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Comparing French and US hospital technologies: a directional input distance function approach

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  • Benoit Dervaux
  • Gary Ferrier
  • Herve Leleu
  • Vivian Valdmanis

Abstract

French and US hospital technologies are compared using directional input distance functions. The aggregation properties of the directional distance function allow comparison of hospital industry-level performance as well as standard firm-level performance with regard to productive efficiency. In addition, the underlying constituents of efficiency - in the short run, congestion and technical inefficiency, and in the long run, scale inefficiency - are analysed by decomposing the overall measure. By virtue of using the directional distance function, it is also possible to obtain an estimate of a lower bound on allocative inefficiency. It is found that French and US hospitals use quite different technologies. Long run scale inefficiencies cause most of the French hospitals' inefficiency, while short run technical inefficiency is the main source of overall productive inefficiency in the US hospitals.

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  • Benoit Dervaux & Gary Ferrier & Herve Leleu & Vivian Valdmanis, 2004. "Comparing French and US hospital technologies: a directional input distance function approach," Applied Economics, Taylor & Francis Journals, vol. 36(10), pages 1065-1081.
    • Handle: RePEc:taf:applec:v:36:y:2004:i:10:p:1065-1081
    DOI: 10.1080/0003684042000246786
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    8. Jean-Philippe Boussemart & Hervé Leleu, 2008. "Comparing TFP Catching-up and Capital Deepening in US and European Growths: A Directional Distance Function Approach," Working Papers 2008-ECO-01, IESEG School of Management.
    9. Färe, Rolf & Pasurka, Carl & Vardanyan, Michael, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," European Journal of Operational Research, Elsevier, vol. 262(1), pages 361-369.
    10. 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).
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    13. Emma Medin & Kjartan Anthun & Unto Häkkinen & Sverre Kittelsen & Miika Linna & Jon Magnussen & Kim Olsen & Clas Rehnberg, 2011. "Cost efficiency of university hospitals in the Nordic countries: a cross-country analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 12(6), pages 509-519, December.
    14. Teresa Harrison, 2006. "Hospital mergers: who merges with whom?," Applied Economics, Taylor & Francis Journals, vol. 38(6), pages 637-647.
    15. Xia, X.H. & Chen, G.Q., 2012. "Energy abatement in Chinese industry: Cost evaluation of regulation strategies and allocation alternatives," Energy Policy, Elsevier, vol. 45(C), pages 449-458.
    16. Bruce Hollingsworth, 2008. "The measurement of efficiency and productivity of health care delivery," Health Economics, John Wiley & Sons, Ltd., vol. 17(10), pages 1107-1128, October.
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    18. An‐Pang Wang & Che‐Wei Chang & Juin‐Ming Tsai & Shiu‐Wan Hung, 2021. "A performance evaluation of Major League Baseball teams: An integrated social network and data envelopment analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1421-1434, September.
    19. Yanzhi Bi, 2021. "Analyzing the performance of the Major League Baseball Teams by using the Data Envelopment Analysis," Business & Entrepreneurship Journal, SCIENPRESS Ltd, vol. 10(1), pages 1-1.
    20. Varabyova, Yauheniya & Schreyögg, Jonas, 2013. "International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches," Health Policy, Elsevier, vol. 112(1), pages 70-79.
    21. Färe, Rolf & Karagiannis, Giannis, 2022. "Aggregating Farrell efficiencies without value data: The case of hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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