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

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

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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File URL: http://pubs.amstat.org/doi/abs/10.1198/jbes.2011.10042
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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. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2006. "Assessing Structural VARs," NBER Working Papers 12353, National Bureau of Economic Research, Inc.
    • 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.
  2. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 638-647, October.
  3. 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.
  4. Pesavento, Elena & Rossi, Barbara, 2004. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," CEPR Discussion Papers 4536, C.E.P.R. Discussion Papers.
  5. Michelle Alexopoulos, 2010. "Read All About it!! What happens following a technology shock?," Working Papers tecipa-391, University of Toronto, Department of Economics.
  6. Yongsung Chang & Jay H. Hong, 2005. "Do technological improvements in the manufacturing sector raise or lower employment?," Working Paper 05-02, Federal Reserve Bank of Richmond.
  7. 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.
  8. Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(04), pages 478-488, September.
  9. 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.
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  11. John Shea, 1999. "What Do Technology Shocks Do?," NBER Chapters, in: NBER Macroeconomics Annual 1998, volume 13, pages 275-322 National Bureau of Economic Research, Inc.
  12. Federico Ravenna, 2005. "Vector Autoregressions and Reduced Form Representations of DSGE Models," 2005 Meeting Papers 841, Society for Economic Dynamics.
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  14. 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.
  15. Jordi Gali & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBS Model Fit Postwar U.S. Data?," NBER Working Papers 10636, National Bureau of Economic Research, Inc.
  16. 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.
  17. 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.
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  19. 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.
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  21. 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.
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