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Persistence and Cycles in US Hours Worked

  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana

This paper analyses monthly hours worked in the US over the sample period 1939m1 - 2011m10 using a cyclical long memory model; this is based on Gegenbauer processes and characterised by autocorrelations decaying to zero cyclically and at a hyperbolic rate along with a spectral density that is unbounded at a non-zero frequency. The reason for choosing this specification is that the periodogram of the hours worked series has a peak at a frequency away from zero. The empirical results confirm that this model works extremely well for hours worked, and it is then employed to analyse their relationship with technology shocks. It is found that hours worked increase on impact in response to a technology shock (though the effect dies away rapidly), consistently with Real Business Cycle (RBC) models.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.395405.de/dp1200.pdf
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Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 1200.

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Length: 26 p.
Date of creation: 2012
Date of revision:
Handle: RePEc:diw:diwwpp:dp1200
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  1. Elena Pesavento & Barbara Rossi, 2003. "Do Technology Shocks Drive Hours Up or Down? A Little Evidence from an Agnostic Procedure," Emory Economics 0326, Department of Economics, Emory University (Atlanta).
  2. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  3. Galí, Jordi, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," CEPR Discussion Papers 1499, C.E.P.R. Discussion Papers.
  4. Glosser, Stuart M. & Golden, Lonnie, 1997. "Average work hours as a leading economic variable in US manufacturing industries," International Journal of Forecasting, Elsevier, vol. 13(2), pages 175-195, June.
  5. Neville Francis & Valerie A. Ramey, 2005. "Measures of Per Capita Hours and their Implications for the Technology-Hours Debate," NBER Working Papers 11694, National Bureau of Economic Research, Inc.
  6. Ignacio N. Lobato & Carlos Velasco, 2005. "Efficient Wald Tests For Fractional Unit Roots," Economics Working Papers we056935, Universidad Carlos III, Departamento de Economía.
  7. Chung, Ching-Fan, 1996. "Estimating a generalized long memory process," Journal of Econometrics, Elsevier, vol. 73(1), pages 237-259, July.
  8. 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.
  9. Christina D. Romer, 1992. "Remeasuring Business Cycles," NBER Working Papers 4150, National Bureau of Economic Research, Inc.
  10. Bernardi, Mauro & Della Corte, Giuseppe & Proietti, Tommaso, 2008. "Extracting the Cyclical Component in Hours Worked: a Bayesian Approach," MPRA Paper 8967, University Library of Munich, Germany.
  11. Romer, Christina, 1986. "Spurious Volatility in Historical Unemployment Data," Journal of Political Economy, University of Chicago Press, vol. 94(1), pages 1-37, February.
  12. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, May.
  13. Robert G. King & Sergio T. Rebelo, 2000. "Resuscitating Real Business Cycles," NBER Working Papers 7534, National Bureau of Economic Research, Inc.
  14. Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 219-261.
  15. Violetta Dalla & Javier Hidalgo, 2005. "A parametric bootstrap test for cycles," LSE Research Online Documents on Economics 6829, London School of Economics and Political Science, LSE Library.
  16. Gil-Alana, Luis Alberiko & Moreno, Antonio, 2009. "Technology Shocks And Hours Worked: A Fractional Integration Perspective," Macroeconomic Dynamics, Cambridge University Press, vol. 13(05), pages 580-604, November.
  17. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.
  18. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  19. Jordi Galí & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
  20. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
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