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

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)

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Article provided by Fundación SEPI in its journal Investigaciones Economicas.

Volume (Year): 26 (2002)
Issue (Month): 1 (January)
Pages: 35-57

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Handle: RePEc:iec:inveco:v:26:y:2002:i:1:p:35-57
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  1. Aoki, Masanao & Canzoneri, Matthew, 1979. "Reduced Forms of Rational Expectations Models," The Quarterly Journal of Economics, MIT Press, vol. 93(1), pages 59-71, February.
  2. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
  3. 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.
  4. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-11, July.
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