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Data envelopment analysis with missing data

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  • T Kuosmanen

    (MTT Agrifood Research Finland)

Abstract

A first systematic attempt to use data containing missing values in data envelopment analysis (DEA) is presented. It is formally shown that allowing missing values into the data set can only improve estimation of the best-practice frontier. Technically, DEA can automatically exclude the missing data from the analysis if blank data entries are coded by appropriate numerical values.

Suggested Citation

  • T Kuosmanen, 2009. "Data envelopment analysis with missing data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1767-1774, December.
  • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:12:d:10.1057_jors.2008.132
    DOI: 10.1057/jors.2008.132
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    References listed on IDEAS

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    1. Kuosmanen, Timo, 2001. "DEA with efficiency classification preserving conditional convexity," European Journal of Operational Research, Elsevier, vol. 132(2), pages 326-342, July.
    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. Kuosmanen, Timo & Post, Thierry & Scholtes, Stefan, 2007. "Non-parametric tests of productive efficiency with errors-in-variables," Journal of Econometrics, Elsevier, vol. 136(1), pages 131-162, January.
    4. C Kao & S-Tai Liu, 2000. "Data envelopment analysis with missing data: an application to University libraries in Taiwan," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(8), pages 897-905, August.
    5. 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.
    6. Thierry Post & Laurens Cherchye & Timo Kuosmanen, 2002. "Nonparametric Efficiency Estimation In Stochastic Environments," Operations Research, INFORMS, vol. 50(4), pages 645-655, August.
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    Cited by:

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    3. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    4. Berna Haktanirlar Ulutas, 2011. "Assessing the Relative Performance of University Departments: Teaching vs. Research," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 13(1), pages 125-138, Special I.
    5. Kenneth Rødseth & Eirik Romstad, 2014. "Environmental Regulations, Producer Responses, and Secondary Benefits: Carbon Dioxide Reductions Under the Acid Rain Program," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 111-135, September.
    6. Ferreira, Diogo Cunha & Marques, Rui Cunha & Pedro, Maria Isabel, 2018. "Explanatory variables driving the technical efficiency of European seaports: An order-α approach dealing with imperfect knowledge," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 41-62.
    7. Zhu, Weiwei & Yu, Yu & Sun, Panpan, 2018. "Data envelopment analysis cross-like efficiency model for non-homogeneous decision-making units: The case of United States companies’ low-carbon investment to attain corporate sustainability," European Journal of Operational Research, Elsevier, vol. 269(1), pages 99-110.
    8. Marques, Rui Cunha & De Witte, Kristof, 2011. "Is big better? On scale and scope economies in the Portuguese water sector," Economic Modelling, Elsevier, vol. 28(3), pages 1009-1016, May.
    9. Ozana Nadoveza Jelic & Margareta Gardijan Kedzo, 2018. "Efficiency vs effectiveness: an analysis of tertiary education across Europe," Public Sector Economics, Institute of Public Finance, vol. 42(4), pages 381-414.

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