IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

Trend breaks, long-run restrictions, and the contractionary effects of technology improvements

  • John G. Fernald

Structural vector-autoregressions with long-run restrictions are extraordinarily sensitive to low-frequency correlations. This paper explores this sensitivity analytically and via simulations, focusing on the contentious issue of whether hours worked rise or fall when technology improves. Recent literature finds that when hours per person enter the VAR in levels, hours rise; when they enter in differences, hours fall. However, once we allow for (statistically and economically plausible) trend breaks in productivity, the treatment of hours is relatively unimportant: Hours fall sharply on impact following a technology improvement. The issue is the common high-low-high pattern of hours per capita and productivity growth since World War II. Such low-frequency correlation almost inevitably implies a positive estimated impulse response. The trend breaks control for this correlation. In addition, the specification with breaks can easily "explain" (or encompass) the positive estimated response when the breaks are omitted; in contrast, the no-breaks specification has more difficulty explaining the negative response when breaks are included. More generally, this example suggests a need for care in applying the long-run-restrictions approach.

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: no

Paper provided by Federal Reserve Bank of San Francisco in its series Working Paper Series with number 2005-21.

in new window

Date of creation: 2005
Date of revision:
Handle: RePEc:fip:fedfwp:2005-21
Contact details of provider: Postal: P.O. Box 7702, San Francisco, CA 94120-7702
Phone: (415) 974-2000
Fax: (415) 974-3333
Web page:

More information through EDIRC

Order Information: 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. Susanto Basu & John G. Fernald & Miles S. Kimball, 2004. "Are technology improvements contractionary?," Working Paper Series WP-04-20, Federal Reserve Bank of Chicago.
  2. James A. Kahn & Robert W. Rich, 2003. "Tracking the new economy: using growth theory to detect changes in trend productivity," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
  3. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  4. Michael R. Pakko, 2001. "What happens when the technology growth trend changes?: transition dynamics, capital growth and the "new economy"," Working Papers 2001-020, Federal Reserve Bank of St. Louis.
  5. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  6. Edge, Rochelle M. & Laubach, Thomas & Williams, John C., 2007. "Learning and shifts in long-run productivity growth," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2421-2438, November.
  7. Jeffrey A. Frankel & Francesco Giavazzi, 2002. "International Seminar on Macroeconomics," NBER Books, National Bureau of Economic Research, Inc, number fran02-1, December.
  8. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1991. "Stochastic trends and economic fluctuations," Working Paper Series, Macroeconomic Issues 91-4, Federal Reserve Bank of Chicago.
  9. 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.
  10. 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.).
  11. 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.).
  12. Jon Faust & Eric M. Leeper, 1994. "When do long-run identifying restrictions give reliable results?," FRB Atlanta Working Paper 94-2, Federal Reserve Bank of Atlanta.
  13. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 381-395, 04/05.
  14. Neville Francis & Valerie A. Ramey, 2006. "The Source of Historical Economic Fluctuations: An Analysis Using Long-Run Restrictions," NBER Chapters, in: NBER International Seminar on Macroeconomics 2004, pages 17-73 National Bureau of Economic Research, Inc.
  15. Jordi Galí & David López-Salido & Javier Vallés, 2000. "Technology Shocks and Monetary policy: Assessing the Fed's Performance," Banco de Espa�a Working Papers 0013, Banco de Espa�a.
  16. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  17. 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.
  18. 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.
  19. Wendy Edelberg & Martin Eichenbaum & Jonas D.M. Fisher, 1999. "Understanding the Effects of a Shock to Government Purchases," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 2(1), pages 166-206, January.
  20. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
  21. Ramey, Valerie A. & Shapiro, Matthew D., 1998. "Costly capital reallocation and the effects of government spending," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 48(1), pages 145-194, June.
  22. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  23. Ellen McGrattan & V. V. Chari & Patrick Kehoe, 2005. "Are Structural VARs Useful Guides for Developing Business Cycle Theories?," 2005 Meeting Papers 664, Society for Economic Dynamics.
  24. Ahmed, Shaghil & Ickes, Barry W. & Ping Wang & Byung Sam Yoo, 1993. "International Business Cycles," American Economic Review, American Economic Association, vol. 83(3), pages 335-59, June.
  25. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, June.
  26. John Y. Campbell, 1992. "Inspecting the Mechanism: An Analytical Approach to the Stochastic Growth Model," NBER Working Papers 4188, National Bureau of Economic Research, Inc.
  27. Bruce E. Hansen, 1995. "Approximate Asymptotic P-Values for Structural Change Tests," Boston College Working Papers in Economics 297., Boston College Department of Economics.
  28. Jordi Galí & Pau Rabanal, 2005. "Technology Shocks and Aggregate Fluctuations: How Well Does the Real Business Cycle Model Fit Postwar U.S. Data?," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 225-318 National Bureau of Economic Research, Inc.
  29. John M. Roberts, 2001. "Estimates of the productivity trend using time-varying parameter techniques," Finance and Economics Discussion Series 2001-08, Board of Governors of the Federal Reserve System (U.S.).
  30. 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.
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:fip:fedfwp:2005-21. 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: (Noah Pollaczek)

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.