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

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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
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    File URL: https://economics.uq.edu.au/files/18267/WP062020.pdf
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    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

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