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Partial frontier efficiency analysis

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  • Harald Tauchmann

    () (Rheinisch-Westfalisches Institut fur Wirtschaftsforschung (RWI))

Abstract

Despite their frequent use in applied work, nonparametric approaches to efficiency analysis-namely, data envelopment analysis and free disposal hull- have bad reputations among econometricians. This is mainly because data envelopment analysis and free disposal hull represent deterministic approaches that are highly sensitive to outliers and measurement errors. However, so-called partial frontier approaches have recently been developed, namely, order-m and order-α. These approaches generalize free disposal hull by allowing for superefficient observations to be located beyond the estimated production-possibility frontier. Although these methods are also purely nonparametric, the sensitivity to outliers is substantially reduced by partial frontier approaches enveloping just a subsample of observations. In this article, I introduce the new Stata commands orderm and orderalpha, which implement order-m, order-α, and free disposal hull efficiency analysis in Stata. The commands allow for several options, such as statistical inference based on subsampling bootstrapping.

Suggested Citation

  • Harald Tauchmann, 2012. "Partial frontier efficiency analysis," Stata Journal, StataCorp LP, vol. 12(3), pages 461-478, September.
  • Handle: RePEc:tsj:stataj:v:12:y:2012:i:3:p:461-478
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    References listed on IDEAS

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    1. Anatoly Pilyavsky & Matthias Staat, 2008. "Efficiency and productivity change in Ukrainian health care," Journal of Productivity Analysis, Springer, vol. 29(2), pages 143-154, April.
    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.
    3. Aragon, Y. & Daouia, A. & Thomas-Agnan, C., 2005. "Nonparametric Frontier Estimation: A Conditional Quantile-Based Approach," Econometric Theory, Cambridge University Press, vol. 21(02), pages 358-389, April.
    4. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    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.
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    1. repec:kap:hcarem:v:20:y:2017:i:3:d:10.1007_s10729-016-9359-1 is not listed on IDEAS
    2. Sandulli, Francesco D. & Baker, Paul M.A. & López-Sánchez, José I., 2013. "Can small and medium enterprises benefit from skill-biased technological change?," Journal of Business Research, Elsevier, vol. 66(10), pages 1976-1982.
    3. Diana Fernández Moreno & Dairo Estrada, 2013. "Colombian bank efficiency and the role of market structure," Temas de Estabilidad Financiera 076, Banco de la Republica de Colombia.
    4. Maria EL KHDARI & Babacar SARR, 2018. "Decentralization, spending efficiency and pro-poor outcomes in Morocco," Working Papers 201805, CERDI.
    5. repec:ebl:ecbull:eb-17-00556 is not listed on IDEAS
    6. Tankari, Mahamadou Roufahi, 2014. "Quelles zones cibler pour accroître l’efficacité agricole en Ouganda?," MPRA Paper 53396, University Library of Munich, Germany.
    7. Klaus Wohlrabe & Elisabeth Friedrich, 2017. "The efficiency of economics departments reconsidered," Economics Bulletin, AccessEcon, vol. 37(3), pages 1602-1611.
    8. Gosse Alserda & Jaap Bikker & Fieke van der Lecq, 2017. "X-efficiency and economies of scale in pension fund administration and investment," DNB Working Papers 547, Netherlands Central Bank, Research Department.
    9. repec:spr:annopr:v:244:y:2016:i:2:d:10.1007_s10479-016-2160-1 is not listed on IDEAS
    10. Jiri Schwarz & Martin Stepanek, 2016. "Patents: A Means to Innovation or Strategic Ends?," Working Papers IES 2016/08, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2016.

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