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

  • Martin Møller Andreasen

    ()

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

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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File URL: ftp://ftp.econ.au.dk/creates/rp/08/rp08_33.pdf
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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
Contact details of provider: Web page: http://www.econ.au.dk/afn/

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  1. Sungbae An & Frank Schorfheide, 2006. "Bayesian analysis of DSGE models," Working Papers 06-5, Federal Reserve Bank of Philadelphia.
  2. 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.
  3. Bekaert, Geert & Cho, Seonghoon & Moreno Ibáñez, Antonio, 2006. "New-Keynesian Macroeconomics and the Term Structure," CEPR Discussion Papers 5956, C.E.P.R. Discussion Papers.
  4. Altig, David & Christiano, Lawrence & Eichenbaum, Martin & Lindé, Jesper, 2004. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Working Paper Series 176, Sveriges Riksbank (Central Bank of Sweden).
  5. 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.
  6. 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.
  7. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper 0107, Federal Reserve Bank of Cleveland.
  8. 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.
  9. Martin Andreasen, 2010. "How to Maximize the Likelihood Function for a DSGE Model," Computational Economics, Society for Computational Economics, vol. 35(2), pages 127-154, February.
  10. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Manuel Santos, 2005. "Convergence Properties of the Likelihood of Computed Dynamic Models," Levine's Bibliography 122247000000000822, UCLA Department of Economics.
  11. Giorgio Primiceri & Alejandro Justiniano, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," 2006 Meeting Papers 353, Society for Economic Dynamics.
  12. 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.
  13. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2005. "Online Appendix to "Firm-Specific Capital, Nominal Rigidities and the Business Cycle"," Technical Appendices 09-191, Review of Economic Dynamics.
  14. 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.
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