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The Effects of Permanent Technology Shocks on Labor Productivity and Hours in the RBC model

  • Lindé, Jesper

    ()

    (Research Department, Central Bank of Sweden)

Recent work on the effects of permanent technology shocks argue that the basic RBC model cannot account for a negative correlation between hours worked and labor productivity. In this paper, I show that this conjecture is not necessarily correct. In the basic RBC model, I find that hours worked fall and labor productivity rises after a positive permanent technology shock once one allows for the possibility that the process for the permanent technology shock is slightly persistent in growth rates. A more serious limitation of the RBC model is its inability to generate a persistent rise in hours worked after a positive permanent technology shock along with a rise in labor productivity that are in line with what the data suggests. These results call for a reconsideration of the real and nominal frictions and policy response that need to be introduced in the basic RBC model in order to improve the model’s ability to match the data.

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File URL: http://www.riksbank.se/upload/WorkingPapers/WP_161.pdf
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Paper provided by Sveriges Riksbank (Central Bank of Sweden) in its series Working Paper Series with number 161.

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Length: 24 pages
Date of creation: 01 Apr 2004
Date of revision:
Handle: RePEc:hhs:rbnkwp:0161
Contact details of provider: Postal: Sveriges Riksbank, SE-103 37 Stockholm, Sweden
Phone: 08 - 787 00 00
Fax: 08-21 05 31
Web page: http://www.riksbank.com/
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  1. Jonas Fisher, 2004. "Technology Shocks Matter," Econometric Society 2004 North American Winter Meetings 14, Econometric Society.
  2. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  3. Rotemberg, Julio J & Woodford, Michael, 1996. "Real-Business-Cycle Models and the Forecastable Movements in Output, Hours, and Consumption," American Economic Review, American Economic Association, vol. 86(1), pages 71-89, March.
  4. Christopher J. Erceg & Luca Guerrieri, 2004. "Can Long-Run Restrictions Identify Technology Shocks?," Computing in Economics and Finance 2004 3, Society for Computational Economics.
  5. 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.).
  6. Hairault, Jean-Olivier & Langot, Francois & Portier, Franck, 1997. "Time to implement and aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 109-121, November.
  7. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
  8. Gali, J., 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," Working Papers 96-28, C.V. Starr Center for Applied Economics, New York University.
  9. Rodolfo E. Manuelli, 2000. "Technological Change, the Labor Market and the Stock Market," NBER Working Papers 8022, National Bureau of Economic Research, Inc.
  10. 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.
  11. 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.
  12. Gary D. Hansen & Edward C. Prescott, 1992. "Recursive methods for computing equilibria of business cycle models," Discussion Paper / Institute for Empirical Macroeconomics 36, Federal Reserve Bank of Minneapolis.
  13. repec:cup:etheor:v:11:y:1995:i:5:p:1148-71 is not listed on IDEAS
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