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A flexible finite-horizon identification of technology shocks

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

Abstract

Recent empirical studies using infinite horizon long-run restrictions question the validity of the technology-driven real business cycle hypothesis. These results have met with their own controversy, stemming from their sensitivity to changes in model specification and the general poor performance of long run restrictions in Monte Carlo experiments. We propose a 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 samples, our identification outperforms its infinite horizon counterpart by producing less biased impulse responses and technology shocks that are more highly correlated with the technology shocks from the underlying model. For U.S. data, we show that the negative hours response is not robust to allowing a greater role for non-technology shocks in the forecast error variance share at a ten year horizon.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 832.

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Date of creation: 2005
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Handle: RePEc:fip:fedgif:832

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Keywords: Econometric models ; Technology - Economic aspects;

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References

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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.
  2. Susanto Basu & John Fernald & Miles Kimball, 2004. "Are technology improvements contractionary?," Working Paper Series WP-04-20, Federal Reserve Bank of Chicago.
  3. Christopher A. Sims & Tao Zha, 1994. "Error Bands for Impulse Responses," Cowles Foundation Discussion Papers 1085, Cowles Foundation for Research in Economics, Yale University.
  4. 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.
  5. Jon Faust & Eric M. Leeper, 1994. "When do long-run identifying restrictions give reliable results?," Working Paper 94-2, Federal Reserve Bank of Atlanta.
  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.
  7. Christopher J. Erceg & Luca Guerrieri, 2004. "Can Long-Run Restrictions Identify Technology Shocks?," Computing in Economics and Finance 2004 3, Society for Computational Economics.
  8. Mark W. Watson, 1991. "Measures of Fit for Calibrated Models," NBER Technical Working Papers 0102, National Bureau of Economic Research, Inc.
  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.
  10. 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.
  11. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
  12. Ramey, Valerie A & Francis, Neville, 2002. "Is The Technology-Driven Real Business Cycle Hypothesis Dead? Shocks and Aggregate Fluctuations Revisted," University of California at San Diego, Economics Working Paper Series qt6x80k3nx, Department of Economics, UC San Diego.
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Cited by:
  1. Patrick Fève & Alain Guay, 2010. "Identification of Technology Shocks in Structural Vars," Economic Journal, Royal Economic Society, vol. 120(549), pages 1284-1318, December.
  2. Hashmat Khan & John Tsoukalas, 2005. "Technology Shocks and UK Business Cycles," Macroeconomics 0512006, EconWPA.
  3. Christopher Otrok & Andre Kurmann, 2011. "News Shocks and the Term Structure of Interest Rates: A Challenge for DSGE Models," 2011 Meeting Papers 426, Society for Economic Dynamics.
  4. André Kurmann & Christopher Otrok, 2012. "News shocks and the slope of the term structure of interest rates," Working Papers 2012-011, Federal Reserve Bank of St. Louis.
  5. Valerie A. Ramey & Neville Francis, 2007. "Measures of Per Capita Hours and their Implications for the Technology-Hours Debate," 2007 Meeting Papers 314, Society for Economic Dynamics.
  6. Kapinos, Pavel, 2011. "Forward-looking monetary policy and anticipated shocks to inflation," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 620-633.
  7. Kilian, Lutz, 2009. "Why Agnostic Sign Restrictions Are Not Enough: Understanding the Dynamics of Oil Market VAR Models," CEPR Discussion Papers 7471, C.E.P.R. Discussion Papers.
  8. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
  9. Tim Berg, 2012. "Did monetary or technology shocks move euro area stock prices?," Empirical Economics, Springer, vol. 43(2), pages 693-722, October.

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