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On the Learnability of Rational Expectations Equilibria in Three Business Cycle Models

Author

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  • Packalen, M.

Abstract

In this thesis we analyze the learnability of rational expectiations equilibria in three general equilibrium business cycle models. The economic example business cycles models comprise the basic real business cycles model, an increasing returns model and a model with both static and dynamic complementarities. In these models the business cycles are driven by both shocks that affect the production technology and by taste shocks that affect the marginal rate of substitution between consumption and labor. In the two latter models we also analyze the existence and learnability of sunspot rational expectations equilibria.

Suggested Citation

  • Packalen, M., 2000. "On the Learnability of Rational Expectations Equilibria in Three Business Cycle Models," University of Helsinki, Department of Economics 87, Department of Economics.
    • Handle: RePEc:fth:helsec:87
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    Citations

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    Cited by:

    1. Adam, Klaus, 2005. "Learning To Forecast And Cyclical Behavior Of Output And Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 9(1), pages 1-27, February.
    2. Adam, K., 2000. "Adaptive Learning and the Cyclical Behavior of Output and Inflation," Economics Working Papers eco2000/25, European University Institute.
    3. Slobodyan, Sergey, 2005. "Indeterminacy, sunspots, and development traps," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 159-185, January.
    4. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.

    More about this item

    Keywords

    EXPECTATIONS ; BUSINESS CYCLES ; LEARNING;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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