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Adaptive learning in models with lagged variables

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  • Wilfredo Leiva

Abstract

In this work I study the stability of the dynamics generated by adaptive learning processes in intertemporal economies with lagged variables. I prove that determinacy of the steady state is a necessary condition for the convergence of the learning dynamics and I show that the reciprocal is not true characterizing the economies where convergence holds. In the case of existence of cycles I show that there is not, in general, a relationship between determinacy and convergence of the learning process to the cycle. I also analyze the expectational stability of these equilibria.

Suggested Citation

  • Wilfredo Leiva, 1999. "Adaptive learning in models with lagged variables," Economics Working Papers 413, Department of Economics and Business, Universitat Pompeu Fabra.
  • Handle: RePEc:upf:upfgen:413
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    References listed on IDEAS

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    1. Chatterji Shurojit, 1995. "Temporary Equilibrium Dynamics with Bayesian Learning," Journal of Economic Theory, Elsevier, vol. 67(2), pages 590-598, December.
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    7. Woodford, Michael, 1990. "Learning to Believe in Sunspots," Econometrica, Econometric Society, vol. 58(2), pages 277-307, March.
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    More about this item

    Keywords

    Intertemporal equilibrium; models with lagged variables; adaptive learning processes; expectational stability;

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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