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The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations

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  • Chunping Liu

    (Department of Economics, University of Guelph, Guelph, Ont., Canada)

  • Audrey Laporte

    (Department of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ont., Canada)

  • Brian S. Ferguson

    (Department of Economics, University of Guelph, Guelph, Ont., Canada)

Abstract

In the health economics literature there is an ongoing debate over approaches used to estimate the efficiency of health systems at various levels, from the level of the individual hospital - or nursing home - up to that of the health system as a whole. The two most widely used approaches to evaluating the efficiency with which various units deliver care are non-parametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Productivity researchers tend to have very strong preferences over which methodology to use for efficiency estimation. In this paper, we use Monte Carlo simulation to compare the performance of DEA and SFA in terms of their ability to accurately estimate efficiency. We also evaluate quantile regression as a potential alternative approach. A Cobb-Douglas production function, random error terms and a technical inefficiency term with different distributions are used to calculate the observed output. The results, based on these experiments, suggest that neither DEA nor SFA can be regarded as clearly dominant, and that, depending on the quantile estimated, the quantile regression approach may be a useful addition to the armamentarium of methods for estimating technical efficiency. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Chunping Liu & Audrey Laporte & Brian S. Ferguson, 2008. "The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1073-1087.
  • Handle: RePEc:wly:hlthec:v:17:y:2008:i:9:p:1073-1087
    DOI: 10.1002/hec.1398
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    References listed on IDEAS

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    1. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
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    8. Gong, Byeong-Ho & Sickles, Robin C., 1992. "Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 259-284.
    9. Banker, Rajiv D. & Chang, Hsihui & Cooper, William W., 2004. "A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 153(3), pages 624-640, March.
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    Cited by:

    1. Kiplimo, L.B. & Ngeno, V., 2016. "Understanding the Effect of Land Fragmentation on Farm Level Efficiency: An Application of Quantile Regression-Based Thick Frontier Approach to Maize Production in Kenya," 2016 AAAE Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 249280, African Association of Agricultural Economists (AAAE).
    2. Galina Besstremyannaya, 2014. "The efficiency of labor matching and remuneration reforms: a panel data quantile regression approach with endogenous treatment variables," Working Papers w0206, Center for Economic and Financial Research (CEFIR).
    3. Berndt, Antje & Hollifield, Burton & Sandås, Patrik, 2017. "What Broker Charges Reveal about Mortgage Credit Risk," Working Paper Series 336, Sveriges Riksbank (Central Bank of Sweden).
    4. Galina Besstremyannaya, 2015. "Heterogeneous effect of residency matching and prospective payment on labor returns and hospital scale economies," Discussion Papers 15-001, Stanford Institute for Economic Policy Research.
    5. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    6. Varabyova, Yauheniya & Müller, Julia-Maria, 2016. "The efficiency of health care production in OECD countries: A systematic review and meta-analysis of cross-country comparisons," Health Policy, Elsevier, vol. 120(3), pages 252-263.
    7. Martin, Cécile, 2014. "Concurrence, prix et qualité de la prise en charge en EHPAD en France : Analyses micro-économétriques," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/13712 edited by Dormont, Brigitte, December.

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