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Why Junior Doctors Don’t Want to Become General Practitioners: A Discrete Choice Experiment from the MABEL Longitudinal Study of Doctors

Author

Listed:
  • Peter Sivey

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

  • Anthony Scott

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

  • Julia Witt

    (Department of Economics, University of Manitoba)

  • Catherine Joyce

    (Department of Epidemiology and Preventive Medicine, Monash University)

  • John Humphreys

    (School of Rural Health, Monash University)

Abstract

A number of studies suggest there is an over-supply of specialists and an undersupply of GPs in many developed countries. Previous econometric studies of specialty choice from the US suggest that a number of factors play a role, including expected future earnings, educational debt, and having predictable working hours. Given endogeneity issues in revealed preference studies, a stated-preference approach is warranted. This paper presents results from a discrete-choice experiment completed by a sample of 532 junior doctors in 2008 before they choose a specialty training program. This was conducted as part of the first wave of the MABEL (Medicine in Australia: Balancing Employment and Life) longitudinal survey of doctors. We include key job attributes such as future earnings and hours worked, but also allow the choice to be influenced by academic research opportunities, continuity of care and the amount of procedural work. Interactions of attributes with doctor characteristics, including gender, educational debt, and personality traits are also examined. We find the income/working hours trade-offs estimated from our discrete choice model are close to the actual wages of senior specialists, but much higher than those of senior GPs. In a policy simulation we find that increasing GPs’ earnings by $50,000, increasing opportunities for procedural or academic work can increase the number of junior doctors choosing General Practice by between 8 and 16 percentage points, approximately 212 to 376 junior doctors per year. The results can inform policymakers looking to address unbalanced supply of doctors across specialties.

Suggested Citation

  • Peter Sivey & Anthony Scott & Julia Witt & Catherine Joyce & John Humphreys, 2010. "Why Junior Doctors Don’t Want to Become General Practitioners: A Discrete Choice Experiment from the MABEL Longitudinal Study of Doctors," Melbourne Institute Working Paper Series wp2010n17, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    • Handle: RePEc:iae:iaewps:wp2010n17
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    References listed on IDEAS

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    1. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LLC, vol. 7(3), pages 388-401, September.
    2. Hall, Jane & Fiebig, Denzil G. & King, Madeleine T. & Hossain, Ishrat & Louviere, Jordan J., 2006. "What influences participation in genetic carrier testing?: Results from a discrete choice experiment," Journal of Health Economics, Elsevier, vol. 25(3), pages 520-537, May.
    3. Scott, Anthony, 2001. "Eliciting GPs' preferences for pecuniary and non-pecuniary job characteristics," Journal of Health Economics, Elsevier, vol. 20(3), pages 329-347, May.
    4. Gerrit Mueller & Erik Plug, 2006. "Estimating the Effect of Personality on Male and Female Earnings," ILR Review, Cornell University, ILR School, vol. 60(1), pages 3-22, October.
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    Cited by:

    1. Jeffrey E. Harris & Beatriz G. López-Valcárcel & Patricia Barber & Vicente Ortún, 2014. "Efficiency versus Equity in the Allocation of Medical Specialty Training Positions in Spain: A Health Policy Simulation Based on a Discrete Choice Model," NBER Working Papers 19896, National Bureau of Economic Research, Inc.
    2. Line Pedersen & Dorte Gyrd-Hansen, 2014. "Preference for practice: a Danish study on young doctors’ choice of general practice using a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(6), pages 611-621, July.

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    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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