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

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Listed author(s):
  • 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.

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Paper provided by Swiss National Bank, Study Center Gerzensee in its series Working Papers with number 08.01.

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Length: 43 pages
Date of creation: Mar 2008
Handle: RePEc:szg:worpap:0801
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  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. 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. 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. Jordi Gali Garreta & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations; How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
  9. 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, 08.
  10. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, 01.
  11. 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.
  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. Jordi Gali Garreta & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations; How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
  14. 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.
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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.

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