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Trends in hours, balanced growth and the role of technology in the business cycle

The present paper revisits a property embedded in most dynamic macroeconomic models: the stationarity of hours worked. First, I argue that, contrary to what is often believed, there are many reasons why hours could be nonstationary in those models, while preserving the property of balanced growth. Second, I show that the postwar evidence for most industrialized economies is clearly at odds with the assumption of stationary hours per capita. Third, I examine the implications of that evidence for the role of technology as a source of economic fl uctuations in the G7 countries.

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Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 829.

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Date of creation: Jan 2005
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Handle: RePEc:upf:upfgen:829
Contact details of provider: Web page: http://www.econ.upf.edu/

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  1. Olivier J. Blanchard & Lawrence H. Summers, 1986. "Hysteresis and the European Unemployment Problem," NBER Chapters, in: NBER Macroeconomics Annual 1986, Volume 1, pages 15-90 National Bureau of Economic Research, Inc.
  2. Whelan, Karl, 2006. "New Evidence on Balanced Growth, Stochastic Trends, and Economic Fluctuations," MPRA Paper 5910, University Library of Munich, Germany.
  3. Robert E. Hall, 1997. "Macroeconomic Fluctuations and the Allocation of Time," NBER Working Papers 5933, National Bureau of Economic Research, Inc.
  4. Susanto Basu & John Fernald & Miles Kimball, 2004. "Are technology improvements contractionary?," Working Paper Series WP-04-20, Federal Reserve Bank of Chicago.
  5. Francis, Neville R & Owyang, Michael T & Theodorou, Athena T, 2005. "What Explains the Varying Monetary Response to Technology Shocks in G-7 Countries?," MPRA Paper 834, University Library of Munich, Germany.
  6. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
  7. Edward C. Prescott, 2004. "Why do Americans Work so Much More than Europeans?," NBER Working Papers 10316, National Bureau of Economic Research, Inc.
  8. repec:ucn:oapubs:10197/226 is not listed on IDEAS
  9. Christopher J. Erceg & Luca Guerrieri, 2004. "Can Long-Run Restrictions Identify Technology Shocks?," Computing in Economics and Finance 2004 3, Society for Computational Economics.
  10. repec:ucn:oapubs:10197/218 is not listed on IDEAS
  11. 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.
  12. Edward C. Prescott, 1986. "Theory ahead of business cycle measurement," Staff Report 102, Federal Reserve Bank of Minneapolis.
  13. King, Robert G. & Rebelo, Sergio T., 1999. "Resuscitating real business cycles," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 14, pages 927-1007 Elsevier.
  14. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-73, September.
  15. Jordi Galí & Mark Gertler & J. David López-Salido, 2002. "Markups, gaps, and the welfare costs of business fluctuations," Banco de Espa�a Working Papers 0204, Banco de Espa�a.
  16. James H. Stock & Mark W. Watson, 1998. "Business Cycle Fluctuations in U.S. Macroeconomic Time Series," NBER Working Papers 6528, National Bureau of Economic Research, Inc.
  17. 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.
  18. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  19. Argia Sbordone, 2002. "An optimizing model of U.S. wage and price dynamics," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  20. Fagan, Gabriel & Henry, Jérôme & Mestre, Ricardo, 2001. "An area-wide model (AWM) for the euro area," Working Paper Series 0042, European Central Bank.
  21. Whelan, Karl, 2004. "Technology Shocks and Hours Worked: Checking for Robust Conclusions," Research Technical Papers 6/RT/04, Central Bank of Ireland.
  22. 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.
  23. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
  24. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
  25. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
  26. John Fernald, 2004. "Trend Breaks, Long Run Restrictions, and the Contractionary Effects of Technology Shocks," 2004 Meeting Papers 477, Society for Economic Dynamics.
  27. Casey B. Mulligan, 2002. "A Century of Labor-Leisure Distortions," NBER Working Papers 8774, National Bureau of Economic Research, Inc.
  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.
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