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Do SVAR Models Justify Discarding the Technology Shock-Driven Real Business Cycle Hypothesis?

  • Hyeon-seung Huh

    (Yonsei University, Republic of Korea)

  • David Kim

    (University of Sydney, Australia)

This paper investigates the validity of technology shocks as a driving force of U.S. business cycle fluctuations. Using three well-known structural vector autoregression (SVAR) models, we analyze how structural shocks are associated with the variations of output and hours worked at business cycle frequencies. Empirical results reveal that technology shocks remain an important source of cyclical movements in output. Furthermore, a positive technology shock does not lead to a decline in hours worked in contrast to previous studies. Our SVARbased evidence does not support discarding a technology shock-driven business cycle theory.

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Paper provided by Yonsei University, Yonsei Economics Research Institute in its series Working papers with number 2013rwp-59.

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Length: 33pages
Date of creation: Dec 2013
Date of revision:
Handle: RePEc:yon:wpaper:2013rwp-59
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  1. Gonzalo, J. & Ng, S., 1996. "A Systematic Framework for Analyzing the Dynamic Effects of Permanent and Transitory Shocks," Cahiers de recherche 9603, Universite de Montreal, Departement de sciences economiques.
  2. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Staff Report 364, Federal Reserve Bank of Minneapolis.
  3. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," Cowles Foundation Discussion Papers 870, Cowles Foundation for Research in Economics, Yale University.
  4. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2003. "The response of hours to a technology shock: evidence based on direct measures of technology," International Finance Discussion Papers 790, Board of Governors of the Federal Reserve System (U.S.).
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  6. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
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  9. Fisher, Lance A. & Huh, Hyeon-Seung & Summers, Peter M., 2000. "Structural Identification of Permanent Shocks in VEC Models: A Generalization," Journal of Macroeconomics, Elsevier, vol. 22(1), pages 53-68, January.
  10. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2008. "New Keynesian models: not yet useful for policy analysis," Staff Report 409, Federal Reserve Bank of Minneapolis.
  11. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
  12. Chantal Dupasquier & Alain Guay & Pierre St-Amant, 1997. "A Comparison of Alternative Methodologies for Estimating Potential Output and the Output Gap," Working Papers 97-5, Bank of Canada.
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  14. Ufuk Demiroglu & Matthew Salomon, 2002. "Using Time-Series Models to Project Output Over the Medium Term: Technical Paper 2002-1," Working Papers 13983, Congressional Budget Office.
  15. 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.
  16. Cochrane, John H, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, MIT Press, vol. 109(1), pages 241-65, February.
  17. Dupasquier, Chantal & Guay, Alain & St-Amant, Pierre, 1999. "A Survey of Alternative Methodologies for Estimating Potential Output and the Output Gap," Journal of Macroeconomics, Elsevier, vol. 21(3), pages 577-595, July.
  18. Fama, Eugene F., 1992. "Transitory variation in investment and output," Journal of Monetary Economics, Elsevier, vol. 30(3), pages 467-480, December.
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