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Time-varying coefficients in a simultaneous equation model: Theoretical concept and some simulation results

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  • Möller, Joachim

Abstract

The paper deals with the estimation of a simultaneous equation system with time-varying parameters. The system is formulated in state space form and it is shown that the Kalman filter algorithm is applicable. The prior information required by this estimation method can be obtained by maximization of the likelihood function via Fisher-Scoring. Applying and extending an approach due to Engle, Watson (1981) leads to the recursive calculation of the score and the information matrix for the model under consideration. Three simulation experiments are run to show that the proposed algorithm performs well with respect to the identification of time-varying parameters in a simultaneous equation model.

Suggested Citation

  • Möller, Joachim, 1988. "Time-varying coefficients in a simultaneous equation model: Theoretical concept and some simulation results," Discussion Papers, Series I 241, University of Konstanz, Department of Economics.
    • Handle: RePEc:zbw:kondp1:241
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    1. Alexander H. Sarris, 1973. "A Bayesian Approach To Estimation Of Time-Varying Regression Coefficients," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 2, number 4, pages 501-523, National Bureau of Economic Research, Inc.
    2. Engle, Robert F., 1984. "Wald, likelihood ratio, and Lagrange multiplier tests in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 13, pages 775-826, Elsevier.
    3. Donald T. Sant, 1977. "Generalized Least Squares Applied to Time Varying Parameter Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 6, number 3, pages 301-314, National Bureau of Economic Research, Inc.
    4. Chow, Gregory C., 1984. "Random and changing coefficient models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 21, pages 1213-1245, Elsevier.
    5. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    6. Watson, Mark W. & Engle, Robert F., 1983. "Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models," Journal of Econometrics, Elsevier, vol. 23(3), pages 385-400, December.
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    Cited by:

    1. Schellhorn, Martin & Winker, Peter, 1994. "Stochastic simulations of a macroeconomic disequilibrium model for West Germany," Discussion Papers, Series II 235, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".

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