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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.

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

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Date of creation: 2005
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Handle: RePEc:fip:fedfwp:2005-21
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  1. 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.
  2. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  3. Michael R. Pakko, 2002. "What Happens When the Technology Growth Trend Changes?: Transition Dynamics, Capital Growth and the 'New Economy'," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(2), pages 376-407, April.
  4. Matthew Shapiro & Mark Watson, 1988. "Sources of Business Cycles Fluctuations," NBER Chapters, in: NBER Macroeconomics Annual 1988, Volume 3, pages 111-156 National Bureau of Economic Research, Inc.
  5. 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.
  6. 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.
  7. Roberts John M., 2001. "Estimates of the Productivity Trend Using Time-Varying Parameter Techniques," The B.E. Journal of Macroeconomics, De Gruyter, vol. 1(1), pages 1-32, July.
  8. Susanto Basu & John G. Fernald & Miles S. Kimball, 2004. "Are technology improvements contractionary?," Working Paper Series WP-04-20, Federal Reserve Bank of Chicago.
  9. Wendy Edelberg & Martin Eichenbaum & Jonas D. M. Fisher, 1998. "Understanding the effects of a shock to government purchases," Working Paper Series WP-98-7, Federal Reserve Bank of Chicago.
  10. 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.
  11. 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.
  12. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  13. 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.
  14. 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.
  15. Jordi Gali & J. David Lopez-Salido & Javier Valles, 2002. "Technology Shocks and Monetary Policy: Assessing the Fed's Performance," NBER Working Papers 8768, National Bureau of Economic Research, Inc.
  16. 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.).
  17. 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.
  18. 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.
  19. Bruce E. Hansen, 1995. "Approximate Asymptotic P-Values for Structural Change Tests," Boston College Working Papers in Economics 297., Boston College Department of Economics.
  20. Jeffrey A. Frankel & Francesco Giavazzi, 2002. "International Seminar on Macroeconomics," NBER Books, National Bureau of Economic Research, Inc, number fran02-1, September.
  21. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1987. "Stochastic Trends and Economic Fluctuations," NBER Working Papers 2229, National Bureau of Economic Research, Inc.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  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. 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.
  28. 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, December.
  29. 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.
  30. 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.
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