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Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter

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Author Info

  • Martin Møller Andreasen

    ()
    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

Abstract

This paper shows how non-linear DSGE models with potential non-normal shocks can be estimated by Quasi-Maximum Likelihood based on the Central Difference Kalman Filter (CDKF). The advantage of this estimator is that evaluating the quasi log-likelihood function only takes a fraction of a second. The second contribution of this paper is to derive a new particle filter which we term the Mean Shifted Particle Filter (MSPFb). We show that the MSPFb outperforms the standard Particle Filter by delivering more precise state estimates, and in general the MSPFb has lower Monte Carlo variation in the reported log-likelihood function.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-33.

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Length: 45
Date of creation: 20 Jun 2008
Date of revision:
Handle: RePEc:aah:create:2008-33

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Multivariate Stirling interpolation; Particle filtering; Non-linear DSGE models; Non-normal shocks; Quasi-maximum likelihood;

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References

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  1. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-52, July.
  2. An, Sungbae & Schorfheide, Frank, 2005. "Bayesian Analysis of DSGE Models," CEPR Discussion Papers 5207, C.E.P.R. Discussion Papers.
  3. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
  4. Seonghoon Cho & Antonio Moreno & Geert Bekaert, 2005. "New-Keynesian Macroeconomics and the Term Structure," Faculty Working Papers 04/05, School of Economics and Business Administration, University of Navarra.
  5. Martin Møller Andreasen, 2008. "How to Maximize the Likelihood Function for a DSGE Model," CREATES Research Papers 2008-32, School of Economics and Management, University of Aarhus.
  6. 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.
  7. Godsill, Simon J. & Doucet, Arnaud & West, Mike, 2004. "Monte Carlo Smoothing for Nonlinear Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 156-168, January.
  8. Alejandro Justiniano & Giorgio E. Primiceri, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," NBER Working Papers 12022, National Bureau of Economic Research, Inc.
  9. Ingvar Strid, 2006. "Parallel particle filters for likelihood evaluation in DSGE models: An assessment," Computing in Economics and Finance 2006 395, Society for Computational Economics.
  10. Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez & Manuel Santos, 2004. "Convergence properties of the likelihood of computed dynamic models," Working Paper 2004-27, Federal Reserve Bank of Atlanta.
  11. Martin Møller Andreasen, 2008. "Ensuring the Validity of the Micro Foundation in DSGE Models," CREATES Research Papers 2008-26, School of Economics and Management, University of Aarhus.
  12. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper Series WP-01-08, Federal Reserve Bank of Chicago.
  13. Jinill Kim & Sunghyun Kim & Ernst Schaumburg & Christopher A. Sims, 2003. "Calculating and Using Second Order Accurate Solutions of Discrete Time," Levine's Bibliography 666156000000000284, UCLA Department of Economics.
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Citations

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Cited by:
  1. Martin Møller Andreasen, 2008. "Explaining Macroeconomic and Term Structure Dynamics Jointly in a Non-linear DSGE Model," CREATES Research Papers 2008-43, School of Economics and Management, University of Aarhus.
  2. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.

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