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A flexible finite-horizon identification of technology shocks

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Author Info
Neville Francis
Michael T. Owyang
Jennifer E. Roush

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Abstract

Recent studies using long-run restrictions question the validity of the technology driven real business cycle hypothesis. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long, but finite, horizon. In small-sample Monte Carlo experiments, our identification outperforms standard long-run restrictions by significantly reducing the bias in the short-run impulse responses and raising their estimation precision. When applied to the data, the hours response is shown to be sensitive to the contribution of non-technology shocks to the variance of productivity at long horizons. We conclude that long-run restrictions aimed at isolating the effects of technology shocks on productivity beyond business cycle frequencies do not provide information sufficient to robustly predict short-run movements in labor hours.

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2005-024.

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Date of creation: 2007
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Handle: RePEc:fip:fedlwp:2005-024

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Keywords: Time-series analysis Business cycles

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  1. Harald Uhlig, 2004. "Do Technology Shocks Lead to a Fall in Total Hours Worked?," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 361-371, 04/05. [Downloadable!] (restricted)
  2. Faust, Jon & Leeper, Eric M, 1997. "When Do Long-Run Identifying Restrictions Give Reliable Results?," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 345-53, July.
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  3. Christiano, Lawrence J. & Eichenbaum, Martin, 1990. "Unit roots in real GNP: Do we know, and do we care?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 32, pages 7-61. [Downloadable!] (restricted)
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  4. Christopher A. Sims, 1989. "Modeling trends," Discussion Paper / Institute for Empirical Macroeconomics 22, Federal Reserve Bank of Minneapolis. [Downloadable!]
  5. Uhlig, Harald, 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," CEPR Discussion Papers 2137, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  6. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2005. "A critique of structural VARs using real business cycle theory," Working Papers 631, Federal Reserve Bank of Minneapolis.
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  7. Christopher Erceg & Luca Guerrieri & Christopher Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
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  8. Susanto Basu & John Fernald & Miles Kimball, 2004. "Are technology improvements contractionary?," Working Paper Series WP-04-20, Federal Reserve Bank of Chicago. [Downloadable!]
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  9. Christopher A. Sims & Harald Uhlig, 1988. "Understanding unit rooters: a helicopter tour," Discussion Paper / Institute for Empirical Macroeconomics 4, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  10. Watson, Mark W, 1993. "Measures of Fit for Calibrated Models," Journal of Political Economy, University of Chicago Press, vol. 101(6), pages 1011-41, December. [Downloadable!] (restricted)
  11. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49, pages 207-244, December. [Downloadable!] (restricted)
  12. John Shea, 1998. "What Do Technology Shocks Do?," NBER Working Papers 6632, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  13. Christopher A. Sims, 1988. "Bayesian skepticism on unit root econometrics," Discussion Paper / Institute for Empirical Macroeconomics 3, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  14. John Fernald, 2004. "Trend Breaks, Long Run Restrictions, and the Contractionary Effects of Technology Shocks," 2004 Meeting Papers 477, Society for Economic Dynamics.
  15. Christopher A. Sims & Tao Zha, 1999. "Error Bands for Impulse Responses," Econometrica, Econometric Society, vol. 67(5), pages 1113-1156, September.
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  16. Stock, James H., 1990. "Unit roots in real GNP: Do we know and do we care? : A comment," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 32, pages 63-82. [Downloadable!] (restricted)
  17. Francis, Neville R & Owyang, Michael T & Theodorou, Athena T, 2005. "What Explains the Varying Monetary Response to Technology Shocks in G-7 Countries?," MPRA Paper 834, University Library of Munich, Germany. [Downloadable!]
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  18. 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. [Downloadable!] (restricted)
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  19. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  20. Neville Francis & Valerie A. Ramey, 2004. "The Source of Historical Economic Fluctuations: An Analysis using Long-Run Restrictions," NBER Working Papers 10631, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  21. Blough, Stephen R, 1992. "The Relationship between Power and Level for Generic Unit Root Tests in Finite Samples," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(3), pages 295-308, July-Sept. [Downloadable!] (restricted)
  22. Jon Faust, 1996. "Theoretical confidence level problems with confidence intervals for the spectrum of a time series," International Finance Discussion Papers 575, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  23. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-68, November.
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  24. Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April. [Downloadable!] (restricted)
  25. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  26. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society. [Downloadable!]
  27. 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. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. FÈVE, Patrick & GUAY, Alain, 2006. "Identification of Technology Shocks in Structural VARs," IDEI Working Papers 383, Institut d'Économie Industrielle (IDEI), Toulouse. [Downloadable!]
  2. Neville Francis & Valerie A. Ramey, 2005. "Measures of Per Capita Hours and their Implications for the Technology-Hours Debate," NBER Working Papers 11694, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  3. Hashmat Khan & John Tsoukalas, 2005. "Technology Shocks and UK Business Cycles," Macroeconomics 0512006, EconWPA. [Downloadable!]
  4. Patrick Fève & Alain Guay, 2007. "Identification of Technology Shocks in Structural VARs," Cahiers de recherche 0736, CIRPEE. [Downloadable!]
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