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The Predictive Value of Subjective Labour Supply Data: A Dynamic Panel Data Model with Measurement Error

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  • Euwals, Rob

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    (CPB Netherlands Bureau for Economic Policy Analysis)

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    Abstract

    This paper tests the predictive value of subjective labour supply data for adjustments in working hours over time. The idea is that if subjective labour supply data help to predict next year’s working hours, such data must contain at least some information on individual labour supply preferences. This informational content can be crucial to identify models of labour supply. Furthermore, it can be crucial to investigate the need for, or, alternatively, the support for laws and collective agreements on working hours flexibility. In this paper I apply dynamic panel data models that allow for measurement error. I find evidence for the predictive power of subjective labour supply data concerning desired working hours in the German Socio- Economic Panel 1988-1996.

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    Bibliographic Info

    Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 400.

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    Length: 29 pages
    Date of creation: Nov 2001
    Date of revision:
    Publication status: published in: Empirical Economics, 2005, 30 (2), 309-329
    Handle: RePEc:iza:izadps:dp400

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    Related research

    Keywords: dynamic panel data models; measurement error; subjective data; Labour supply;

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    References

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    1. Bell, Linda A. & Freeman, Richard B., 2001. "The incentive for working hard: explaining hours worked differences in the US and Germany," Labour Economics, Elsevier, Elsevier, vol. 8(2), pages 181-202, May.
    2. Shulamit Kahn & Kevin Lang, 1988. "The Effects of Hours Constraints on Labor Supply Estimates," NBER Working Papers 2647, National Bureau of Economic Research, Inc.
    3. Charles F. Manski, 2000. "Economic Analysis of Social Interactions," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 14(3), pages 115-136, Summer.
    4. Jennifer Hunt, 1998. "Hours Reductions as Work-Sharing," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 29(1), pages 339-381.
    5. Euwals, R.W. & Soest, A.H.O. van, 1996. "Desired and Actual Labour Supply of Unmarried Men and Women in the Netherlands," Discussion Paper, Tilburg University, Center for Economic Research 1996-23, Tilburg University, Center for Economic Research.
    6. Rob Euwals & Bertrand Melenberg & Arthur van Soest, 1998. "Testing the predictive value of subjective labour supply data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 13(5), pages 567-585.
    7. Ilmakunnas, Seija & Pudney, Stephen, 1990. "A model of female labour supply in the presence of hours restrictions," Journal of Public Economics, Elsevier, Elsevier, vol. 41(2), pages 183-210, March.
    8. Stewart, Mark B & Swaffield, Joanna K, 1997. "Constraints on the Desired Hours of Work of British Men," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 107(441), pages 520-35, March.
    9. F. Thomas Juster, 1966. "Consumer Buying Intentions and Purchase Probability: An Experiment in Survey Design," NBER Books, National Bureau of Economic Research, Inc, National Bureau of Economic Research, Inc, number just66-2.
    10. Ham, John C, 1982. "Estimation of a Labour Supply Model with Censoring Due to Unemployment and Underemployment," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 49(3), pages 335-54, July.
    11. Kapteyn, Arie & Kooreman, Peter, 1992. "Household labor supply: What kind of data can tell us how many decision makers there are?," European Economic Review, Elsevier, Elsevier, vol. 36(2-3), pages 365-371, April.
    12. Euwals, Rob, 2001. "Female Labour Supply, Flexibility of Working Hours, and Job Mobility," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 111(471), pages C120-34, May.
    13. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 58(2), pages 277-97, April.
    14. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 31(1), pages 93-118, February.
    15. Pannenberg, Markus & Wagner, Gert G., 2001. "Why Do Overtime Work, Overtime Compensation and the Distribution of Economic Well-Being Evidence for the West Germany and Great Britain," IZA Discussion Papers 318, Institute for the Study of Labor (IZA).
    16. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, Elsevier, vol. 104(2), pages 259-268, September.
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