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Nonparametric measures of efficiency in the presence of undesirable outputs: a by-production approach

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  • Subhash C. Ray

    (University of Connecticut)

  • Kankana Mukherjee

    (Babson College)

  • Anand Venkatesh

    (Institute of Rural Management)

Abstract

In empirical research on productivity measurement adjusted for undesirable outputs on the side, the good and the bad outcomes are treated as joint products of the underlying production process. In the present paper, following Murty, Russell, and Levkoff, we conceptualize the good output as technologically separable from the bad output. Joint disposability is assumed between the bad output and the polluting input, rather than weak disposability and null jointness between the good and bad outputs. Moreover, we set up an integrated DEA optimization problem over the intersection of these two subtechnologies to measure the efficiency of a firm that produces a bad output alongside the good output. In an empirical illustration of our methodology, we use country-level data for an unbalanced panel of 64 countries over the years 1986 through 2011 where per capita GDP is the good and per capita $$\hbox {CO}_{2}$$ CO 2 emission is the bad output. We then utilize our DEA results to compute opportunity costs of a targeted reduction in $$\hbox {CO}_{2}$$ CO 2 emission in terms of required dollar amounts of reduction in per capita GDP for the individual countries in selected years.

Suggested Citation

  • Subhash C. Ray & Kankana Mukherjee & Anand Venkatesh, 2018. "Nonparametric measures of efficiency in the presence of undesirable outputs: a by-production approach," Empirical Economics, Springer, vol. 54(1), pages 31-65, February.
  • Handle: RePEc:spr:empeco:v:54:y:2018:i:1:d:10.1007_s00181-017-1234-5
    DOI: 10.1007/s00181-017-1234-5
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    References listed on IDEAS

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    Cited by:

    1. Andreas Eder, 2022. "Environmental efficiency measurement when producers control pollutants under heterogeneous conditions: a generalization of the materials balance approach," Journal of Productivity Analysis, Springer, vol. 57(2), pages 157-176, April.
    2. Shen, Zhiyang & Wu, Haitao & Bai, Kaixuan & Hao, Yu, 2022. "Integrating economic, environmental and societal performance within the productivity measurement," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.
    4. Aparicio, Juan & Kapelko, Magdalena & Zofío, José L., 2020. "The measurement of environmental economic inefficiency with pollution-generating technologies," Resource and Energy Economics, Elsevier, vol. 62(C).
    5. Chuang Li & Subhash C. Ray, 2021. "Opportunity Cost and Employment Effect of Emission Reduction: An Inter-Industry Comparison of Targeted Pollution Reduction," Working papers 2021-13, University of Connecticut, Department of Economics.
    6. Sushama Murty & Resham Nagpal, "undated". "Choice of models for emission-generating technologies and designing technical efficiency improvements," Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi Discussion Papers 19-01, Centre for International Trade and Development, Jawaharlal Nehru University, New Delhi, India.
    7. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
    8. Fukuyama, Hirofumi & Tan, Yong, 2022. "Implementing strategic disposability for performance evaluation: Innovation, stability, profitability and corporate social responsibility in Chinese banking," European Journal of Operational Research, Elsevier, vol. 296(2), pages 652-668.
    9. repec:zbw:inwedp:752021 is not listed on IDEAS
    10. Fang, Lei, 2020. "Opening the “black box” of environmental production technology in a nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 769-780.
    11. Jean-Philippe Boussemart & Hervé Leleu & Zhiyang Shen & Vivian Valdmanis, 2020. "Performance analysis for three pillars of sustainability," Journal of Productivity Analysis, Springer, vol. 53(3), pages 305-320, June.
    12. Andreas Eder, 2021. "Environmental efficiency measurement when producers control pollutants under heterogeneous conditions: a generalization of the materials balance approach," Working Papers 752021, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    13. Sushama Murty & R. Robert Russell, 2021. "A commentary on “Performance measurement and joint production of intended and unintended outputs” by Finn Førsund," Journal of Productivity Analysis, Springer, vol. 55(3), pages 177-184, June.
    14. West, Steele, 2021. "The Estimation of Farm Business Inefficiency in the Presence of Debt Repayment," 2021 Conference, August 17-31, 2021, Virtual 315048, International Association of Agricultural Economists.
    15. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    16. Fukuyama, Hirofumi & Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2021. "Measuring the capacity utilization of the 48 largest iron and steel enterprises in China," European Journal of Operational Research, Elsevier, vol. 288(2), pages 648-665.

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    More about this item

    Keywords

    Bad output; Weak disposability; Null jointness; By-production; Joint disposability;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects

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