IDEAS home Printed from https://ideas.repec.org/p/szg/worpap/0801.html
   My bibliography  Save this paper

Are Spectral Estimators Useful for Implementing Long-Run Restrictions in SVARs?

Author

Listed:
  • Elmar Mertens

    (Study Center Gerzensee and University of Lausanne)

Abstract

No, not really. Responding to lingering concerns about the reliability of SVARs, Christiano et al (NBER Macro Annual, 2006, "CEV") propose to combine OLS estimates of a VAR with a spectral estimate of long-run variance. In principle, this could help alleviate specification problems of SVARs in identifying long-run shocks. But in practice, spectral estimators suffer from small sample biases similar to those from VARs. Moreover, the spectral estimates contain information about serial correlation in VAR residuals and the VAR dynamics must be adjusted accordingly. Otherwise, a naive application of the CEV procedure would misrepresent the data's variance.

Suggested Citation

  • Elmar Mertens, 2008. "Are Spectral Estimators Useful for Implementing Long-Run Restrictions in SVARs?," Working Papers 08.01, Swiss National Bank, Study Center Gerzensee.
    • Handle: RePEc:szg:worpap:0801
    as

    Download full text from publisher

    File URL: http://www.szgerzensee.ch/fileadmin/Dateien_Anwender/Dokumente/working_papers/wp-0801.pdf
    File Function: Full text
    Download Restriction: None
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Li, Lei M., 2005. "Factorization of moving-average spectral densities by state-space representations and stacking," Journal of Multivariate Analysis, Elsevier, vol. 96(2), pages 425-438, October.
    2. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    3. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    4. Domenico Giannone & Lucrezia Reichlin, 2006. "Does information help recovering structural shocks from past observations?," Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 455-465, 04-05.
    5. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    6. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    7. Ravenna, Federico, 2007. "Vector autoregressions and reduced form representations of DSGE models," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2048-2064, October.
    8. Peter C. B. Phillips & Yixiao Sun & Sainan Jin, 2006. "Spectral Density Estimation And Robust Hypothesis Testing Using Steep Origin Kernels Without Truncation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(3), pages 837-894, August.
    9. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    10. Canova, Fabio & de Nicolo, Gianni, 2003. "On the sources of business cycles in the G-7," Journal of International Economics, Elsevier, vol. 59(1), pages 77-100, January.
    11. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    12. Martial Dupaigne & Patrick Feve, 2009. "Technology shocks around the world," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(4), pages 592-607, October.
    13. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
    14. 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.
    15. Patrick J. Kehoe, 2006. "How to Advance Theory with Structural VARs: Use the Sims-Cogley-Nason Approach," NBER Working Papers 12575, National Bureau of Economic Research, Inc.
    16. 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.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christopher J. Gust & Robert J. Vigfusson, 2009. "The power of long-run structural VARs," International Finance Discussion Papers 978, Board of Governors of the Federal Reserve System (U.S.).
    2. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    3. 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.

    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. 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.
    2. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    3. 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.
    4. Laura Bisio & Andrea Faccini, 2010. "Does Cointegration Matter? An Analysis in a RBC Perspective," Working Papers in Public Economics 133, University of Rome La Sapienza, Department of Economics and Law.
    5. Giancarlo Corsetti & Luca Dedola & Sylvain Leduc, 2008. "Productivity, External Balance, and Exchange Rates: Evidence on the Transmission Mechanism among G7 Countries," NBER Chapters, in: NBER International Seminar on Macroeconomics 2006, pages 117-194, National Bureau of Economic Research, Inc.
    6. Nikolay Gospodinov & Alex Maynard & Elena Pesavento, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 455-467, October.
    7. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    8. 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.
    9. Beaudry, Paul & Collard, Fabrice & Portier, Franck, 2011. "Gold rush fever in business cycles," Journal of Monetary Economics, Elsevier, vol. 58(2), pages 84-97, March.
    10. 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.
    11. Malley, Jim & Woitek, Ulrich, 2010. "Technology shocks and aggregate fluctuations in an estimated hybrid RBC model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1214-1232, July.
    12. Sergio Rebelo, 2005. "Real Business Cycle Models: Past, Present, and Future," NBER Working Papers 11401, National Bureau of Economic Research, Inc.
    13. Elmar Mertens, 2005. "Puzzling Comovements between Output and Interest Rates? Multiple Shocks are the Answer," Working Papers 05.05, Swiss National Bank, Study Center Gerzensee.
    14. Patrick Fève & Alain Guay, 2010. "Identification of Technology Shocks in Structural Vars," Economic Journal, Royal Economic Society, vol. 120(549), pages 1284-1318, December.
    15. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    16. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology‐Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    17. Gubler, Matthias & Hertweck, Matthias S., 2013. "Commodity price shocks and the business cycle: Structural evidence for the U.S," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 324-352.
    18. Martial Dupaigne & Patrick Fève, 2010. "Hours Worked and Permanent Technology Shocks in Open Economies," Open Economies Review, Springer, vol. 21(1), pages 69-86, February.
    19. Hikaru Saijo, 2019. "Technology Shocks and Hours Revisited: Evidence from Household Data," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 31, pages 347-362, January.
    20. Dupaigne, M. & Fève, P. & Matheron, J., 2005. "Technology Shock and Employment: Do We Really Need DSGE Models with a Fall in Hours?," Working papers 124, Banque de France.

    More about this item

    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:szg:worpap:0801. 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: library (email available below). General contact details of provider: https://szgerzensee.ch/ .

    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.