IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

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: http://www.frbsf.org/economic-research/files/wp05-21bk.pdf
Download Restriction: no

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

as
in new window

Length:
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: http://www.frbsf.org/
Email:


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. 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.
  2. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
  3. James A. Kahn & Robert W. Rich, 2003. "Tracking the new economy: using growth theory to detect changes in trend productivity," Staff Reports 159, Federal Reserve Bank of New York.
  4. 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.
  5. 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.
  6. Gali, Jordi & Lopez-Salido, J. David & Valles, Javier, 2003. "Technology shocks and monetary policy: assessing the Fed's performance," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 723-743, May.
  7. 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.
  8. 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.
  9. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
  10. 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.
  11. 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.
  12. 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.
  13. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  14. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  15. Bruce E. Hansen, 1995. "Approximate Asymptotic P-Values for Structural Change Tests," Boston College Working Papers in Economics 297., Boston College Department of Economics.
  16. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2006. "Assessing Structural VARs," NBER Working Papers 12353, National Bureau of Economic Research, Inc.
    • 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.
  17. Valerie A. Ramey & Matthew D. Shapiro, 1999. "Costly Capital Reallocation and the Effects of Government Spending," NBER Working Papers 6283, National Bureau of Economic Research, Inc.
  18. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  19. 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.
  20. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," NBER Working Papers 10254, National Bureau of Economic Research, Inc.
  21. Rochelle M. Edge & Thomas Laubach & John C. Williams, 2004. "Learning and shifts in long-run productivity growth," Working Paper Series 2004-04, Federal Reserve Bank of San Francisco.
  22. 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.
  23. Campbell, John Y., 1994. "Inspecting the mechanism: An analytical approach to the stochastic growth model," Journal of Monetary Economics, Elsevier, vol. 33(3), pages 463-506, June.
  24. Ahmed, S. & Ickes, B. & Wang, P. & Yoo, S., 1989. "International Business Cycles," Papers 7-89-4, Pennsylvania State - Department of Economics.
  25. 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.
  26. 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.
  27. 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.).
  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. 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.
  30. Jeffrey A. Frankel & Francesco Giavazzi, 2002. "International Seminar on Macroeconomics," NBER Books, National Bureau of Economic Research, Inc, number fran02-1.
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.