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A low dimensional Kalman filter for systems with lagged states in the measurement equation

Author

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  • Nimark, Kristoffer P.

Abstract

This note describes how the Kalman filter and the Kalman smoother can be modified to allow for the vector of observables to be a function of lagged state variables without increasing the dimension of the state vector in the filter.

Suggested Citation

  • Nimark, Kristoffer P., 2015. "A low dimensional Kalman filter for systems with lagged states in the measurement equation," Economics Letters, Elsevier, vol. 127(C), pages 10-13.
  • Handle: RePEc:eee:ecolet:v:127:y:2015:i:c:p:10-13
    DOI: 10.1016/j.econlet.2014.12.016
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    References listed on IDEAS

    as
    1. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
    2. Kristoffer Nimark, 2009. "Speculative dynamics in the term structure of interest rates," Economics Working Papers 1194, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2012.
    3. Hang Qian, 2014. "A Flexible State Space Model And Its Applications," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 79-88, March.
    Full references (including those not matched with items on IDEAS)

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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Seeking feedback: Towards a New Keynesian Theory of the Price Level
      by bankunderground in Bank Underground on 2015-07-13 12:30:00

    Citations

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    Cited by:

    1. Pagan, Adrian & Robinson, Tim, 2022. "Excess shocks can limit the economic interpretation," European Economic Review, Elsevier, vol. 145(C).
    2. Lerby Ergun & Andreas Uthemann, 2020. "Strategic Uncertainty in Financial Markets: Evidence from a Consensus Pricing Service," Staff Working Papers 20-55, Bank of Canada.
    3. Ergun, Lerby & Uthemann, Andreas, 2020. "Higher-order uncertainty in financial markets: evidence from a consensus pricing service," LSE Research Online Documents on Economics 118893, London School of Economics and Political Science, LSE Library.
    4. Hauber, Philipp & Schumacher, Christian & Zhang, Jiachun, 2019. "A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing," Discussion Papers 15/2019, Deutsche Bundesbank.
    5. Adrian Pagan & Tim Robinson, 2019. "Implications of Partial Information for Applied Macroeconomic Modelling," Melbourne Institute Working Paper Series wp2019n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    6. Adrian Pagan & Tim Robinson, 2020. "Too many shocks spoil the interpretation," CAMA Working Papers 2020-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Kristoffer Nimark, 2007. "Dynamic higher order expectations," Economics Working Papers 1118, Department of Economics and Business, Universitat Pompeu Fabra, revised Mar 2011.
    8. Kurz, Malte S., 2018. "A note on low-dimensional Kalman smoothers for systems with lagged states in the measurement equation," Economics Letters, Elsevier, vol. 168(C), pages 42-45.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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