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The effects of permanent technology shocks on hours: Can the RBC-model fit the VAR evidence?

  • Lindé, Jesper

I show that a standard RBC-model can be used to explain why hours per capita decrease in response to a permanent technology shock when hours enter a vector autoregressive (VAR) in first differences and why hours increase when hours enter in levels. There are two parts to my argument. First, empirical evidence suggests that a positive permanent technology shock goes together with a persistent increase in the expected growth rate and the RBC-model predicts this increase in the expected growth rate to have a downward effect on hours worked (and can even result in a sizeable negative response of hours). Second, first-differencing hours in VARs results in a considerable downward bias. Using the estimated parameters for the technology process, I find (i) that the true model response of hours is positive and (ii) that when the VAR methodology is used with finite samples of simulated data then the hours' response is negative (positive) when hours enter the VAR in first differences (levels).

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Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 33 (2009)
Issue (Month): 3 (March)
Pages: 597-613

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Handle: RePEc:eee:dyncon:v:33:y:2009:i:3:p:597-613
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  1. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  2. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2003. "The response of hours to a technology shock: evidence based on direct measures of technology," International Finance Discussion Papers 790, Board of Governors of the Federal Reserve System (U.S.).
  3. Lawrence J. Christiano & Richard M. Todd, 1996. "Time to plan and aggregate fluctuations," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 14-27.
  4. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1148-1171, October.
  5. Susanto Basu & John Fernald & Miles Kimball, 2004. "Are Technology Improvements Contractionary?," NBER Working Papers 10592, National Bureau of Economic Research, Inc.
  6. 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.
  7. Gary Hansen, 2010. "Indivisible Labor and the Business Cycle," Levine's Working Paper Archive 233, David K. Levine.
  8. Beaudry, Paul & Portier, Franck, 2004. "When Can Changes in Expectations Cause Business Cycle Fluctuations in Neo-Classical Settings?," IDEI Working Papers 304, Institut d'Économie Industrielle (IDEI), Toulouse.
  9. Christopher J. Erceg & Luca Guerrieri, 2004. "Can Long-Run Restrictions Identify Technology Shocks?," Computing in Economics and Finance 2004 3, Society for Computational Economics.
  10. 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.
  11. Hairault, Jean-Olivier & Langot, François & Portier, Franck, 1996. "Time to implement and aggregate fluctuations," CEPREMAP Working Papers (Couverture Orange) 9606, CEPREMAP.
  12. Julio J. Rotemberg, 2003. "Stochastic Technical Progress, Smooth Trends, and Nearly Distinct Business Cycles," American Economic Review, American Economic Association, vol. 93(5), pages 1543-1559, December.
  13. Beaudry, Paul & Portier, Franck, 2001. "An Exploration into Pigou's Theory of Cycles," CEPR Discussion Papers 2996, C.E.P.R. Discussion Papers.
  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. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
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