Stochastic Frontier Analysis for Healthcare, with Illustrations in R

Robin Sickles, Zhichao Wang and Valentin Zelenyuk
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Zhichao Wang: School of Economics, University of Queensland, Brisbane, Qld 4072, Australia

No WP052022, CEPA Working Papers Series from University of Queensland, School of Economics

Abstract: In this chapter, we provide a brief overview of the stochastic frontier analysis (SFA) in the context of analysing healthcare, with a focus on hospitals, where it has received most attention. We start with the classical SFA model of Aigner, Lovell and Schmidt (1977) and then consider many of its popular extensions and generalizations in both cross-sectional and panel data (mainly published in Journal of Econometrics, Journal of Business & Economic Statistics and Journal of Productivity Analysis). We also briefly discuss semi-parametric and non-parametric generalizations, spatial frontiers, and Bayesian SFA. Whenever possible, we refer the readers to various applications of these general methods to healthcare, and for hospitals in particular. Finally, we also illustrate some of these methods for real data on public hospitals in Queensland, Australia, as well as provide practical guidance and references for their computational implementations via R.

Keywords: Stochastic frontier analysis; R; healthcare; hospital; Queensland (search for similar items in EconPapers)
Date: 2022-05
New Economics Papers: this item is included in nep-ecm and nep-eff
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:qld:uqcepa:177

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