IDEAS home Printed from https://ideas.repec.org/p/qld/uqcepa/177.html
   My bibliography  Save this paper

Stochastic Frontier Analysis for Healthcare, with Illustrations in R

Author

Listed:
  • Robin C. Sickles

    (Department of Economics, Rice University, Houston, TX 77251-1892, USA)

  • Zhichao Wang

    (School of Economics, University of Queensland, Brisbane, Qld 4072, Australia)

  • Valentin Zelenyuk

    (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia)

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.

Suggested Citation

  • Robin C. Sickles & Zhichao Wang & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis for Healthcare, with Illustrations in R," CEPA Working Papers Series WP052022, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uqcepa:177
    as

    Download full text from publisher

    File URL: https://economics.uq.edu.au/files/35634/WP052022.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Bayesian measurement of productivity and efficiency in the presence of undesirable outputs: crediting electric utilities for reducing air pollution," Journal of Econometrics, Elsevier, vol. 126(2), pages 445-468, June.
    2. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    3. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    4. Vitaliano, Donald F. & Toren, Mark, 1994. "Cost and efficiency in nursing homes: a stochastic frontier approach," Journal of Health Economics, Elsevier, vol. 13(3), pages 281-300, October.
    5. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Valentin Zelenyuk & Zhichao Wang, 2023. "Random vs. Explained Inefficiency in Stochastic Frontier Analysis: The Case of Queensland Hospitals," CEPA Working Papers Series WP052023, School of Economics, University of Queensland, Australia.
    2. Tsionas, Mike G. & Patel, Pankaj C., 2023. "Accounting for intra-industry technological heterogeneity in the measurement of operations efficiency," International Journal of Production Economics, Elsevier, vol. 260(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    2. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    3. Jin Yang & Hui Wang & Songqing Jin & Kevin Chen & Jeffrey Riedinger & Chao Peng, 2016. "Migration, local off-farm employment, and agricultural production efficiency: evidence from China," Journal of Productivity Analysis, Springer, vol. 45(3), pages 247-259, June.
    4. Sarmiento, Miguel & Galán, Jorge E., 2017. "The influence of risk-taking on bank efficiency: Evidence from Colombia," Emerging Markets Review, Elsevier, vol. 32(C), pages 52-73.
    5. Holtkamp, A.M. & Brummer, B., 2018. "Environmental efficiency of smallholder rubber production," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277518, International Association of Agricultural Economists.
    6. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    7. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    8. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    9. Andriakopoulos, Konstantinos & Ladas, Augoustinos & Andriakopoulos, Panagiotis, 2020. "Bank efficiency and leasing in U.S.A. banking system," MPRA Paper 112645, University Library of Munich, Germany.
    10. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    11. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.
    12. Tauer, Loren W. & Mishra, Ashok K., 2005. "U.S. Dairy Farm Cost Efficiency," Working Papers 127079, Cornell University, Department of Applied Economics and Management.
    13. Gangopadhyay, Partha & Jain, Siddharth & Bakry, Walid, 2022. "In search of a rational foundation for the massive IT boom in the Australian banking industry: Can the IT boom really drive relationship banking?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    14. Williams, Jonathan, 2004. "Determining management behaviour in European banking," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2427-2460, October.
    15. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    16. Guohua Feng & Chuan Wang & Apostolos Serletis, 2018. "Shadow prices of $$\hbox {CO}_{2}$$ CO 2 emissions at US electric utilities: a random-coefficient, random-directional-vector directional output distance function approach," Empirical Economics, Springer, vol. 54(1), pages 231-258, February.
    17. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    18. Antony Andrews & Omphile Temoso & Sean Kimpton, 2021. "Persistent and Transient Inefficiency of Australian States and Territories in Providing Public Hospital Services: An Application of Bayesian Stochastic Finite Mixture Frontier Analysis," Economic Papers, The Economic Society of Australia, vol. 40(2), pages 104-115, June.
    19. Subal Kumbhakar & Efthymios Tsionas, 2008. "Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks," Empirical Economics, Springer, vol. 34(3), pages 585-602, June.
    20. Wollni, Meike & Brümmer, Bernhard, 2012. "Productive efficiency of specialty and conventional coffee farmers in Costa Rica: Accounting for technological heterogeneity and self-selection," Food Policy, Elsevier, vol. 37(1), pages 67-76.

    More about this item

    Keywords

    Stochastic frontier analysis; R; healthcare; hospital; Queensland;
    All these keywords.

    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:177. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.