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Dynamic employment adjustments over business cycles

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Author Info

  • Tung Liu

    ()
    (Department of Economics, Ball State University)

  • Lee C. Spector

    ()
    (Department of Economics, Ball State University)

Abstract

This paper uses U.S. monthly industrial production employment data between 1964 and 2000 to examine the dynamic labor adjustments of production workers and nonproduction workers in both the short and longrun. The results from the short-run analysis show that the dynamic adjustment of production workers is consistent with business cycles. However, the adjustment of nonproduction workers is relatively fixed, lags behind the shocks over business cycle changes, and exhibits the quasi-fixed factor property. In the long-run, we found that nonproduction workers and production workers are cointegrated indicating that the two series are in long-run equilibrium.

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File URL: http://econfac.iweb.bsu.edu/research/workingpapers/bsuecwp200302liu.pdf
File Function: First version, 2003
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Bibliographic Info

Paper provided by Ball State University, Department of Economics in its series Working Papers with number 200302.

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Length: 19 pages
Date of creation: Dec 2003
Date of revision: Jan 2005
Publication status: Published in Empircal Economics, 2005, vol. 30, no. 1, pp. 151-169
Handle: RePEc:bsu:wpaper:200302

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Keywords: Employment adjustment; business cycles; quasi-fixed labor;

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References

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  1. Gary Hansen, 2010. "Indivisible Labor and the Business Cycle," Levine's Working Paper Archive 233, David K. Levine.
  2. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July.
  3. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-28, August.
  4. Burnside, Craig & Eichenbaum, Martin & Rebelo, Sergio, 1993. "Labor Hoarding and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 101(2), pages 245-73, April.
  5. Leybourne, S J, 1995. "Testing for Unit Roots Using Forward and Reverse Dickey-Fuller Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(4), pages 559-71, November.
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  7. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
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  12. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  13. DeJong, D.N. & Whiteman, C.H., 1991. "The Case for Trend-Stationarity is Stronger than we Thought," Working Papers 91-05, University of Iowa, Department of Economics.
  14. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
  15. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  16. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
  17. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
  18. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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Citations

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Cited by:
  1. Cravo, Túlio A., 2011. "Are small employers more cyclically sensitive? Evidence from Brazil," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 754-769.
  2. T√∫lio Cravo, 2011. "Are Small Firms more cyclically Sensitive than Large Ones? National, Regional and Sectoral Evidence from Brazil," ERSA conference papers ersa10p507, European Regional Science Association.

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