IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v239y2019ics0277953619305386.html
   My bibliography  Save this article

Spatial heterogeneity in non-parametric efficiency: An application to Italian hospitals

Author

Listed:
  • Auteri, M.
  • Guccio, C.
  • Pammolli, F.
  • Pignataro, G.
  • Vidoli, F.

Abstract

This paper introduces a new empirical procedure for the estimation of hospitals' technical efficiency in presence of spatial heterogeneity. We propose a methodology that allows treating spatial heterogeneity independently of a predetermined reference to administrative borders. We define geographical spatial regimes, characterised by spatial proximity and homogeneity of relevant demand characteristics, within which to assess the efficiency of hospitals. The methodology has then been tested on a large sample of Italian hospitals, for which their production efficiency has been assessed within homogeneous demand areas.

Suggested Citation

  • Auteri, M. & Guccio, C. & Pammolli, F. & Pignataro, G. & Vidoli, F., 2019. "Spatial heterogeneity in non-parametric efficiency: An application to Italian hospitals," Social Science & Medicine, Elsevier, vol. 239(C).
    • Handle: RePEc:eee:socmed:v:239:y:2019:i:c:s0277953619305386
    DOI: 10.1016/j.socscimed.2019.112544
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953619305386
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2019.112544?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yu Fu & Agus Supriyadi & Tao Wang & Luwei Wang & Giuseppe T. Cirella, 2020. "Effects of Regional Innovation Capability on the Green Technology Efficiency of China’s Manufacturing Industry: Evidence from Listed Companies," Energies, MDPI, vol. 13(20), pages 1-22, October.
    2. Vidoli, Francesco & Pignataro, Giacomo & Benedetti, Roberto, 2022. "Identification of spatial regimes of the production function of Italian hospitals through spatially constrained cluster-wise regression," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    3. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    4. Guccio, C. & Lisi, D. & Martorana, M.F. & Pignataro, G., 2020. "Incorporating quality in the efficiency assessment of hospitals using a generalized directional distance function approach," Health, Econometrics and Data Group (HEDG) Working Papers 20/17, HEDG, c/o Department of Economics, University of York.
    5. Cristian Barra & Raffaele Lagravinese & Roberto Zotti, 2022. "Exploring hospital efficiency within and between Italian regions: new empirical evidence," Journal of Productivity Analysis, Springer, vol. 57(3), pages 269-284, June.
    6. Roberto Benedetti & Federica Piersimoni & Giacomo Pignataro & Francesco Vidoli, 2020. "Identification of spatially constrained homogeneous clusters of COVID‐19 transmission in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(6), pages 1169-1187, December.
    7. Cavalieri, Marina & Di Caro, Paolo & Guccio, Calogero & Lisi, Domenico, 2020. "Does neighbours' grass matter? Testing spatial dependent heterogeneity in technical efficiency of Italian hospitals," Social Science & Medicine, Elsevier, vol. 265(C).
    8. Georgios Georgiadis & Ioannis Politis & Panagiotis Papaioannou, 2020. "How Does Operational Environment Influence Public Transport Effectiveness? Evidence from European Urban Bus Operators," Sustainability, MDPI, vol. 12(12), pages 1-19, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:239:y:2019:i:c:s0277953619305386. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.