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Measures of Per Capita Hours and their Implications for the Technology-Hours Debate

  • Valerie A. Ramey

    (University of California, San Diego)

  • Neville Francis

    (University of North Carolina, Chapel Hill)

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 has significant low frequency movements that are the source of the conflicting results. HP filtered hours per capita produce results consistent with those obtained when hours are assumed to have a unit root. We provide alternative measures of hours per capita that adjust for low frequency movements in government and nonprofit employment, as well as the age composition of the population. When the new measures are used to determine the effect of technology shocks on hours using long-run restrictions, both the levels and the difference specifications give the same answer: hours decline in the short-run in response to a positive technology shock.

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Paper provided by Society for Economic Dynamics in its series 2007 Meeting Papers with number 314.

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Date of creation: 2007
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Handle: RePEc:red:sed007:314
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  1. Jordi Gali, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations," NBER Working Papers 5721, National Bureau of Economic Research, Inc.
  2. 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.
  3. 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.
  4. Burnside, Craig & Eichenbaum, Martin, 1996. "Factor-Hoarding and the Propagation of Business-Cycle Shocks," American Economic Review, American Economic Association, vol. 86(5), pages 1154-74, December.
  5. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  6. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2005. "A critique of structural VARs using real business cycle theory," Working Papers 631, Federal Reserve Bank of Minneapolis.
  7. Christopher Erceg & Luca Guerrieri & Christopher Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.).
  8. 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.
  9. Valerie A. Ramey & Neville Francis, 2006. "A Century of Work and Leisure," NBER Working Papers 12264, National Bureau of Economic Research, Inc.
  10. 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(3), pages 638-647, October.
  11. Edward C. Prescott, 2004. "Why Do Americans Work So Much More Than Europeans?," Levine's Bibliography 122247000000000413, UCLA Department of Economics.
  12. 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.
  13. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
  14. King, R.G. & Baxter, M., 1990. "Fiscal Policy In General Equilibrium," RCER Working Papers 244, University of Rochester - Center for Economic Research (RCER).
  15. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," Cowles Foundation Discussion Papers 870, Cowles Foundation for Research in Economics, Yale University.
  16. 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.).
  17. John Fernald, 2004. "Trend Breaks, Long Run Restrictions, and the Contractionary Effects of Technology Shocks," 2004 Meeting Papers 477, Society for Economic Dynamics.
  18. Kent D. Wall, 1976. "Interequation Constraint and the Specification of Dynamic Structure," NBER Working Papers 0119, National Bureau of Economic Research, Inc.
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