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Non-Radial Directional Performance Measurement with Undesirable Outputs

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  • Chen, Po-Chi
  • Yu, Ming-Miin
  • Chang, Ching-Cheng
  • Managi, Shunsuke

Abstract

The objective of this paper is to provide a comprehensive efficiency measures to estimate the performances of OECD and non-OECD countries. A Russell directional distance function that appropriately credits the decision making unit not only for increase in desirable outputs but also for the decrease of undesirable outputs is derived from the proposed weighted Russell directional distance model. The method was applied to a panel of 99 countries over 1991 and 2003. This framework also decomposes the comprehensive efficiency measure into individual input/output components’ inefficiency scores that are useful for policy making. The results reveal that the OECD countries perform better than the non-OECD countries in overall, goods, labor and capital efficiencies, but worse in bad and energy efficiencies.

Suggested Citation

  • Chen, Po-Chi & Yu, Ming-Miin & Chang, Ching-Cheng & Managi, Shunsuke, 2014. "Non-Radial Directional Performance Measurement with Undesirable Outputs," MPRA Paper 57189, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:57189
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    1. Rolf Färe & Shawna Grosskopf & Gerald Whittaker, 2014. "Network DEA II," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 307-327, Springer.
    2. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    3. Ray, Subhash C. & Jeon, Yongil, 2008. "Reputation and efficiency: A non-parametric assessment of America's top-rated MBA programs," European Journal of Operational Research, Elsevier, vol. 189(1), pages 245-268, August.
    4. 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.
    5. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    6. W. Cooper & L. Seiford & K. Tone & J. Zhu, 2007. "Some models and measures for evaluating performances with DEA: past accomplishments and future prospects," Journal of Productivity Analysis, Springer, vol. 28(3), pages 151-163, December.
    7. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    8. tone, Kaoru, 2010. "Variations on the theme of slacks-based measure of efficiency in DEA," European Journal of Operational Research, Elsevier, vol. 200(3), pages 901-907, February.
    9. Taskin, Fatma & Zaim, Osman, 2001. "The role of international trade on environmental efficiency: a DEA approach," Economic Modelling, Elsevier, vol. 18(1), pages 1-17, January.
    10. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    11. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    12. Timo Kuosmanen & Victor Podinovski, 2008. "Weak Disposability in Nonparametric Production Analysis: Reply to Färe and Grosskopf," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(2), pages 539-545.
    13. Seiford, Lawrence M. & Zhu, Joe, 1999. "An investigation of returns to scale in data envelopment analysis," Omega, Elsevier, vol. 27(1), pages 1-11, February.
    14. Byung M. Jeon & Robin C. Sickles, 2004. "The role of environmental factors in growth accounting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 567-591.
    15. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    16. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    17. Ruggiero, John & Bretschneider, Stuart, 1998. "The weighted Russell measure of technical efficiency," European Journal of Operational Research, Elsevier, vol. 108(2), pages 438-451, July.
    18. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    19. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    20. Smith, P, 1990. "Data envelopment analysis applied to financial statements," Omega, Elsevier, vol. 18(2), pages 131-138.
    21. Liu, Junming & Tone, Kaoru, 2008. "A multistage method to measure efficiency and its application to Japanese banking industry," Socio-Economic Planning Sciences, Elsevier, vol. 42(2), pages 75-91, June.
    22. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    23. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties," European Journal of Operational Research, Elsevier, vol. 196(2), pages 764-794, July.
    24. Zhou, Peng & Poh, Kim Leng & Ang, Beng Wah, 2007. "A non-radial DEA approach to measuring environmental performance," European Journal of Operational Research, Elsevier, vol. 178(1), pages 1-9, April.
    25. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    26. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    27. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    28. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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    Cited by:

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    2. María Molinos-Senante & Ramon Sala-Garrido, 2017. "Decomposition of Productivity Growth of Water and Sewerage Companies: An Empirical Approach for Chile," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(13), pages 4309-4321, October.
    3. María Molinos-Senante & Manuel Mocholi-Arce & Ramón Sala-Garrido, 2016. "Efficiency Assessment of Water and Sewerage Companies: a Disaggregated Approach Accounting for Service Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4311-4328, September.
    4. Hidemichi Fujii & Jing Cao & Shunsuke Managi, 2015. "Decomposition of Productivity Considering Multi-environmental Pollutants in Chinese Industrial Sector," Review of Development Economics, Wiley Blackwell, vol. 19(1), pages 75-84, February.
    5. Wei, Chu & Löschel, Andreas & Liu, Bing, 2015. "Energy-saving and emission-abatement potential of Chinese coal-fired power enterprise: A non-parametric analysis," Energy Economics, Elsevier, vol. 49(C), pages 33-43.
    6. Nabavieh, Alireza & Gholamiangonabadi, Davoud & Ahangaran, Ali Asghar, 2015. "Dynamic changes in CO2 emission performance of different types of Iranian fossil-fuel power plants," Energy Economics, Elsevier, vol. 52(PA), pages 142-150.
    7. Halkos, George & Petrou, Kleoniki Natalia, 2019. "Treating undesirable outputs in DEA: A critical review," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 97-104.
    8. Arocena, Pablo & Cabasés, Fermín & Pascual, Pedro, 2022. "A centralized directional distance model for efficient and horizontally equitable grants allocation to local governments," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    9. José Antonio Palomero-González & Vicent Almenar-Llongo & Ramón Fuentes-Pascual, 2021. "Evaluating the Efficiency of Water Distribution Network Sectors Using the DEA-Weight Russell Directional Distance Model: The Case of the City of Valencia (Spain)," Sustainability, MDPI, vol. 13(19), pages 1-21, September.
    10. Christian Hernández-Guedes & Jorge V Pérez-Rodríguez & Casiano Manrique-de-Lara-Peñate, 2024. "Input inefficiencies in the hotel industry. A non-radial directional performance measurement," Tourism Economics, , vol. 30(7), pages 1753-1779, November.
    11. Rebai, Sonia & Ben Yahia, Fatma & Essid, Hédi, 2020. "A graphically based machine learning approach to predict secondary schools performance in Tunisia," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    12. Halkos, George & Petrou, Kleoniki Natalia, 2018. "A critical review of the main methods to treat undesirable outputs in DEA," MPRA Paper 90374, University Library of Munich, Germany.

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    More about this item

    Keywords

    data envelopment analysis; directional distance function; undesirable output; Russell measure; slacks-based model;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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