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An auxiliary particle filter for nonlinear dynamic equilibrium models

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  • Yang, Yuan
  • Wang, Lu

Abstract

We develop a particle filter algorithm to approximate the likelihood function of nonlinear dynamic stochastic general equilibrium models. The new algorithm reduces the Monte Carlo variance of likelihood approximation and accelerates the convergence of posterior sampler. It requires much fewer particles to achieve comparable results as currently available particle filters. We illustrate our algorithm in Bayesian estimation of a new Keynesian macroeconomic model.

Suggested Citation

  • Yang, Yuan & Wang, Lu, 2016. "An auxiliary particle filter for nonlinear dynamic equilibrium models," Economics Letters, Elsevier, vol. 144(C), pages 112-114.
    • Handle: RePEc:eee:ecolet:v:144:y:2016:i:c:p:112-114
    DOI: 10.1016/j.econlet.2016.04.020
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    References listed on IDEAS

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    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.
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    3. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    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. 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.
    6. Martin M. Andreasen, 2013. "Non‐Linear Dsge Models And The Central Difference Kalman Filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(6), pages 929-955, September.
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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
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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