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Eco-efficiency and eco-productivity change over time in a multisectoral economic system

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  • Mahlberg, Bernhard
  • Luptacik, Mikulas

Abstract

We measure eco-efficiency of an economy by means of an augmented Leontief input–output model extended by constraints for primary inputs. Using a multi-objective optimisation model the eco-efficiency frontier of the economy is generated. The results of these multi-objective optimisation problems define eco-efficient virtual decision making units (DMUs). The eco-efficiency is obtained as a solution of a data envelopment analysis (DEA) model with virtual DMUs defining the potential and a DMU describing the actual performance of the economy. This procedure is then extended to an intertemporal approach in the spirit of the Luenberger productivity indicator. This indicator permits decomposing eco-productivity change into eco-efficiency change and eco-technical change. The indicator is then further decompounded in a way that enables us to examine the contributions of individual production factors, undesirable as well as desirable outputs to eco-productivity change over time. For illustration purposes the proposed model is applied to investigate eco-productivity growth of the Austrian economy.

Suggested Citation

  • Mahlberg, Bernhard & Luptacik, Mikulas, 2014. "Eco-efficiency and eco-productivity change over time in a multisectoral economic system," European Journal of Operational Research, Elsevier, vol. 234(3), pages 885-897.
  • Handle: RePEc:eee:ejores:v:234:y:2014:i:3:p:885-897 DOI: 10.1016/j.ejor.2013.11.017
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    Cited by:

    1. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2015. "Assessing environmental performance trends in the transport industry: Eco-innovation or catching-up?," Energy Economics, Elsevier, vol. 51(C), pages 570-580.
    2. repec:gam:jsusta:v:9:y:2017:i:9:p:1634-:d:112002 is not listed on IDEAS
    3. Zhang, Zibin & Ye, Jianliang, 2015. "Decomposition of environmental total factor productivity growth using hyperbolic distance functions: A panel data analysis for China," Energy Economics, Elsevier, vol. 47(C), pages 87-97.
    4. repec:gam:jsusta:v:9:y:2017:i:6:p:952-:d:100532 is not listed on IDEAS
    5. Yang, Fuxia & Yang, Mian, 2015. "Analysis on China's eco-innovations: Regulation context, intertemporal change and regional differences," European Journal of Operational Research, Elsevier, vol. 247(3), pages 1003-1012.
    6. Picazo-Tadeo, Andrés J. & Castillo-Giménez, Juana & Beltrán-Esteve, Mercedes, 2014. "An intertemporal approach to measuring environmental performance with directional distance functions: Greenhouse gas emissions in the European Union," Ecological Economics, Elsevier, vol. 100(C), pages 173-182.
    7. Juan Aparicio & Magdalena Kapelko & Bernhard Mahlberg & Jose L. Sainz-Pardo, 2017. "Measuring input-specific productivity change based on the principle of least action," Journal of Productivity Analysis, Springer, vol. 47(1), pages 17-31, February.
    8. Wang, Ke & Wei, Yi-Ming, 2016. "Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator," Energy Economics, Elsevier, vol. 54(C), pages 50-59.
    9. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    10. Ke Wang & Yujiao Xian & Yi-Ming Wei & Zhimin Huang, 2016. "Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function," CEEP-BIT Working Papers 91, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    11. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, pages 617-631.

    More about this item

    Keywords

    Data envelopment analysis; Luenberger indicator; Multi-objective optimisation; Neoclassical growth accounting;

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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