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A flexible finite-horizon alternative to long-run restrictions with an application to technology shock

  • Neville Francis
  • Michael T. Owyang
  • Jennifer E. Roush
  • Riccardo DiCecio

Recent studies using long-run restrictions question the validity of the technology-driven real business cycle hypothesis. We propose an alternative identi cation 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. Unlike its long-run restriction counterpart, when our Max Share identification technique is applied to U.S. data it delivers the robust result that hours worked responds negatively to positive technology shocks. ; Earlier title: A flexible finite-horizon identification of technology shocks

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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: 2010
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Handle: RePEc:fip:fedlwp:2005-024
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  1. Christopher A. Sims & Tao Zha, 1995. "Error bands for impulse responses," Working Paper 95-6, Federal Reserve Bank of Atlanta.
  2. Neville R. Francis & Michael T. Owyang & Athena T. Theodorou, 2005. "What Explains the Varying Monetary Response to Technology Shocks in G-7 Countries?," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
  3. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
  4. Jordi Gali, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations," NBER Working Papers 5721, National Bureau of Economic Research, Inc.
  5. Neville Francis & Valerie A. Ramey, 2006. "The Source of Historical Economic Fluctuations: An Analysis Using Long-Run Restrictions," NBER Chapters, in: NBER International Seminar on Macroeconomics 2004, pages 17-73 National Bureau of Economic Research, Inc.
  6. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
  7. 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.
  8. 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.
  9. Mark W. Watson, 1991. "Measures of Fit for Calibrated Models," NBER Technical Working Papers 0102, National Bureau of Economic Research, Inc.
  10. 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(1), pages 7-61, 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. Jon Faust & Eric M. Leeper, 1994. "When do long-run identifying restrictions give reliable results?," Working Paper 94-2, Federal Reserve Bank of Atlanta.
  13. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," Working Paper 96-13, Federal Reserve Bank of Atlanta.
  14. Christopher A. Sims & Harald Uhlig, 1988. "Understanding unit rooters: a helicopter tour," Discussion Paper / Institute for Empirical Macroeconomics 4, Federal Reserve Bank of Minneapolis.
  15. John Fernald, 2004. "Trend Breaks, Long Run Restrictions, and the Contractionary Effects of Technology Shocks," 2004 Meeting Papers 477, Society for Economic Dynamics.
  16. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005. "Can Long-Run Restrictions Identify Technology Shocks?," Journal of the European Economic Association, MIT Press, vol. 3(6), pages 1237-1278, December.
  17. Sims, Christopher A., 1988. "Bayesian skepticism on unit root econometrics," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 463-474.
  18. 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.).
  19. 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.
  20. repec:dgr:kubcen:199928 is not listed on IDEAS
  21. John Shea, 1998. "What Do Technology Shocks Do?," NBER Working Papers 6632, National Bureau of Economic Research, Inc.
  22. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
  23. Uhlig, H.F.H.V.S., 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," Discussion Paper 1999-28, Tilburg University, Center for Economic Research.
  24. Christopher A. Sims, 1989. "Modeling trends," Discussion Paper / Institute for Empirical Macroeconomics 22, Federal Reserve Bank of Minneapolis.
  25. 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.).
  26. 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.
  27. Neville Francis & Valerie A. Ramey, 2002. "Is the Technology-Driven Real Business Cycle Hypothesis Dead?," NBER Working Papers 8726, National Bureau of Economic Research, Inc.
  28. 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(1), pages 63-82, January.
  29. 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.
  30. 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.
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