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An Improved Auxiliary Particle Filter for Nonlinear Dynamic Equilibrium Models

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  • Yang, Yuan
  • Wang, Lu

Abstract

We develop a procedure that efficiently computes likelihood function in nonlinear dynamic stochastic general equilibrium (DSGE) models. The procedure employs linearization to the measurement equation and delivers competitive results as the fully-adapted particle filter. The resulting likelihood approximation has much lower Monte Carlo variance than currently available particle filters, which greatly enhances the likelihood-based inference of DSGE models. We illustrate our procedure in applications to Bayesian estimation of a new Keynesian macroeconomic model.

Suggested Citation

  • Yang, Yuan & Wang, Lu, 2015. "An Improved Auxiliary Particle Filter for Nonlinear Dynamic Equilibrium Models," Dynare Working Papers 47, CEPREMAP.
    • Handle: RePEc:cpm:dynare:047
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    References listed on IDEAS

    as
    1. Amisano, Gianni & Tristani, Oreste, 2010. "Euro area inflation persistence in an estimated nonlinear DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1837-1858, October.
    2. Hall, Jamie & Pitt, Michael K. & Kohn, Robert, 2014. "Bayesian inference for nonlinear structural time series models," Journal of Econometrics, Elsevier, vol. 179(2), pages 99-111.
    3. Andreasen, Martin M., 2011. "Non-linear DSGE models and the optimized central difference particle filter," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1671-1695, October.
    4. 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.
    5. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    6. Flury, Thomas & Shephard, Neil, 2011. "Bayesian Inference Based Only On Simulated Likelihood: Particle Filter Analysis Of Dynamic Economic Models," Econometric Theory, Cambridge University Press, vol. 27(5), pages 933-956, October.
    7. Roman Liesenfeld & Guilherme V. Moura & Jean-François Richard & Hariharan Dharmarajan, 2013. "Efficient Likelihood Evaluation of State-Space Representations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(2), pages 538-567.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    DSGE model; auxiliary particle filter; Bayesian estimation;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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