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Restricted Kalman filtering revisited

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  • Pizzinga, Adrian
  • Fernandes, Cristiano
  • Contreras, Sergio

Abstract

We propose a more compact and general derivation of results concerning the estimation of linear state space models with linear restrictions in the state vector. The resulting methodological contributions are that the restricted Kalman filtering is valid regardless of the type of linear restriction being considered, and that linear restrictions can be carried out by any type of state smoothing.

Suggested Citation

  • Pizzinga, Adrian & Fernandes, Cristiano & Contreras, Sergio, 2008. "Restricted Kalman filtering revisited," Journal of Econometrics, Elsevier, vol. 144(2), pages 428-429, June.
  • Handle: RePEc:eee:econom:v:144:y:2008:i:2:p:428-429
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    References listed on IDEAS

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    1. Doran, Howard E. & Rambaldi, Alicia N., 1997. "Applying linear time-varying constraints to econometric models: With an application to demand systems," Journal of Econometrics, Elsevier, vol. 79(1), pages 83-95, July.
    2. Doran, Howard E, 1992. "Constraining Kalman Filter and Smoothing Estimates to Satisfy Time-Varying Restrictions," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 568-572, August.
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    Cited by:

    1. Adrian Pizzinga, 2010. "Constrained Kalman Filtering: Additional Results," International Statistical Review, International Statistical Institute, vol. 78(2), pages 189-208, August.
    2. Pizzinga, Adrian, 2009. "Further investigation into restricted Kalman filtering," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 264-269, January.
    3. A. Peyrache & A. N. Rambaldi, 2012. "A State-Space Stochastic Frontier Panel Data Model," CEPA Working Papers Series WP012012, School of Economics, University of Queensland, Australia.

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