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Una nota metodológica acerca de aplicaciones del filtro de Kalman a las calibraciones en modelos de ciclo real

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Abstract

This paper pursues two objectives. One is to generalize the Kalman Filter to dynamic models with rational expectations which include current expectations of future endogenous variables. A second objective is to ilustrate two applications of this estimation procedure to stochastic rational expectations growth models. The first application is a proposal to calibrate some parameters in these models whose estimation is difficult because of the lack of appropriate data (for example, the coefficient of relative risk aversion). In the second application, the previous calibration procedure is used to offer an objective measure which allows for discriminating among alternative models that have, in some aspects, a similar stochastic behaviour. (Copyright: Fundación Empresa Pública)

Suggested Citation

  • Jesús Ruiz, 2002. "Una nota metodológica acerca de aplicaciones del filtro de Kalman a las calibraciones en modelos de ciclo real," Investigaciones Economicas, Fundación SEPI, vol. 26(1), pages 35-57, January.
    • Handle: RePEc:iec:inveco:v:26:y:2002:i:1:p:35-57
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    References listed on IDEAS

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    1. William A. Brock & Leonard J. Mirman, 2001. "Optimal Economic Growth And Uncertainty: The Discounted Case," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 1, pages 3-37, Edward Elgar Publishing.
    2. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    3. Masanao Aoki & Matthew Canzoneri, 1979. "Reduced Forms of Rational Expectations Models," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 93(1), pages 59-71.
    4. Burmeister, Edwin & Wall, Kent D., 1982. "Kalman filtering estimation of unobserved rational expectations with an application to the German hyperinflation," Journal of Econometrics, Elsevier, vol. 20(2), pages 255-284, November.
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    More about this item

    Keywords

    Kalman filter; calibration; real business cycle models; rational expectations; dynamic systems;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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