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Long Work Hours: Volunteers and Conscripts

Author

Listed:
  • Robert Drago

    (Pennsylvania State University, USA)

  • Mark Wooden

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

  • David Black

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne and Brotherhood of St Laurence)

Abstract

Panel data from Australia are used to study the prevalence of work hours mismatch among long hours workers and, more importantly, how that mismatch persists and changes over time, and what factors are associated with these changes. Particular attention is paid to the roles played by household debt, ideal worker characteristics and gender. Both static and dynamic multinomial logit models are estimated, with the dependent variable distinguishing long hours workers from other workers, and within the former, between “volunteers”, who prefer long hours, and “conscripts”, who do not. The results suggest that: (i) high levels of debt are mainly associated with conscript status; (ii) ideal worker types can be found among both volunteers and conscripts, but are much more likely to be conscripts; and (iii) women are relatively rare among long hours workers, and especially long hours volunteers, suggesting long hours jobs may be discriminatory. The research highlights the importance of distinguishing conscripts and volunteers to understand the prevalence and dynamics of long work hours.

Suggested Citation

  • Robert Drago & Mark Wooden & David Black, 2006. "Long Work Hours: Volunteers and Conscripts," Melbourne Institute Working Paper Series wp2006n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  • Handle: RePEc:iae:iaewps:wp2006n27
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    References listed on IDEAS

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    Cited by:

    1. Mark Wooden & Robert Drago, 2007. "The Changing Distribution of Working Hours in Australia," Melbourne Institute Working Paper Series wp2007n19, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    2. Lucía Artazcoz & Imma Cortès-Franch & Vicenta Escribà-Agüir & María López & Fernando G. Benavides, 2018. "Long Working Hours and Job Quality in Europe: Gender and Welfare State Differences," IJERPH, MDPI, vol. 15(11), pages 1-15, November.
    3. Cathy Honge Gong & Xiaojun He, 2019. "Factors Predicting Voluntary and Involuntary Workforce Transitions at Mature Ages: Evidence from HILDA in Australia," IJERPH, MDPI, vol. 16(19), pages 1-20, October.
    4. Robert Breunig & Xiaodong Gong & Gordon Leslie, 2015. "The Dynamics of Satisfaction with Working Hours in Australia: The Usefulness of Panel Data in Evaluating the Case for Policy Intervention," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 2(1), pages 130-154, January.
    5. Stefanie Gerold & Matthias Nocker, 2015. "Reduction of Working Time in Austria. A Mixed Methods Study Relating a New Work Time Policy to Employee Preferences. WWWforEurope Working Paper No. 97," WIFO Studies, WIFO, number 58139, April.
    6. Iain Campbell, 2007. "Long Working Hours in Australia: Working-Time Regulation and Employer Pressures," The Economic and Labour Relations Review, , vol. 17(2), pages 37-68, April.
    7. Frei, Irina & Grund, Christian, 2017. "Antecedents of Overtime Work: The Case of Junior Academics," IZA Discussion Papers 11065, Institute of Labor Economics (IZA).
    8. Wan-Ju Cheng & Li-Chung Pien & Tomohide Kubo & Yawen Cheng, 2020. "Trends in Work Conditions and Associations with Workers’ Health in Recent 15 Years: The Role of Job Automation Probability," IJERPH, MDPI, vol. 17(15), pages 1-12, July.
    9. Gerold, Stefanie & Nocker, Matthias, 2018. "More Leisure or Higher Pay? A Mixed-methods Study on Reducing Working Time in Austria," Ecological Economics, Elsevier, vol. 143(C), pages 27-36.
    10. Argyro Avgoustaki & Almudena Cañibano, 2020. "Motivational Drivers of Extensive Work Effort: Are Long Hours Always Detrimental to Well‐being?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 59(3), pages 355-398, July.
    11. Hendrik Schmitz & Ansgar Wübker, 2011. "What determines influenza vaccination take‐up of elderly Europeans?," Health Economics, John Wiley & Sons, Ltd., vol. 20(11), pages 1281-1297, November.

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    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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