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Modeling Blank Data Entries in Data Envelopment Analysis

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  • Timo Kuosmanen

    (Wageningen University)

Abstract

We show how Data Envelopment Analysis (DEA) can handle missing data. When blank data entries are coded by appropriate dummy values, the DEA model automatically excludes the missing data from the analysis. We extend this result to weight-restricted DEA models by presenting a simple modification to the usual weight restrictions, which automatically relaxes the weight restriction in case of missing data. Our approach is illustrated by a case study, describing an application to international sustainable development indices.

Suggested Citation

  • Timo Kuosmanen, 2002. "Modeling Blank Data Entries in Data Envelopment Analysis," Econometrics 0210001, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0210001
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    1. 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.
    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. Laurens Cherchye & & Timo Kuosmanen, 2002. "Benchmarking Sustainable Development: A Synthetic Meta-index Approach," Others 0210001, University Library of Munich, Germany, revised 04 Dec 2002.
    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.
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    1. repec:ags:ijag24:345070 is not listed on IDEAS
    2. Laurens Cherchye & & Timo Kuosmanen, 2002. "Benchmarking Sustainable Development: A Synthetic Meta-index Approach," Others 0210001, University Library of Munich, Germany, revised 04 Dec 2002.
    3. Vilarinho, Hermilio & D’Inverno, Giovanna & Nóvoa, Henriqueta & Camanho, Ana S., 2023. "The measurement of asset management performance of water companies," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    4. Kristof Witte & Nicky Rogge, 2010. "To publish or not to publish? On the aggregation and drivers of research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 657-680, December.
    5. Laurens Cherchye & Wim Moesen & Tom Van Puyenbroeck, 2004. "Legitimately Diverse, yet Comparable: On Synthesizing Social Inclusion Performance in the EU," Journal of Common Market Studies, Wiley Blackwell, vol. 42(5), pages 919-955, December.
    6. Murat Bilsel & Nurhan Davutyan, 2014. "Hospital efficiency with risk adjusted mortality as undesirable output: the Turkish case," Annals of Operations Research, Springer, vol. 221(1), pages 73-88, October.
    7. Morais, Paulo & Camanho, Ana S., 2011. "Evaluation of performance of European cities with the aim to promote quality of life improvements," Omega, Elsevier, vol. 39(4), pages 398-409, August.
    8. Vilarinho, Hermilio & Pereira, Miguel Alves & D’Inverno, Giovanna & Nóvoa, Henriqueta & Camanho, Ana S., 2024. "Water Utility Service Quality Index: A customer-centred approach for assessing the quality of service in the water sector," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    9. A. Gelan & B.W. Muriithi, 2012. "Measuring and explaining technical efficiency of dairy farms: a case study of smallholder farms in East Africa," Agrekon, Taylor & Francis Journals, vol. 51(2), pages 53-74.
    10. Vilarinho, Hermilio & D’Inverno, Giovanna & Nóvoa, Henriqueta & Camanho, Ana S., 2023. "Performance analytics for regulation in retail water utilities: Guiding asset management by identifying peers and targets," Utilities Policy, Elsevier, vol. 82(C).
    11. Ya Chen & Yongjun Li & Huaqing Wu & Liang Liang, 2014. "Data Envelopment Analysis With Missing Data: A Multiple Linear Regression Analysis Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 137-153.
    12. Amado, Carla A.F. & São José, José M.S. & Santos, Sérgio P., 2016. "Measuring active ageing: A Data Envelopment Analysis approach," European Journal of Operational Research, Elsevier, vol. 255(1), pages 207-223.
    13. M. C. Portela & A. S. Camanho, 2007. "Performance Assessment of Portuguese Secondary Schools," Working Papers de Economia (Economics Working Papers) 07, Católica Porto Business School, Universidade Católica Portuguesa.

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    More about this item

    Keywords

    Data Envelopment Analysis; Weight Restrictions; Missing Data; Blank Entries;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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