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Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations

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  • Sueyoshi, Toshiyuki
  • Yuan, Yan

Abstract

This study discusses the new use of DEA (Data Envelopment Analysis) environmental assessment to measure MRT (Marginal Rate of Transformation) and RS (Rate of Substitution) among production factors (e.g., inputs, desirable and undesirable outputs). To measure the degree on MRT and RS, this study first examines a concept of disposability from the perspective of economic strategies to combat various environmental issues. The strategies are extendable to a policy change for pollution prevention. The underlying concept is separated into natural and managerial disposability. Under managerial disposability, it is possible for us to measure an occurrence of desirable congestion, or eco-technology innovation. Considering the disposability concept, this study discusses how to measure the type and magnitude of MRT and RS. A problem of the MRT & RS measurement is that these measures usually become unstable (e.g., very large or small in these magnitudes) because DEA does not assume any functional form for economic activities. To overcome such a difficulty, this study equips DEA environmental assessment with multiplier restriction by utilizing a unique feature on a proposed data treatment. The multiplier restriction in DEA has been never explored in previous works on environmental assessment. In an application, this study finds three important economic concerns on Europe and North America. First, Western Europe outperforms Eastern Europe and North America in their unified efficiency measures under managerial disposability. This study statistically confirms a difference between Western and Eastern Europe, but not between Western Europe and North America. This result exhibits that Eastern Europe is not yet well developed at the level of the other two regions. Second, Eastern Europe has exhibited MRT estimates that are different from Western Europe and North America. The nations in Eastern Europe have an economic potential for industrial developments because the level of their industrial pollutions is less than that of the other two regions. The potential is also found in their MRT estimates. Finally, an interesting difference can be found in the RS estimate between Eastern Europe and Western Europe from 2008 to 2012. They have statistically exhibited a difference between the two regimes, but not with North America. This is because most nations in both Western Europe and North America have already attained a high level of economic successes so that they have a limited industrial potential under current production technology and eco-technology. The situation of the two regions will be changed along with new technology development. In contrast, Eastern Europe is different from the other two regions in terms of attaining such a level of social sustainability because of limited capital accumulation and limited opportunity for technology innovation.

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  • Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Marginal Rate of Transformation and Rate of Substitution measured by DEA environmental assessment: Comparison among European and North American nations," Energy Economics, Elsevier, vol. 56(C), pages 270-287.
  • Handle: RePEc:eee:eneeco:v:56:y:2016:i:c:p:270-287
    DOI: 10.1016/j.eneco.2016.01.017
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    Cited by:

    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Toshiyuki Sueyoshi & Yan Yuan & Aijun Li & Daoping Wang, 2017. "Social Sustainability of Provinces in China: A Data Envelopment Analysis (DEA) Window Analysis under the Concepts of Natural and Managerial Disposability," Sustainability, MDPI, vol. 9(11), pages 1-18, November.
    3. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
    4. Sueyoshi, Toshiyuki & Yuan, Yan, 2016. "Returns to damage under undesirable congestion and damages to return under desirable congestion measured by DEA environmental assessment with multiplier restriction: Economic and energy planning for s," Energy Economics, Elsevier, vol. 56(C), pages 288-309.
    5. Toshiyuki Sueyoshi & Mika Goto, 2019. "DEA Non-Radial Approach for Resource Allocation and Energy Usage to Enhance Corporate Sustainability in Japanese Manufacturing Industries," Energies, MDPI, vol. 12(9), pages 1-22, May.
    6. Anyu Yu & Guangshe Jia & Jianxin You & Puwei Zhang, 2018. "Estimation of PM 2.5 Concentration Efficiency and Potential Public Mortality Reduction in Urban China," IJERPH, MDPI, vol. 15(3), pages 1-19, March.
    7. Sueyoshi, Toshiyuki & Goto, Mika & Wang, Derek, 2017. "Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces," Energy Economics, Elsevier, vol. 67(C), pages 554-571.
    8. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    9. Sueyoshi, Toshiyuki & Wang, Derek, 2018. "DEA environmental assessment on US petroleum industry: Non-radial approach with translation invariance in time horizon," Energy Economics, Elsevier, vol. 72(C), pages 276-289.
    10. Aizhen Zhang & Aijun Li & Yaping Gao, 2018. "Social Sustainability Assessment across Provinces in China: An Analysis of Combining Intermediate Approach with Data Envelopment Analysis (DEA) Window Analysis," Sustainability, MDPI, vol. 10(3), pages 1-24, March.
    11. Yang, Jun & Cheng, Jixin & Zou, Ran & Geng, Zhifei, 2021. "Industrial SO2 technical efficiency, reduction potential and technology heterogeneities of China's prefecture-level cities: A multi-hierarchy meta-frontier parametric approach," Energy Economics, Elsevier, vol. 104(C).
    12. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    13. Sueyoshi, Toshiyuki & Yuan, Yan & Li, Aijun & Wang, Daoping, 2017. "Methodological comparison among radial, non-radial and intermediate approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 67(C), pages 439-453.
    14. A. Ghazi & F. Hosseinzadeh Lotfi, 2023. "Marginal rates in DEA using defining hyperplanes of PPS with CRS technology," Operational Research, Springer, vol. 23(1), pages 1-37, March.
    15. Sueyoshi, Toshiyuki & Wang, Derek, 2017. "Measuring scale efficiency and returns to scale on large commercial rooftop photovoltaic systems in California," Energy Economics, Elsevier, vol. 65(C), pages 389-398.
    16. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    17. Halkos, George & Bampatsou, Christina, 2016. "Investigating the effect of efficiency and technical changes on productivity," MPRA Paper 76287, University Library of Munich, Germany.
    18. Zurano-Cervelló, Patricia & Pozo, Carlos & Mateo-Sanz, Josep María & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2019. "Sustainability efficiency assessment of the electricity mix of the 28 EU member countries combining data envelopment analysis and optimized projections," Energy Policy, Elsevier, vol. 134(C).

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    Keywords

    DEA environmental assessment; Marginal rate of transformation; Rate of substitution;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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