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Kalman Filter Model with Qualitative Dependent Variables

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  • Tanizaki, Hisashi

Abstract

In this paper, the time-varying parameter model based on the Kalman filter is combined with the binary choice model. Next, estimation of the unknown parameters is examined without using any distribution. Finally, a money excess demand function is estimated as an application to the problem. Copyright 1993 by MIT Press.

Suggested Citation

  • Tanizaki, Hisashi, 1993. "Kalman Filter Model with Qualitative Dependent Variables," The Review of Economics and Statistics, MIT Press, vol. 75(4), pages 747-752, November.
    • Handle: RePEc:tpr:restat:v:75:y:1993:i:4:p:747-52
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    Cited by:

    1. Du, Rex Yuxing & Kamakura, Wagner A., 2015. "Improving the statistical performance of tracking studies based on repeated cross-sections with primary dynamic factor analysis," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 94-112.
    2. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    3. Alvaro Montenegro, 2005. "Introducción al filtro Kalman," Documentos de Economía 2920, Universidad Javeriana - Bogotá.
    4. Naik, P. & Piersma, N., 2002. "Understanding the role of marketing communications in direct marketing," Econometric Institute Research Papers EI 2002-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Fukasawa, T. & Basawa, I. V., 2002. "Estimation for a class of generalized state-space time series models," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 459-473, December.
    6. Chung‐Hua Shen & David R. Hakes & Kenneth Brown, 1999. "Time‐Varying Response of Monetary Policy to Macroeconomic Conditions," Southern Economic Journal, John Wiley & Sons, vol. 65(3), pages 584-593, January.

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