IDEAS home Printed from https://ideas.repec.org/a/cup/hecopl/v17y2022i2p175-199_4.html
   My bibliography  Save this article

An application of PCA-DEA with the double-bootstrap approach to estimate the technical efficiency of New Zealand District Health Boards

Author

Listed:
  • Andrews, Antony

Abstract

Using yearly panel data from 2011 to 2017 on New Zealand District Health Boards (DHBs), this study combines principal component analysis and data envelopment intertemporal analysis with the double-bootstrap approach to estimate the technical efficiency of health care providers along with the trend of efficiency performances. The results show that although most large DHBs have improved their level of technical efficiency between 2011 and 2017, the majority of medium- and small-sized DHBs have not seen any noticeable improvement in their level of technical efficiency. The results also show that large and tertiary DHBs operate at a high level of technical efficiency. In contrast, most of the medium- and small-sized DHBs posted some of the lowest technical efficiency scores. Furthermore, the results show that medium- and small-sized DHBs have a higher average length of hospital stays which is found to be associated with decreasing levels of technical efficiency scores.

Suggested Citation

  • Andrews, Antony, 2022. "An application of PCA-DEA with the double-bootstrap approach to estimate the technical efficiency of New Zealand District Health Boards," Health Economics, Policy and Law, Cambridge University Press, vol. 17(2), pages 175-199, April.
  • Handle: RePEc:cup:hecopl:v:17:y:2022:i:2:p:175-199_4
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1744133120000420/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Yu He & Wenkuan Chen, 2023. "Evaluation of Sustainable Development Policy of Sichuan Citrus Industry in China Based on DEA–Malmquist Index and DID Model," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
    2. Muchen Luo & Yimin Wu, 2022. "Data-Driven Evaluation and Optimisation of Livelihood Improvement Efficiency," Sustainability, MDPI, vol. 14(13), pages 1-24, July.
    3. Zihong Liu & Haitao Xiong & Ying Sun, 2023. "Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
    4. Yu He, 2024. "Assessment of Climate Adaptability in the Late-Maturing Citrus Industry in Sichuan Province," Agriculture, MDPI, vol. 14(7), pages 1-16, July.

    More about this item

    Statistics

    Access and download statistics

    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:cup:hecopl:v:17:y:2022:i:2:p:175-199_4. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/hep .

    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.