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Posterior Predictive Analysis for Evaluating DSGE Models

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  • Faust, Jon
  • Gupta, Abhishek

Abstract

In this paper, we develop and apply certain tools to evaluate the strengths and weaknesses of dynamic stochastic general equilibrium (DSGE) models. In particular, this paper makes three contributions: One, it argues the need for such tools to evaluate the usefulness of the these models; two, it defines these tools which take the form of prior and particularly posterior predictive analysis and provides illustrations; and three, it provides a justification for the use of these tools in the DSGE context in defense against the standard criticisms for the use of these tools.

Suggested Citation

  • Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:26721
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    3. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    4. Gupta, Abhishek, 2010. "A Forecasting Metric for Evaluating DSGE Models for Policy Analysis," MPRA Paper 26718, University Library of Munich, Germany.
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    Cited by:

    1. 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.
    2. 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.
    3. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    4. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, Elsevier.
    5. repec:aea:aecrev:v:107:y:2017:i:8:p:2409-54 is not listed on IDEAS
    6. Michal Andrle & Jan Bruha & Serhat Solmaz, 2016. "On the Sources of Business Cycles: Implications for DSGE Models," Working Papers 2016/03, Czech National Bank, Research Department.
    7. Richter, Alexander & Throckmorton, Nathaniel, 2016. "Are nonlinear methods necessary at the zero lower bound?," Working Papers 1606, Federal Reserve Bank of Dallas.
    8. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    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. Gupta, Abhishek, 2010. "A Forecasting Metric for Evaluating DSGE Models for Policy Analysis," MPRA Paper 26718, University Library of Munich, Germany.
    11. 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.
    12. Malte Rieth, 2017. "Capital Taxation and Government Debt Policy with Public Discounting," Discussion Papers of DIW Berlin 1697, DIW Berlin, German Institute for Economic Research.
    13. Michal Andrle & Jaromir Benes, 2013. "System Priors; Formulating Priors about DSGE Models' Properties," IMF Working Papers 13/257, International Monetary Fund.
    14. 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.
    15. repec:eee:dyncon:v:85:y:2017:i:c:p:1-20 is not listed on IDEAS
    16. 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.

    More about this item

    Keywords

    Prior and posterior predictive analysis; DSGE Model Evaluation; Monetary Policy.;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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