Filter

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  • Cuthbertson, Keith

Abstract

Muth-rational expectations embody instantaneous learning by agents. The author relaxes this assumption and suggests that agents slowly learn about the time series behavior of variables, in a model with time varying parameters. The approach can be made empirically tractable via the Kalman filter. The complex structure of the Kalman filter is reinterpreted in terms of familiar least squares procedures. The importance of "optimal" expectations schemes that embody "learning" are compared with adaptive and Muth-rational approaches. Copyright 1988 by Blackwell Publishers Ltd and The Victoria University of Manchester

Suggested Citation

  • 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.
    • Handle: RePEc:bla:manch2:v:56:y:1988:i:3:p:223-46
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    Cited by:

    1. Giorgio Valente, 2003. "Monetary policy rules and regime shifts," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 525-535.
    2. Vitor Leone, 2011. "From Property Companies to Real Estate Investment Trusts: The Impact of Economic and Property Factors on UK Listed Property Returns," Economic Issues Journal Articles, Economic Issues, vol. 16(1), pages 19-36, March.
    3. Priestley, Richard, 1996. "The arbitrage pricing theory, macroeconomic and financial factors, and expectations generating processes," Journal of Banking & Finance, Elsevier, vol. 20(5), pages 869-890, June.
    4. Shepherd, Ben, 2012. "When are adaptive expectations rational? A generalization," Economics Letters, Elsevier, vol. 115(1), pages 4-6.
    5. Reneéa Koekemoer, 2001. "Variable Parameter Estimation Of Consumer Price Expectations For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 69(1), pages 1-39, March.
    6. Roula INGLESI-LOTZ & Renee VAN EYDEN & Charlotte DU TOIT, 2014. "The evolution and contribution of technological progress to the South African economy: Growth accounting and Kalman filter application," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 14(1), pages 175-188.
    7. Inglesi-Lotz, R., 2011. "The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application," Energy Policy, Elsevier, vol. 39(6), pages 3690-3696, June.
    8. Vitor Leone, 2010. "From Property Companies to Real Estate Investment Trusts: The Impact of Economic and Property Factors in the UK Commercial Property Returns," NBS Discussion Papers in Economics 2010/4, Economics, Nottingham Business School, Nottingham Trent University.
    9. Mark Holmes, 2000. "Monetary Shocks, Inflation and the Asymmetric Adjustment of EU Output," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 27(3), pages 253-263, September.
    10. J. L. Ford & Wee Ching Pok & S. Poshakwale, 2006. "The Predictability of KLSE CI Stock Index Futures Returns and The Conditional Multifactor APT Model," Discussion Papers 06-09, Department of Economics, University of Birmingham.

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