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Estimating DSGE Models: Recent Advances and Future Challenges

Author

Listed:
  • Jesús Fernández-Villaverde

    (Department of Economics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA)

  • Pablo A. Guerrón-Quintana

    (Department of Economics, Boston College, Chestnut Hill, Massachusetts 02467, USA)

Abstract

We review the current state of the estimation of dynamic stochastic general equilibrium (DSGE) models. After introducing a general framework for dealing with DSGE models, the state-space representation, we discuss how to evaluate moments or the likelihood function implied by such a structure. We discuss, in varying degrees of detail, recent advances in the field, such as the tempered particle filter, approximated Bayesian computation, Hamiltonian Monte Carlo, variational inference, and machine learning. These methods show much promise but have not been fully explored by the DSGE community yet. We conclude by outlining three future challenges for this line of research.

Suggested Citation

  • Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2021. "Estimating DSGE Models: Recent Advances and Future Challenges," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 229-252, August.
    • Handle: RePEc:anr:reveco:v:13:y:2021:p:229-252
    DOI: 10.1146/annurev-economics-081020-044812
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    Cited by:

    1. Farkas, Mátyás & Tatar, Balint, 2020. "Bayesian estimation of DSGE models with Hamiltonian Monte Carlo," IMFS Working Paper Series 144, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    2. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Juselius, Mikael, 2025. "Navigating the sea of natural real interest rate estimates," BoF Economics Review 3/2025, Bank of Finland.
    5. Barrie, Mohamed Samba & Jackson, Emerson Abraham, 2022. "Impact of Technological Shock on the Sierra Leone Economy: A Dynamic Stochastic General Equilibrium (DSGE) Approach," MPRA Paper 113636, University Library of Munich, Germany, revised 10 Jun 2022.

    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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