IDEAS home Printed from https://ideas.repec.org/p/fip/fedfwp/2005-21.html
   My bibliography  Save this paper

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

Author

Listed:
  • John G. Fernald

Abstract

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.

Suggested Citation

  • John G. Fernald, 2005. "Trend breaks, long-run restrictions, and the contractionary effects of technology improvements," Working Paper Series 2005-21, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfwp:2005-21
    as

    Download full text from publisher

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jordi Galí & Pau Rabanal, 2005. "Technology Shocks and Aggregate Fluctuations: How Well Does the Real Business Cycle Model Fit Postwar US Data?," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 225-318, National Bureau of Economic Research, Inc.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Kahn, James A. & Rich, Robert W., 2007. "Tracking the new economy: Using growth theory to detect changes in trend productivity," Journal of Monetary Economics, Elsevier, vol. 54(6), pages 1670-1701, September.
    8. 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.
    9. Jeffrey A. Frankel & Francesco Giavazzi, 2002. "International Seminar on Macroeconomics 2001," NBER Books, National Bureau of Economic Research, Inc, number fran02-1, February.
    10. 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, May.
    11. 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.
    12. 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.
    13. 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.
    14. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-840, September.
    15. 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.
    16. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    17. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    18. 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.
    19. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    20. Rochelle Edge & Thomas Laubach, 2004. "Learning and Shifts in Long-Run Growth," Computing in Economics and Finance 2004 123, Society for Computational Economics.
    21. 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.
    22. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Chapters, in: NBER Macroeconomics Annual 1988, Volume 3, pages 111-156, National Bureau of Economic Research, Inc.
    23. Ahmed, Shaghil & Ickes, Barry W. & Ping Wang & Byung Sam Yoo, 1993. "International Business Cycles," American Economic Review, American Economic Association, vol. 83(3), pages 335-359, June.
    24. 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.
    25. 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.
    26. 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.
    27. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    28. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    29. Faust, Jon & Leeper, Eric M, 1997. "When Do Long-Run Identifying Restrictions Give Reliable Results?," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 345-353, July.
    30. 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.
    31. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luca Gambetti & Jordi Galí, 2009. "On the Sources of the Great Moderation," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 26-57, January.
    2. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology-Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    3. Patrick J. Kehoe, 2006. "How to advance theory with structural VARs: use the Sims-Cogley-Nason approach," Staff Report 379, Federal Reserve Bank of Minneapolis.
    4. Mikael Carlsson & Jon Smedsaas, 2007. "Technology Shocks and the Labor‐Input Response: Evidence from Firm‐Level Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1509-1520, September.
    5. Louis Phaneuf & Nooman Rebei, 2007. "Technology Shocks and Business Cycles: The Role of Processing Stages and Nominal Rigidities," Staff Working Papers 07-7, Bank of Canada.
    6. Peter N. Ireland, 2009. "On the Welfare Cost of Inflation and the Recent Behavior of Money Demand," American Economic Review, American Economic Association, vol. 99(3), pages 1040-1052, June.
    7. Karel Mertens & Morten O. Ravn, 2011. "Technology-Hours Redux: Tax Changes and the Measurement of Technology Shocks," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 7(1), pages 41-76.
    8. Hashmat Khan & John Tsoukalas, 2005. "Technology Shocks and UK Business Cycles," Macroeconomics 0512006, University Library of Munich, Germany.
    9. Peter Ireland & Scott Schuh, 2008. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 473-492, July.
    10. Richard Dion & Robert Fay, 2008. "Understanding Productivity: A Review of Recent Technical Research," Discussion Papers 08-3, Bank of Canada.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
    2. Peter Ireland & Scott Schuh, 2008. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 473-492, July.
    3. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
    4. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    5. Peter N. Ireland, 2009. "On the Welfare Cost of Inflation and the Recent Behavior of Money Demand," American Economic Review, American Economic Association, vol. 99(3), pages 1040-1052, June.
    6. 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.
    7. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology‐Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    8. 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.
    9. Domenico J. Marchetti & Francesco Nucci, 2007. "Pricing Behavior and the Response of Hours to Productivity Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1587-1611, October.
    10. Hashmat Khan & John Tsoukalas, 2005. "Technology Shocks and UK Business Cycles," Macroeconomics 0512006, University Library of Munich, Germany.
    11. 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.
    12. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    13. Thomet, Jacqueline & Wegmueller, Philipp, 2021. "Technology Shocks And Hours Worked: A Cross-Country Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 25(4), pages 1020-1052, June.
    14. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    15. 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.
    16. Sean Holly & Ivan Petrella, 2008. "Factor demand linkages and the business cycle: interpreting aggregate fluctuations as sectoral fluctuations," CDMA Conference Paper Series 0809, Centre for Dynamic Macroeconomic Analysis.
    17. Arabinda Basistha, 2009. "Hours per capita and productivity: evidence from correlated unobserved components models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 187-206.
    18. Yongsung Chang & Jay H. Hong, 2006. "Do Technological Improvements in the Manufacturing Sector Raise or Lower Employment?," American Economic Review, American Economic Association, vol. 96(1), pages 352-368, March.
    19. Benati, Luca, 2007. "Drift and breaks in labor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2847-2877, August.
    20. Giancarlo Corsetti & Luca Dedola & Sylvain Leduc, 2008. "Productivity, External Balance, and Exchange Rates: Evidence on the Transmission Mechanism among G7 Countries," NBER Chapters, in: NBER International Seminar on Macroeconomics 2006, pages 117-194, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. 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.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Federal Reserve Bank of San Francisco Research Library (email available below). General contact details of provider: https://edirc.repec.org/data/frbsfus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.