IDEAS home Printed from https://ideas.repec.org/p/fsu/wpaper/wp2021_10_01.html
   My bibliography  Save this paper

Testing for Spurious Dynamics in Structural Models with Applications to Monetary Policy

Author

Listed:
  • Mikhail Dmitriev

    (Department of Economics, Florida State University)

  • Manoj Atolia

    (Department of Economics, Florida State University)

Abstract

We propose a universal and straightforward test for validating assumptions in the structural models. Structural models impose a causal structure, take data as an input, and then produce exact structural parameters. We simulate the new data while breaking the original causal structure. We then feed the model the simulated data and then see whether it produces different results. If its conclusions are the same, then the models’ implications are not sensitive to the underlying data, and the model fails the test. We then apply our test to the models analyzing monetary policy. We find out that simple SVARs successfully pass the test and can be used to identify monetary policy effects. On the other hand, DSGE models estimated via full-information methods such as Smets and Wouters (2007) fail the test and potentially force their conclusions on the data.

Suggested Citation

  • Mikhail Dmitriev & Manoj Atolia, 2021. "Testing for Spurious Dynamics in Structural Models with Applications to Monetary Policy," Working Papers wp2021_10_01, Department of Economics, Florida State University.
    • Handle: RePEc:fsu:wpaper:wp2021_10_01
    as

    Download full text from publisher

    File URL: https://coss.fsu.edu/econpapers/wpaper/wp2021_10_01.pdf
    File Function: First version, 2021-10
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2009. "New Keynesian Models: Not Yet Useful for Policy Analysis," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 242-266, January.
    2. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106, National Bureau of Economic Research, Inc.
    3. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2004. "A Critique of Structural VARs Using Real Business Cycle Theory," Levine's Bibliography 122247000000000518, UCLA Department of Economics.
    4. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    5. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
    6. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    7. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Forni, Lorenzo & Monteforte, Libero & Sessa, Luca, 2009. "The general equilibrium effects of fiscal policy: Estimates for the Euro area," Journal of Public Economics, Elsevier, vol. 93(3-4), pages 559-585, April.
    2. Martial Dupaigne & Patrick Feve & Julien Matheron, 2007. "Technology Shocks, Non-stationary Hours and DSVAR," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 10(2), pages 238-255, April.
    3. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    4. Patrick Fève & Alain Guay, 2009. "The Response of Hours to a Technology Shock: A Two‐Step Structural VAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(5), pages 987-1013, August.
    5. Mertens, Elmar, 2012. "Are spectral estimators useful for long-run restrictions in SVARs?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1831-1844.
    6. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    7. Anna Mikusheva, 2014. "Estimation of dynamic stochastic general equilibrium models (in Russian)," Quantile, Quantile, issue 12, pages 1-21, February.
    8. Enders, Zeno & Müller, Gernot J., 2009. "On the international transmission of technology shocks," Journal of International Economics, Elsevier, vol. 78(1), pages 45-59, June.
    9. Patrick Fève & Alain Guay, 2010. "Identification of Technology Shocks in Structural Vars," Economic Journal, Royal Economic Society, vol. 120(549), pages 1284-1318, December.
    10. Dieppe, Alistair & Francis, Neville & Kindberg-Hanlon, Gene, 2021. "The identification of dominant macroeconomic drivers: coping with confounding shocks," Working Paper Series 2534, European Central Bank.
    11. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    12. Alexander Mihailov & Giovanni Razzu & Zhe Wang, 2019. "Heterogeneous effects of single monetary policy on unemployment rates in the largest EMU economies," Economics Discussion Papers em-dp2019-07, Department of Economics, University of Reading.
    13. Hussain, Syed M. & Liu, Lin, 2016. "A note on the Cogley–Nason–Sims approach," Economics Letters, Elsevier, vol. 146(C), pages 77-81.
    14. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    16. Rupert, Peter & Šustek, Roman, 2019. "On the mechanics of New-Keynesian models," Journal of Monetary Economics, Elsevier, vol. 102(C), pages 53-69.
    17. Alok Johri & Muhebullah Karimzada, 2021. "Learning efficiency shocks, knowledge capital and the business cycle: A Bayesian evaluation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(3), pages 1314-1360, November.
    18. Khan, Hashmat & Phaneuf, Louis & Victor, Jean Gardy, 2020. "Rules-based monetary policy and the threat of indeterminacy when trend inflation is low," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 317-333.
    19. Igor Vetlov & Tibor Hlédik & Magnus Jonsson & Henrik Kucsera & Massimiliano Pisani, 2011. "Potential Output in DSGE Models," Bank of Lithuania Working Paper Series 9, Bank of Lithuania.
    20. Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2016. "Exploiting the monthly data flow in structural forecasting," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 201-215.

    More about this item

    Keywords

    VARs; SVARs; DSGE; monetary policy;
    All these keywords.

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fsu:wpaper:wp2021_10_01. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Luke Rodgers (email available below). General contact details of provider: https://edirc.repec.org/data/defsuus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.