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Technology Shocks and Employment: Do We Really Need DSGE Models with a Fall in Hours?

  • Dupaigne, Martial
  • Fève, Patrick
  • Matheron, Julien

The recent empirical literature that uses Structural Vector Autoregressions (SVAR) has shown that productivity shocks identified using long--run restrictions lead to a persistent and significant decline in hours worked. This evidence calls into question standard RBC models in which a positive technology shock leads to a rise in hours. In this paper, we estimate and test a standard RBC model using Indirect Inference on impulse responses of hours worked after technology and non-technology shocks. We find that this model is not rejected by the data and is able to produce impulse responses in SVAR from simulated data similar to impulse responses in SVAR from actual data. Moreover, technology shocks represent the main contribution to the variance of the business cycle component of output under the estimated DSGE model. Our results suggest that we do not necessarily need DSGE models with a fall in hours to reproduce the results deriving from SVAR models.

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Paper provided by Institut d'Économie Industrielle (IDEI), Toulouse in its series IDEI Working Papers with number 349.

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Date of creation: Apr 2005
Date of revision:
Handle: RePEc:ide:wpaper:4482
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  1. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2002. "Business cycle accounting," Working Papers 625, Federal Reserve Bank of Minneapolis.
  2. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2002. "VARs, Common Factors and the Empirical Validation of Equilibrium Business Cycle Models," CEPR Discussion Papers 3701, C.E.P.R. Discussion Papers.
  3. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
  4. Eichenbaum, Martin S & Hansen, Lars Peter & Singleton, Kenneth J, 1988. "A Time Series Analysis of Representative Agent Models of Consumption and Leisure Choice under Uncertainty," The Quarterly Journal of Economics, MIT Press, vol. 103(1), pages 51-78, February.
  5. Hall, Robert E, 1997. "Macroeconomic Fluctuations and the Allocation of Time," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages S223-50, January.
  6. Michele Boldrin & Lawrence J. Christiano & Jonas D. M. Fisher, 2000. "Habit persistence, asset returns and the business cycle," Staff Report 280, Federal Reserve Bank of Minneapolis.
  7. David E. Altig & Lawrence J. Christiano & Martin Eichenbaum & Jesper Linde, 2004. "Firm-specific capital, nominal rigidities, and the business cycle," Working Paper 0416, Federal Reserve Bank of Cleveland.
  8. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
  9. 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.
  10. Beaudry, Paul & Guay, Alain, 1996. "What do interest rates reveal about the functioning of real business cycle models?," Journal of Economic Dynamics and Control, Elsevier, vol. 20(9-10), pages 1661-1682.
  11. Gary Hansen, 2010. "Indivisible Labor and the Business Cycle," Levine's Working Paper Archive 233, David K. Levine.
  12. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2005. "Online Appendix to "Firm-Specific Capital, Nominal Rigidities and the Business Cycle"," Technical Appendices 09-191, Review of Economic Dynamics.
  13. Gary D. Hansen, 1989. "Technical Progress and Aggregate Fluctuations," UCLA Economics Working Papers 546, UCLA Department of Economics.
  14. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
  15. Prescott, Edward C., 1986. "Theory ahead of business-cycle measurement," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 11-44, January.
  16. Christopher J. Erceg & Luca Guerrieri & Christopher J. Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.).
  17. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
  18. 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.
  19. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  20. Julio Rotemberg & Michael Woodford, 1997. "An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 297-361 National Bureau of Economic Research, Inc.
  21. Jordi Galí, 2004. "On The Role of Technology Shocks as a Source of Business Cycles: Some New Evidence," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 372-380, 04/05.
  22. Bover, Olympia, 1991. "Relaxing Intertemporal Separability: A Rational Habits Model of Labor Supply Estimated from Panel Data," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 85-100, January.
  23. Neville Francis & Valerie A. Ramey, 2004. "The Source of Historical Economic Fluctuations: An Analysis using Long-Run Restrictions," NBER Working Papers 10631, National Bureau of Economic Research, Inc.
  24. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
  25. 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.
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