IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

Technology Shocks, Non-stationary Hours and DSVAR

  • Martial Dupaigne

    (University of Western Brittany)

  • Patrick Feve

    (Universite de Toulouse)

  • Julien Matheron

    (Banque de France)

Structural Vector Autoregressions with a differenced specification of hours (DSVAR) suggest that productivity shocks identified using long--run restrictions lead to a persistent and significant decline in hours worked. This evidence calls into question standard business cycle models in which a positive technology shock leads to a rise in hours. In this paper we argue that such a conclusion is unwarranted because model's data and actual data are not treated symmetrically. To illustrate this problem, we estimate and test a flexible-price DSGE model with non-stationary hours using Indirect Inference on impulse responses of hours and output after technology and non-technology shocks. We find that, once augmented with a moderate amount of real frictions, the model can mimic well impulse responses obtained form a DSVAR on actual data. Using this model as a data generating process, we show that our estimation method is less subject to bias than a method that would directly compare theoretical responses with responses from the DSVAR. (Copyright: Elsevier)

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: Access to full texts is restricted to ScienceDirect subscribers and institutional members. See for details.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier for the Society for Economic Dynamics in its journal Review of Economic Dynamics.

Volume (Year): 10 (2007)
Issue (Month): 2 (April)
Pages: 238-255

in new window

Handle: RePEc:red:issued:05-128
Contact details of provider: Postal:
Marina Azzimonti, Department of Economics, Stonybrook University, 10 Nicolls Road, Stonybrook NY 11790 USA

Web page:

More information through EDIRC

Order Information: Web: Email:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Robert E. Hall, 1997. "Macroeconomic Fluctuations and the Allocation of Time," NBER Working Papers 5933, National Bureau of Economic Research, Inc.
  2. Hafedh Bouakez & Takashi Kano, 2005. "Learning-by-Doing or Habit Formation?," Staff Working Papers 05-15, Bank of Canada.
  3. 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.
  4. Jon Faust & Eric M. Leeper, 1994. "When do long-run identifying restrictions give reliable results?," International Finance Discussion Papers 462, Board of Governors of the Federal Reserve System (U.S.).
  5. 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.).
  6. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005. "Can Long-Run Restrictions Identify Technology Shocks?," Journal of the European Economic Association, MIT Press, vol. 3(6), pages 1237-1278, December.
  7. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper Series WP-01-08, Federal Reserve Bank of Chicago.
  8. 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.
  9. Timothy Cogley & James M. Nason, 1993. "Output dynamics in real business cycle models," Working Papers in Applied Economic Theory 93-10, Federal Reserve Bank of San Francisco.
  10. Altig, David & Christiano, Lawrence & Eichenbaum, Martin & Lindé, Jesper, 2004. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Working Paper Series 176, Sveriges Riksbank (Central Bank of Sweden).
  11. 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.
  12. 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.
  13. Hansen, Gary D., 1997. "Technical progress and aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1005-1023, June.
  14. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
  15. 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.
  16. Jordi Gali Garreta & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations; How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
  17. Chang, Yongsung & Doh, Taeyoung & Schorfheide, Frank, 2005. "Non-stationary Hours in a DSGE Model," CEPR Discussion Papers 5232, C.E.P.R. Discussion Papers.
  18. 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.
  19. 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.
  20. Martin S. Eichenbaum & Lars Peter Hansen & Kenneth J. Singleton, 1988. "A Time Series Analysis of Representative Agent Models of Consumption and Leisure Choice Under Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 103(1), pages 51-78.
  21. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
  22. Christopher A. Sims, 1989. "Models and Their Uses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 489-494.
  23. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2004. "A Critique of Structural VARs Using Real Business Cycle Theory," Levine's Bibliography 122247000000000518, UCLA Department of Economics.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:red:issued:05-128. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christian Zimmermann)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.