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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, 2007. "Assessing Structural VARs," NBER Chapters, in: NBER Macroeconomics Annual 2006, Volume 21, pages 1-106 National Bureau of Economic Research, Inc.
  2. 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.
  3. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  4. Galí, Jordi, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," CEPR Discussion Papers 1499, C.E.P.R. Discussion Papers.
  5. Yongsung Chang & Jay H. Hong, 2005. "Do technological improvements in the manufacturing sector raise or lower employment?," Working Papers 05-5, Federal Reserve Bank of Philadelphia.
  6. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
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  8. Barbara Rossi & Elena Pesavento, 2006. "Small-sample confidence intervals for multivariate impulse response functions at long horizons," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1135-1155.
  9. Rossi, Barbara & Pesavento, Elena, 2003. "Do Technology Shocks Drive Hours Up or Down? A Little Evidence from an Agnostic Procedure," Working Papers 03-23, Duke University, Department of Economics.
  10. Federico Ravenna, 2005. "Vector Autoregressions and Reduced Form Representations of DSGE Models," 2005 Meeting Papers 841, Society for Economic Dynamics.
  11. 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.
  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.
  13. 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.
  14. 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.
  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. 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. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Staff Report 364, Federal Reserve Bank of Minneapolis.
  18. 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.
  19. Michelle Alexopoulos, 2010. "Read All About it!! What happens following a technology shock?," Working Papers tecipa-391, University of Toronto, Department of Economics.
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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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