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Measures of per Capita Hours and Their Implications for the Technology-Hours Debate*

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  • NEVILLE FRANCIS
  • VALERIE A. RAMEY

Abstract

Structural vector autoregressions give conflicting results on the effects of technology shocks on hours. The results depend crucially on the assumed data generating process for hours per capita. We show that the standard measure of hours per capita and productivity have significant low-frequency movements that are the source of the conflicting results. Hodrick-Prescott (HP)-filtered hours per capita produce results consistent with those obtained when hours are assumed to have a unit root. We show that important sources of the low-frequency movements in the standard measure are sectoral shifts in hours and the changing age composition of the working-age population. When we control for these low-frequency components to determine the effect of technology shocks on hours using long-run restrictions we get one consistent answer: hours decline in the short run in response to a positive technology shock. We further extend the analysis by examining the effects of demographic controls on the impulse responses to investment-specific technology shocks. Our results are less conclusive. Copyright (c) 2009 The Ohio State University.

Suggested Citation

  • 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.
  • Handle: RePEc:mcb:jmoncb:v:41:y:2009:i:6:p:1071-1097
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    References listed on IDEAS

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    1. Valerie A. Ramey & Neville Francis, 2009. "A Century of Work and Leisure," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(2), pages 189-224, July.
    2. 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.
    3. 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.
    4. L. Rachel Ngai & Christopher A. Pissarides, 2008. "Trends in Hours and Economic Growth," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(2), pages 239-256, April.
    5. Hansen, G D, 1993. "The Cyclical and Secular Behaviour of the Labour Input: Comparing Efficiency Units and Hours Worked," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 71-80, Jan.-Marc.
    6. 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.
    7. Burnside, Craig & Eichenbaum, Martin, 1996. "Factor-Hoarding and the Propagation of Business-Cycle Shocks," American Economic Review, American Economic Association, vol. 86(5), pages 1154-1174, December.
    8. Edward C. Prescott, 2004. "Why do Americans work so much more than Europeans?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 28(Jul), pages 2-13.
    9. 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.
    10. Neville Francis & Valerie A. Ramey, 2002. "Is the Technology-Driven Real Business Cycle Hypothesis Dead?," NBER Working Papers 8726, National Bureau of Economic Research, Inc.
    11. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 638-647, October.
    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. 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.
    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. 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. Kent D. Wall, 1976. "Interequation Constraint and the Specification of Dynamic Structure," NBER Working Papers 0119, National Bureau of Economic Research, Inc.
    17. 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.
    18. Stephanie Aaronson & Bruce Fallick & Andrew Figura & Jonathan Pingle & William Wascher, 2006. "The Recent Decline in the Labor Force Participation Rate and Its Implications for Potential Labor Supply," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 37(1), pages 69-154.
    19. 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.
    20. Christiano, Lawrence J & Eichenbaum, Martin, 1992. "Current Real-Business-Cycle Theories and Aggregate Labor-Market Fluctuations," American Economic Review, American Economic Association, vol. 82(3), pages 430-450, June.
    21. Eichenbaum, Martin & Fisher, Jonas D M, 2005. "Fiscal Policy in the Aftermath of 9/11," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(1), pages 1-22, February.
    22. 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.
    23. John Fernald, 2004. "Trend Breaks, Long Run Restrictions, and the Contractionary Effects of Technology Shocks," 2004 Meeting Papers 477, Society for Economic Dynamics.
    24. Neville Francis & Michael T. Owyang & Jennifer E. Roush, 2005. "A Flexible Finite-Horizon Identification of Technology Shocks," International Finance Discussion Papers 832, Board of Governors of the Federal Reserve System (U.S.).
    25. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    26. James Feyrer, 2007. "Demographics and Productivity," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 100-109, February.
    27. 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.
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    Replication

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  • Maik H. Wolters, 2018. "How the baby boomers' retirement wave distorts model‐based output gap estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 680-689, August.
  • More about this item

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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