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How Good are Out of Sample Forecasting Tests on DSGE Models?

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  • Patrick Minford
  • Yongdeng Xu
  • Peng Zhou

Abstract

Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check (a) the specification and (b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of specification will almost definitely also improve on VAR forecasts. Copyright Società Italiana degli Economisti (Italian Economic Association) 2015

Suggested Citation

  • Patrick Minford & Yongdeng Xu & Peng Zhou, 2015. "How Good are Out of Sample Forecasting Tests on DSGE Models?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(3), pages 333-351, November.
  • Handle: RePEc:spr:italej:v:1:y:2015:i:3:p:333-351
    DOI: 10.1007/s40797-015-0020-9
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    Cited by:

    1. Patrick Minford & Yi Wang & Peng Zhou, 2020. "Resolving the public-sector wage premium puzzle by indirect inference," Applied Economics, Taylor & Francis Journals, vol. 52(7), pages 726-741, February.
    2. Chou, Jenyu & Easaw, Joshy & Minford, Patrick, 2023. "Does inattentiveness matter for DSGE modeling? An empirical investigation," Economic Modelling, Elsevier, vol. 118(C).
    3. Meenagh, David & Minford, Patrick & Wickens, Michael, 2021. "Estimating macro models and the potentially misleading nature of Bayesian estimation," Cardiff Economics Working Papers E2021/22, Cardiff University, Cardiff Business School, Economics Section.
    4. David Meenagh & Patrick Minford & Michael Wickens & Yongdeng Xu, 2019. "Testing DSGE Models by Indirect Inference: a Survey of Recent Findings," Open Economies Review, Springer, vol. 30(3), pages 593-620, July.
    5. Loberto, Michele & Perricone, Chiara, 2017. "Does trend inflation make a difference?," Economic Modelling, Elsevier, vol. 61(C), pages 351-375.

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    More about this item

    Keywords

    Out of sample forecasts; DSGE; VAR; Specification tests; Indirect inference; Forecast performance; E10; E17;
    All these keywords.

    JEL classification:

    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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