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Posterior Predictive Analysis for Evaluating DSGE Models

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  • Jon Faust
  • Abhishek Gupta

Abstract

While dynamic stochastic general equilibrium (DSGE) models for monetary policy analysis have come a long way, there is considerable difference of opinion over the role these models should play in the policy process. The paper develops three main points about assessing the value of these models. First, we document that DSGE models continue to have aspects of crude approximation and omission. This motivates the need for tools to reveal the strengths and weaknesses of the models--both to direct development efforts and to inform how best to use the current flawed models. Second, posterior predictive analysis provides a useful and economical tool for finding and communicating strengths and weaknesses. In particular, we adapt a form of discrepancy analysis as proposed by Gelman, et al. (1996). Third, we provide a nonstandard defense of posterior predictive analysis in the DSGE context against long-standing objections. We use the iconic Smets-Wouters model for illustrative purposes, showing a number of heretofore unrecognized properties that may be important from a policymaking perspective.

Suggested Citation

  • Jon Faust & Abhishek Gupta, 2012. "Posterior Predictive Analysis for Evaluating DSGE Models," NBER Working Papers 17906, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17906
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    Cited by:

    1. Mumtaz, Haroon & Theodoridis, Konstantinos, 2020. "Fiscal policy shocks and stock prices in the United States," European Economic Review, Elsevier, vol. 129(C).
    2. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    3. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.),Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    4. Michal Andrle & Jan Bruha & Serhat Solmaz, 2016. "On the Sources of Business Cycles: Implications for DSGE Models," Working Papers 2016/03, Czech National Bank.
    5. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    6. Gupta, Abhishek, 2010. "A Forecasting Metric for Evaluating DSGE Models for Policy Analysis," MPRA Paper 26718, University Library of Munich, Germany.
    7. Eric M. Leeper & Nora Traum & Todd B. Walker, 2015. "Clearing Up the Fiscal Multiplier Morass: Prior and Posterior Analysis," NBER Working Papers 21433, National Bureau of Economic Research, Inc.
    8. Fabio Canova & Filippo Ferroni & Christian Matthes, 2014. "Choosing The Variables To Estimate Singular Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1099-1117, November.
    9. Eric M. Leeper & Nora Traum & Todd B. Walker, 2017. "Clearing Up the Fiscal Multiplier Morass," American Economic Review, American Economic Association, vol. 107(8), pages 2409-2454, August.
    10. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers CWP41/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Brede, Maren, 2018. "Real exchange rate dynamics in New-Keynesian models – The Balassa-Samuelson effect revisited," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181539, Verein für Socialpolitik / German Economic Association.
    12. Jon Faust, 2012. "DSGE Models: I Smell a Rat (and It Smells Good)," International Journal of Central Banking, International Journal of Central Banking, vol. 8(1), pages 53-64, March.
    13. Abhishek Gupta, 2016. "A Forecasting Metric for Evaluating DSGE Models for Policy Analysis," International Journal of Central Banking, International Journal of Central Banking, vol. 12(1), pages 33-65, March.
    14. Alexander W. Richter & Nathaniel Throckmorton, 2016. "Are nonlinear methods necessary at the zero lower bound?," Working Papers 1606, Federal Reserve Bank of Dallas.
    15. Gelain, Paolo & Manganelli, Simone, 2020. "Monetary policy with judgment," Working Paper Series 2404, European Central Bank.
    16. Rieth, Malte, 2017. "Capital taxation and government debt policy with public discounting," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 1-20.
    17. Sylvain Leduc & Zheng Liu, 2020. "The Weak Job Recovery in a Macro Model of Search and Recruiting Intensity," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 310-343, January.
    18. Michal Andrle & Jaromir Benes, 2013. "System Priors; Formulating Priors about DSGE Models' Properties," IMF Working Papers 13/257, International Monetary Fund.

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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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