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Estimating the State Vector of Linearized DSGE Models without the Kalman Filter

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  • Robert Kollmann

Abstract

This note presents a simple method for estimating the state vector of linearized DSGE models without using the Kalman filter. The conditional covariance matrix of the state vector is also derived. The method can easily cope with filtered data, and with arbitrary patterns of missing observations.
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Suggested Citation

  • Robert Kollmann, 2013. "Estimating the State Vector of Linearized DSGE Models without the Kalman Filter," Working Papers ECARES ECARES 2013-08, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:eca:wpaper:2013/139176
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    References listed on IDEAS

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    1. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
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    More about this item

    Keywords

    DSGE Models; Kalman Filter; smoothing;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models

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