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

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  • Chunping Liu
  • Audrey Laporte
  • Brian S. Ferguson

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.

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  • 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, September.
    • Handle: RePEc:wly:hlthec:v:17:y:2008:i:9:p:1073-1087
    DOI: 10.1002/hec.1398
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    6. Zhichao Wang & Valentin Zelenyuk, 2021. "Performance Analysis of Hospitals in Australia and its Peers: A Systematic Review," CEPA Working Papers Series WP012021, School of Economics, University of Queensland, Australia.
    7. Tsionas, Mike G. & Assaf, A. George & Andrikopoulos, Athanasios, 2020. "Quantile stochastic frontier models with endogeneity," Economics Letters, Elsevier, vol. 188(C).
    8. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    9. Darya Dancaková & Jozef Glova & Alena Andrejovská, 2021. "The Robust Efficiency Estimation in Lower Secondary Education: Cross-Country Evidence," Mathematics, MDPI, vol. 9(24), pages 1-15, December.
    10. Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
    11. Zhichao Wang & Bao Hoang Nguyen & Valentin Zelenyuk, 2024. "Performance analysis of hospitals in Australia and its peers: a systematic and critical review," Journal of Productivity Analysis, Springer, vol. 62(2), pages 139-173, October.
    12. Galina Besstremyannaya, 2014. "The efficiency of labor matching and remuneration reforms: a panel data quantile regression approach with endogenous treatment variables," Working Papers w0206, New Economic School (NES).
    13. 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 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 249280, African Association of Agricultural Economists (AAAE).
    14. Fengyi Lin & Yung-Jr Deng & Wen-Min Lu & Qian Long Kweh, 2019. "Impulse response function analysis of the impacts of hospital accreditations on hospital efficiency," Health Care Management Science, Springer, vol. 22(3), pages 394-409, September.
    15. 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).
    16. William C. Horrace & Christopher F. Parmeter & Ian A. Wright, 2024. "On asymmetry and quantile estimation of the stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 61(1), pages 19-36, February.
    17. Sakouvogui Kekoura & Shaik Saleem & Doetkott Curt & Magel Rhonda, 2021. "Sensitivity analysis of stochastic frontier analysis models," Monte Carlo Methods and Applications, De Gruyter, vol. 27(1), pages 71-90, March.
    18. 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.
    19. Besstremyannaya, Galina & Golovan, Sergei, 2021. "Measuring heterogeneity with fixed effect quantile regression: Long panels and short panels," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 70-82.
    20. 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.
    21. E. Fusco & R. Benedetti & F. Vidoli, 2023. "Stochastic frontier estimation through parametric modelling of quantile regression coefficients," Empirical Economics, Springer, vol. 64(2), pages 869-896, February.
    22. Zhang, Ning & Huang, Xuhui & Liu, Yunxiao, 2021. "The cost of low-carbon transition for China's coal-fired power plants: A quantile frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    23. 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.
    24. Monje, Juan Cabas & Sidhoum, Amer Ait & Gil, Jose M., 2021. "Investigating Technical Efficiency of Spanish Pig Farming: A Quantile Regression Approach," 2021 Conference, August 17-31, 2021, Virtual 315196, International Association of Agricultural Economists.

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