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What happens after a technology shock?

  • Lawrence J. Christiano
  • Martin Eichenbaum
  • Robert Vigfusson

We provide empirical evidence that a positive shock to technology drives up per capita hours worked, consumption, investment, average productivity and output . This evidence contrasts sharply with the results reported in a large and growing literature that argues, on the basis of aggregate data, that per capita hours worked fall after a positive technology shock. We argue that the difference in results primarily reflects specification error in the way that the literature models the low-frequency component of hours worked.

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Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 768.

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Date of creation: 2003
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Handle: RePEc:fip:fedgif:768
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  1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
  2. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," Cowles Foundation Discussion Papers 870, Cowles Foundation for Research in Economics, Yale University.
  3. Susanto Basu & John Fernald & Miles Kimball, 2004. "Are Technology Improvements Contractionary?," NBER Working Papers 10592, National Bureau of Economic Research, Inc.
  4. Lawrence J. Christiano & Martin Eichenbaum, 1990. "Current real business cycle theories and aggregate labor market fluctuations," Working Paper Series, Macroeconomic Issues 90, Federal Reserve Bank of Chicago.
  5. 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.
  6. Elliott, Graham & Jansson, Michael, 2000. "Testing for Unit Roots with Stationary Covariances," University of California at San Diego, Economics Working Paper Series qt47k7z69n, Department of Economics, UC San Diego.
  7. 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.
  8. DeJong, David N, et al, 1992. "Integration versus Trend Stationarity in Time Series," Econometrica, Econometric Society, vol. 60(2), pages 423-33, March.
  9. Galí, Jordi & Gertler, Mark & Lopez-Salido, Jose David, 2002. "Markups, Gaps and the Welfare Costs of Business Fluctuations," CEPR Discussion Papers 3212, C.E.P.R. Discussion Papers.
  10. John Shea, 1998. "What Do Technology Shocks Do?," NBER Working Papers 6632, National Bureau of Economic Research, Inc.
  11. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1998. "Monetary Policy Shocks: What Have We Learned and to What End?," NBER Working Papers 6400, National Bureau of Economic Research, Inc.
  12. Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band Pass Filter," NBER Working Papers 7257, National Bureau of Economic Research, Inc.
    • Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, 05.
  13. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  14. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
  15. Lawrence J. Christiano & Martin Eichenbaum, 1989. "Unit Roots in Real GNP: Do We Know, and Do We Care?," NBER Working Papers 3130, National Bureau of Economic Research, Inc.
  16. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  17. Boldrin, M. & Christiano, L.J. & Fischer, J.D.M., 1996. "Asset Pricing Lessons for Modeling Business Cycles," Papers 268, Banca Italia - Servizio di Studi.
  18. repec:cup:etheor:v:11:y:1995:i:5:p:1148-71 is not listed on IDEAS
  19. Jordi Gali & J. David Lopez-Salido & Javier Valles, 2002. "Technology Shocks and Monetary Policy: Assessing the Fed's Performance," NBER Working Papers 8768, National Bureau of Economic Research, Inc.
  20. Caner, Mehmet & Kilian, Lutz, 2000. "Size Distortions Of Tests Of The Null Hypothesis Of Stationarity: Evidence And Implications For The PPP Debate," CEPR Discussion Papers 2425, C.E.P.R. Discussion Papers.
  21. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-40, September.
  22. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
  23. Martin S. Eichenbaum & Kenneth J. Singleton, 1986. "Do Equilibrium Real Business Cycle Theories Explain Post-War U.S. Business Cycles?," NBER Working Papers 1932, National Bureau of Economic Research, Inc.
  24. Neville Francis & Valerie A. Ramey, 2002. "Is the Technology-Driven Real Business Cycle Hypothesis Dead?," NBER Working Papers 8726, National Bureau of Economic Research, Inc.
  25. Leybourne, S J & McCabe, B P M, 1994. "A Consistent Test for a Unit Root," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 157-66, April.
  26. Jonas D. M. Fisher, 2002. "Technology shocks matter," Working Paper Series WP-02-14, Federal Reserve Bank of Chicago.
  27. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
  28. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
  29. 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.
  30. Lawrence J. Christiano & Lars Ljungqvist, 1987. "Money does Granger-cause output in the bivariate output-money relation," Staff Report 108, Federal Reserve Bank of Minneapolis.
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