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Clustering in a Data Envelopment Analysis Using Bootstrapped Efficiency Scores

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  • Joseph G. Hirschberg
  • Jenny N. Lye

Abstract

This paper explores the insight from the application of cluster analysis to the results of a Data Envelopment Analysis of productive behaviour. Cluster analysis involves the identification of groups among a set of different objects (individuals or characteristics). This is done via the definitions of a distance matrix that defines the relationship between the different objects, which then allows the determination of which objects are most similar into clusters. In the case of DEA, cluster analysis methods can be used to determine the degree of sensitivity of the efficiency score for a particular DMU to the presence of the other DMUs in the sample that make up the reference technology to that DMU. Using the bootstrapped values of the efficiency measures we construct two types of distance matrices. One is defined as a function of the variance covariance matrix of the scores with respect to each other. This implies that the covariance of the score of one DMU is used as a measure of the degree to which the efficiency measure for a single DMU is influenced by the efficiency level of another. An alternative distance measure is defined as a function of the ranks of the bootstrapped efficiency. An example is provided using both measures as the clustering distance for both a one input one output case and a two input two output case.

Suggested Citation

  • Joseph G. Hirschberg & Jenny N. Lye, 2001. "Clustering in a Data Envelopment Analysis Using Bootstrapped Efficiency Scores," Department of Economics - Working Papers Series 800, The University of Melbourne.
    • Handle: RePEc:mlb:wpaper:800
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    References listed on IDEAS

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    1. J. G. Hirschberg, 2000. "Modelling time of day substitution using the second moments of demand," Applied Economics, Taylor & Francis Journals, vol. 32(8), pages 979-986.
    2. Uwe Jensen, 2000. "Is it efficient to analyse efficiency rankings?," Empirical Economics, Springer, vol. 25(2), pages 189-208.
    3. Gary Ferrier & Joseph Hirschberg, 1999. "Can We Bootstrap DEA Scores?," Journal of Productivity Analysis, Springer, vol. 11(1), pages 81-92, February.
    4. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    5. Mickael Lothgren & Magnus Tambour, 1999. "Bootstrapping the data envelopment analysis Malmquist productivity index," Applied Economics, Taylor & Francis Journals, vol. 31(4), pages 417-425.
    6. Joseph G. Hirschberg & Esfandiar Maasoumi & Daniel J. Slottje, 2001. "Clusters of attributes and well-being in the USA," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 445-460.
    7. Hirschberg, Joseph G. & Slottje, D. J., 1989. "Remembrance of things past the distribution of earnings across occupations and the kappa criterion," Journal of Econometrics, Elsevier, vol. 42(1), pages 121-130, September.
    8. Mei Xue & Patrick T. Harker, 1999. "Overcoming the Inherent Dependency of DEA Efficiency Scores: A Bootstrap Approach," Center for Financial Institutions Working Papers 99-17, Wharton School Center for Financial Institutions, University of Pennsylvania.
    9. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    10. Hirschberg, Joseph G. & Slottje, Daniel J., 1994. "An empirical Bayes approach to analyzing earnings functions for various occupations and industries," Journal of Econometrics, Elsevier, vol. 61(1), pages 65-79, March.
    11. Hirschberg, J.G. & Maasoumi, E. & Slottje, D.J., 1998. "The Environment and the Quality of Life in the United States Over Time," Department of Economics - Working Papers Series 654, The University of Melbourne.
    12. Gary Ferrier & Joseph Hirschberg, 1997. "Bootstrapping Confidence Intervals for Linear Programming Efficiency Scores: With an Illustration Using Italian Banking Data," Journal of Productivity Analysis, Springer, vol. 8(1), pages 19-33, March.
    13. 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.
    14. G.D. Ferrier & J. G. Hirschberg, 1992. "Climate Control Efficiency," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 37-54.
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    Cited by:

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    3. Yang Li & An-Chi Liu & Yi-Ying Yu & Yueru Zhang & Yiting Zhan & Wen-Cheng Lin, 2022. "Bootstrapped DEA and Clustering Analysis of Eco-Efficiency in China’s Hotel Industry," Sustainability, MDPI, vol. 14(5), pages 1-16, March.
    4. Kelly P. Murillo & Eugenio M. Rocha, 2020. "Factors Influencing the Economic Behavior of the Food, Beverages and Tobacco Industry: A Case Study for Portuguese Enterprises," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 6(2), pages 99-121, December.
    5. Fuad Aleskerov & Vsevolod Petrushchenko, 2016. "DEA by sequential exclusion of alternatives in heterogeneous samples," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 5-22, January.
    6. Dickens S Omondi Aduda & Collins Ouma & Rosebella Onyango & Mathews Onyango & Jane Bertrand, 2015. "Voluntary Medical Male Circumcision Scale-Up in Nyanza, Kenya: Evaluating Technical Efficiency and Productivity of Service Delivery," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-17, February.
    7. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2010. "Determining sources of relative inefficiency in heterogeneous samples: Methodology using Cluster Analysis, DEA and Neural Networks," European Journal of Operational Research, Elsevier, vol. 206(2), pages 479-487, October.
    8. Yang Li & An-Chi Liu & Shu-Mei Wang & Yiting Zhan & Jingran Chen & Hsiao-Fen Hsiao, 2022. "A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach," Energies, MDPI, vol. 15(9), pages 1-13, April.
    9. Hassan Najadat & Ahmad Alaiad & Sanaa Abu Alasal & Ghadeer Anwar Mrayyan & Izzat Alsmadi, 2020. "Integration of Data Envelopment Analysis and Clustering Methods," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-19, March.
    10. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.

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