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Fundamental shock selection in DSGE models

Author

Listed:
  • Filippo Ferroni
  • Stefano Grassi
  • Miguel A. Leon-Ledesma
Abstract
DSGE models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of introducing nonfundamental shocks for the estimation of DSGE model parameters and propose a method to select the structural shocks driving uncertainty. We show that forcing the existence of non-fundamental structural shocks produces a downward bias in the estimated internal persistence of the model. We then show how these distortions can be reduced by allowing the covariance matrix of the structural shocks to be rank deficient using priors for standard deviations whose support includes zero. The method allows us to accurately select fundamental shocks and estimate model parameters with precision. Finally, we revisit the empirical evidence on an industry standard medium-scale DSGE model and find that government, price, and wage markup shocks are non-fundamental.

Suggested Citation

  • Filippo Ferroni & Stefano Grassi & Miguel A. Leon-Ledesma, 2015. "Fundamental shock selection in DSGE models," Studies in Economics 1508, School of Economics, University of Kent.
    • Handle: RePEc:ukc:ukcedp:1508
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    References listed on IDEAS

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    Cited by:

    1. Alexander Falter & Dennis Wesselbaum, 2018. "Correlated shocks in estimated DSGE models," Economics Bulletin, AccessEcon, vol. 38(4), pages 2026-2036.
    2. Inaba, Masaru & Nutahara, Kengo & Shirai, Daichi, 2022. "What drives fluctuations of labor wedge and business cycles? Evidence from Japan," Journal of Macroeconomics, Elsevier, vol. 72(C).
    3. Blouri, Yashar & Ehrlich, Maximilian V., 2020. "On the optimal design of place-based policies: A structural evaluation of EU regional transfers," Journal of International Economics, Elsevier, vol. 125(C).
    4. Den Haan, Wouter J. & Drechsel, Thomas, 2021. "Agnostic Structural Disturbances (ASDs): Detecting and reducing misspecification in empirical macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 258-277.
    5. Juan Paez-Farrell, 2023. "On the unimportance of commitment for monetary policy," Papers 2308.08044, arXiv.org, revised Aug 2023.
    6. repec:wrk:wrkemf:11 is not listed on IDEAS
    7. Galvão, Ana Beatriz, 2017. "Data revisions and DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 215-232.
    8. Mario Carceller del Arco & Jan Willem van den End, 2023. "Robust monetary policy under shock uncertainty," Working Papers 793, DNB.

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    More about this item

    Keywords

    Reduced rank covariance matrix; DSGE models; stochastic dimension search;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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