[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/qld/uqcepa/149.html
   My bibliography  Save this paper

Aggregate Efficiency of Industry and its Groups: The case of Queensland Public Hospitals

Author

Abstract
In this paper, we explore the efficiency of different groups of hospitals in Queens-land, Australia, focusing on teaching and non-teaching hospitals, by adapting the most recent developments on statistical analysis of aggregate efficiency. We focus on the two approaches: the bootstrap approach proposed by Simar and Zelenyuk (2007) and the central limits theorems recently developed by Simar and Zelenyuk (2018, 2020). To adapt these developments, we extend the central limit theorems to the context where there are several sub-groups in the population. Using real data on Queensland public hospitals, we found that teaching hospitals are significantly less efficient than non-teaching hospitals when benchmarking is done with respect to the constant returns to scale frontier, but are significantly more efficient when benchmarking with respect to the variable returns to scale frontier.

Suggested Citation

  • Bao Hoang Nguyen & Valentin Zelenyuk, 2020. "Aggregate Efficiency of Industry and its Groups: The case of Queensland Public Hospitals," CEPA Working Papers Series WP062020, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uqcepa:149
    as

    Download full text from publisher

    File URL: https://economics.uq.edu.au/files/18267/WP062020.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Hospitals; Aggregate Efficiency; Envelopment Estimators; Bootstrap; Central Limit Theorems.;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:qld:uqcepa:149. 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: SOE IT (email available below). General contact details of provider: https://edirc.repec.org/data/decuqau.html .

    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.