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A hybrid approach to efficiency measurement with empirical illustrations from education and health

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  • Wagstaff, Adam
  • Wang, L. Choon

Abstract

Inefficiency is commonplace, yet exercises aimed at improving provider performance efforts to date to measure inefficiency and use it in benchmarking exercises have not been altogether satisfactory. This paper proposes a new approach that blends the themes of Data Envelopment Analysis and the Stochastic Frontier Approach to measure overall efficiency. The hybrid approach nonparametrically estimates inefficiency by comparing actual performance with comparable real-life"best practice"on the frontier and could be useful in exercises aimed at improving provider performance. Four applications in the education and health sectors are used to illustrate the features and strengths of this hybrid approach.

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Bibliographic Info

Paper provided by The World Bank in its series Policy Research Working Paper Series with number 5751.

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Date of creation: 01 Aug 2011
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Handle: RePEc:wbk:wbrwps:5751

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Related research

Keywords: Health Monitoring&Evaluation; Health Systems Development&Reform; Tertiary Education; Disease Control&Prevention; Education For All;

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References

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  1. António Afonso & Miguel St. Aubyn, 2005. "Non-parametric approaches to education and health efficiency in OECD countries," Journal of Applied Economics, Universidad del CEMA, vol. 0, pages 227-246, November.
  2. Unto Häkkinen & Isabelle Joumard, 2007. "Cross-Country Analysis of Efficiency in OECD Health Care Sectors: Options for Research," OECD Economics Department Working Papers 554, OECD Publishing.
  3. Andrew Worthington, 2001. "An Empirical Survey of Frontier Efficiency Measurement Techniques in Education," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 245-268.
  4. Fuchs, Thomas & Wößmann, Ludger, 2007. "What accounts for international differences in student performance? A re-examination using PISA data," Munich Reprints in Economics 20303, University of Munich, Department of Economics.
  5. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  6. Bruce Hollingsworth & Andrew Street, 2006. "The market for efficiency analysis of health care organisations," Health Economics, John Wiley & Sons, Ltd., vol. 15(10), pages 1055-1059.
  7. Crampes, C. & Hollander, A., 1992. "Duopoly and Quality Standards," Papers 92.g, Toulouse - GREMAQ.
  8. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
  9. Deller, Steven C. & Rudnicki, Edward, 1993. "Production efficiency in elementary education: The case of Maine public schools," Economics of Education Review, Elsevier, vol. 12(1), pages 45-57, March.
  10. Edwin Leuven & Barbara Sianesi, 2003. "PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing," Statistical Software Components S432001, Boston College Department of Economics, revised 12 Feb 2014.
  11. Andreas Ammermueller, 2007. "PISA: What makes the difference?," Empirical Economics, Springer, vol. 33(2), pages 263-287, September.
  12. Weaver, Marcia & Deolalikar, Anil, 2004. "Economies of scale and scope in Vietnamese hospitals," Social Science & Medicine, Elsevier, vol. 59(1), pages 199-208, July.
  13. Bruce Hollingsworth, 2008. "The measurement of efficiency and productivity of health care delivery," Health Economics, John Wiley & Sons, Ltd., vol. 17(10), pages 1107-1128.
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Cited by:
  1. World Bank, 2011. "Saber - School Finance Objectives and Conceptual Approach," World Bank Other Operational Studies 12560, The World Bank.
  2. Emiliana Vegas & Chelsea Coffin, 2012. "Education Finance : It's How, Not Simply How Much, That Counts," World Bank Other Operational Studies 10056, The World Bank.

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