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Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks

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  • Gospodinov, Nikolay
  • Maynard, Alex
  • Pesavento, Elena

Abstract

This paper clarifies the empirical source of the debate on the effect of technology shocks on hours worked. We find that the contrasting conclusions from levels and differenced VAR specifications can be explained by a small, but important, low frequency co-movement between hours worked and labour productivity growth, which is allowed for in the levels specification but is implicitly set to zero in the differenced VAR. Our theoretical analysis shows that, even when the root of hours is very close to one and the low frequency co-movement is quite small, assuming away or explicitly removing the low frequency component can have large implications for the long-run identifying restrictions, giving rise to biases large enough to account for the empirical difference between the two specifications.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 29 (2011)
Issue (Month): 4 ()
Pages: 455-467

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Handle: RePEc:bes:jnlbes:v:29:i:4:y:2011:p:455-467

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  1. Barbara Rossi (Duke) & Elena Pesavento (Emory), 2004. "Small sample confidence intervals for multivariate impulse response functions at long horizons," Econometric Society 2004 North American Winter Meetings 364, Econometric Society.
  2. Michelle Alexopoulos, 2004. "Read All About it: What happens following a technology shock," 2004 Meeting Papers 56, Society for Economic Dynamics.
  3. 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 655-73, September.
  4. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106 National Bureau of Economic Research, Inc.
  5. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
  6. Federico Ravenna, 2006. "Vector autoregressions and reduced form representations of DSGE models," Banco de Espa�a Working Papers 0619, Banco de Espa�a.
  7. Jordi Galí & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations," IMF Working Papers 04/234, International Monetary Fund.
  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. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2008. "Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory?," NBER Working Papers 14430, National Bureau of Economic Research, Inc.
  10. 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.
  11. 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.
  12. Gospodinov, Nikolay, 2010. "Inference in Nearly Nonstationary SVAR Models With Long-Run Identifying Restrictions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 1-12.
  13. John Shea, 1998. "What Do Technology Shocks Do?," NBER Working Papers 6632, National Bureau of Economic Research, Inc.
  14. 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.
  15. Neville Francis & Michael T. Owyang & Athena T. Theodorou, 2003. "The use of long-run restrictions for the identification of technology shocks," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 53-66.
  16. Chang, Yongsung & Hornstein, Andreas & Sarte, Pierre-Daniel, 2009. "On the employment effects of productivity shocks: The role of inventories, demand elasticity, and sticky prices," Journal of Monetary Economics, Elsevier, vol. 56(3), pages 328-343, April.
  17. 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.
  18. Elena Pesavento & Barbara Rossi, 2004. "Do Technology Shocks Drive Hours Up or Down? A Little Evidence From an Agnostic Procedure," Econometrics 0411002, EconWPA.
  19. Yongsung Chang & Jay H. Hong, 2006. "Do Technological Improvements in the Manufacturing Sector Raise or Lower Employment?," American Economic Review, American Economic Association, vol. 96(1), pages 352-368, March.
  20. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2010. "A flexible finite-horizon alternative to long-run restrictions with an application to technology shock," Working Papers 2005-024, Federal Reserve Bank of St. Louis.
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Cited by:
  1. Michelle Alexopoulos & Trevor Tombe, 2010. "Management Matters," Working Papers tecipa-406, University of Toronto, Department of Economics.
  2. Yohei Yamamoto & Pierre Perron, 2013. "Estimating and testing multiple structural changes in linear models using band spectral regressions," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 400-429, October.
  3. Jon Cohen & Michelle Alexopoulos, 2012. "The Media is the Measure: Technical change and employment, 1909-1949," 2012 Meeting Papers 301, Society for Economic Dynamics.
  4. Chaudourne, Jeremy & Fève, Patrick & Guay, Alain, 2014. "Understanding the effect of technology shocks in SVARs with long-run restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 154-172.
  5. Gubler, Matthias & Hertweck, Matthias S., 2013. "Commodity price shocks and the business cycle: Structural evidence for the U.S," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 324-352.
  6. Kilian, Lutz, 2011. "Structural Vector Autoregressions," CEPR Discussion Papers 8515, C.E.P.R. Discussion Papers.
  7. Nikolay Gospodinov & Damba Lkhagvasuren, 2011. "A Moment-Matching Method for Approximating Vector Autoregressive Processes by Finite-State Markov Chains," Working Papers 11005, Concordia University, Department of Economics, revised 16 Dec 2011.
  8. Michelle Alexopoulos & Jon Cohen, 2012. "The Effects of Computer Technologies on the Canadian Economy: Evidence from New Direct Measures," International Productivity Monitor, Centre for the Study of Living Standards, vol. 23, pages 17-32, Spring.

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