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A directional distance function approach for identifying the input/output status of medical residents

Author

Listed:
  • Gary Ferrier
  • Herve Leleu

    (UCL FGES - Université Catholique de Lille - Faculté de gestion, économie et sciences - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille, LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Vivian Valdmanis
  • Michael Vardanyan

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

Abstract

The application of the human capital theory, the production theory, and the comparison of costs between teaching and non-teaching hospitals all point to the difficulties in identifying whether medical residents should be considered as inputs or outputs. We add to the debate by using a data-driven parametric approach based on the directional technology distance function to determine the status of medical residents. Using the American Hospital Association data from 1994 to 2010 we show that residents are inputs in all rural and in public non-teaching hospitals, but outputs in urban-area teaching not-for-profit hospitals. We also demonstrate that the status of residents is related to the case-mix index and that it can sometimes vary with hospital size.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Gary Ferrier & Herve Leleu & Vivian Valdmanis & Michael Vardanyan, 2017. "A directional distance function approach for identifying the input/output status of medical residents," Post-Print hal-01744641, HAL.
    • Handle: RePEc:hal:journl:hal-01744641
    DOI: 10.1080/00036846.2017.1349287
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    References listed on IDEAS

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    4. Paolo Guarda & Abdelaziz Rouabah & Michael Vardanyan, 2013. "Identifying bank outputs and inputs with a directional technology distance function," Journal of Productivity Analysis, Springer, vol. 40(2), pages 185-195, October.
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    Cited by:

    1. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    2. Maria J. Perez-Villadóniga & Ana Rodriguez-Alvarez & David Roibas, 2022. "The contribution of resident physicians to hospital productivity," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(2), pages 301-312, March.
    3. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
    4. Boussemart, Jean Philippe & Leleu, Hervé & Shen, Zhiyang, 2015. "Environmental growth convergence among Chinese regions," China Economic Review, Elsevier, vol. 34(C), pages 1-18.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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