Warianty tytułu
Języki publikacji
Abstrakty
Summing up the discussion on specification errors it should be pointed out that such widespread methods as ad hoc specifications and sensitivity analysis are of little use for the estimation of an unknown hyper-structure with time-varying parameters. And that is exactly what is important for the improvement of the prognostic quality of the econometric model. It is also particularly significant for the economic interpretation of an estimated course of the parameter. The course of the estimated values of the parameter βt/t is definitely dependant on the choice of the covariance matrix Q. Moreover, if the influence of specification errors of the transition matrix F is considered, we can easily imagine that without a proper criterion of estimation, practically every "demanded" course of the parameter can be estimated according to the "proper" choice of a hyper-structure.(fragment of text)
Twórcy
autor
- University of Szczecin, Poland
Bibliografia
- Anderson, B. D. O., Moore, J. B. (1984), Optimal Filtering, PWN Warszawa.
- Athans, M. (1974), The Importance of Kalman Filtering Methods for Economic Systems, Annals of Economic and Social Measurement, no 3.
- Brännäs, K. (1981), On the Estimation of Time-Varying Parameters for Forecasting and Control, in: K. Brännäs, H. Stenlund, i A.Westlund (ed.), Econometrics and Stochastic Control in Macro-Economic Planning, Almquist&Wicksell, Stockholm.
- Brännäs, K., Westlund, A. (1981), A Robustness Analysis of Kalman Filtering for Estimation of Interdependent Systems, in: K. Brännäs, J. A. Eklöf, H. Stenlund, A. Westlund (ed.), Econometrics and Stochastic Control in Macro-Economic Planing, Almquist & Wickell, Stockholm.
- Grzesiak, S. (1995), Równania filtru Kalmana w modelowaniu ekonometrycznym (Kalman Filter Equations in Econometric Modelling), Przegląd Statystyczny (Sta-tistical Survey), no. 1.
- Grzesiak, S. (1997), O wyznaczaniu wartości początkowych algorytmu filtru Kalmana (On Determining the Initial Values for Kalman Filter Algorithm), Przegląd Statystyczny (Statistical Survey), no. 1.
- Grzesiak, S. (1999), Problem wygładzania w filtracji kalmanowskiej (The Problem of Smoothing in Kalman Filtration), Przegląd Statystyczny (Statistical Survey), no. 4.
- Haas, P. (1983), Zustands- und Parameterschätzungen in ökonometrischen Modellen mit Hilfe von linearen Filter-Methoden, Verlag A. Hain, Königsstein/Taunus.
- Haas, P., Hild, C. (1982), Linear Filter Methods: An Application to a Stock Production Model, in: W. Eichhorn, R.Henn, K.Neumann i R. Shephard (ed.), Economic Theory of Natural Resources, Physica Verlag, Würzburg-Wien.
- Jazwinski, A. H. (1970), Stochastic Processes and Filtering Theory, Academic Press New York, London.
- Klein, L. R. (1950), Economic Fluctuations in the United States, 1921-1941, Cowles Commission Monograph 11, John Wiley & Sons, New York.
- McWhorter, A., Narasimhan, G., Simonds, R. (1977), An Empirical Examination of the Predictive Performance of an Econometric Model with Random Coefficients, International Statistical Review, vol. 45.
- McWhorter, A., Spivey, W. A., Wrobleski, W. J., A (1976), Sensitivity Analysis of Varying Parameter Econometric Models, International Statistical Review, vol. 44.
- Otter, P. W. (1978), The Discrete Kalman Filter Applied to Linear Regression Models: Statistical Considerations and an Application, Statistica Neerlandica, 32.
- Sage, A., Husa, G. (1969), Adaptive Filtering with unknown Prior Statistic, Proc. 10. Joint Automatic Control Conference, Boulder, Col., 1969.
- Schaps, J. (1982), Zur Verwendung des Kalman-Ansatzes für eine Verbesserung der Prognosegüte ökonometrischer Modelle, Dissertation, Universität Göttingen.
- Szeto, M. W. (1973), Estimation of the Volatility of Securities in the Stock Market by Kalman Filtering Techniques, Proceedings of the 14, Joint Automatic Control Conference, Columbus, Ohio.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171296637