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Measuring Carbon Emissions Performance in 123 Countries: Application of Minimum Distance to the Strong Efficiency Frontier Analysis

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  • Ling Wang

    ()
    (School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China)

  • Zhongchang Chen

    ()
    (School of Public Affairs, Chongqing University, Chongqing, 400044, China)

  • Dalai Ma

    ()
    (School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China)

  • Pei Zhao

    ()
    (School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China)

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    Abstract

    In this paper, we have proposed a general approach to obtain a projection of the nearest targets and minimum distance for a given unit. The method takes undesirable output into account. The idea behind it is that nearest targets and minimum distance lead to less variation in inputs and outputs of the inefficient decision making units (DMUs) being evaluated to reach the production possibility set (PPS) frontier. Our results have shown that the carbon emissions comprehensive performance indexes (CECPIs) of developing countries are lower than those of developed countries, and that the inefficiency shares of energy consumption, capital stock and desirable output are declining while those of labor force and undesirable output are climbing. Further, using cluster analysis, we have shown that nine countries, including Ukraine, Kazakhstan, Uzbekistan and Iraq, should take severe measures to save energy and reduce carbon emissions. Moreover, the gap in CECPIs among the 123 countries is narrowing by kernel density estimation.

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    Bibliographic Info

    Article provided by MDPI, Open Access Journal in its journal Sustainability.

    Volume (Year): 5 (2013)
    Issue (Month): 12 (December)
    Pages: 5319-5332

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    Handle: RePEc:gam:jsusta:v:5:y:2013:i:12:p:5319-5332:d:31146

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    Related research

    Keywords: carbon emissions efficiency; minimum distance to the strong efficiency frontier; kernel density estimation; cluster analysis; data envelopment analysis;

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    References

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    1. Stephen Casler & Adam Rose, 1998. "Carbon Dioxide Emissions in the U.S. Economy: A Structural Decomposition Analysis," Environmental & Resource Economics, European Association of Environmental and Resource Economists, European Association of Environmental and Resource Economists, vol. 11(3), pages 349-363, April.
    2. Grossman, Gene M & Krueger, Alan B, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 110(2), pages 353-77, May.
    3. Justin Tevie & Kristine M. Grimsrud & Robert P. Berrens, 2011. "Testing the Environmental Kuznets Curve Hypothesis for Biodiversity Risk in the US: A Spatial Econometric Approach," Sustainability, MDPI, Open Access Journal, MDPI, Open Access Journal, vol. 3(11), pages 2182-2199, November.
    4. ZhongXiang Zhang, 1996. "Macroeconomic Effects of CO2 Emission Limits: A Computable General Equilibrium Analysis for China," Mansholt Working Papers, Wageningen University, Mansholt Graduate School of Social Sciences 01-96, Wageningen University, Mansholt Graduate School of Social Sciences.
    5. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, Elsevier, vol. 60(1), pages 111-118, November.
    6. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, Elsevier, vol. 32(1), pages 194-201, January.
    7. G. R. Jahanshahloo & J. Vakili & M. Zarepisheh, 2012. "A Linear Bilevel Programming Problem For Obtaining The Closest Targets And Minimum Distance Of A Unit From The Strong Efficient Frontier," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1250011-1-1.
    8. Wang, Ke & Lu, Bin & Wei, Yi-Ming, 2013. "China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis," Applied Energy, Elsevier, Elsevier, vol. 112(C), pages 1403-1415.
    9. Juan Aparicio & José Ruiz & Inmaculada Sirvent, 2007. "Closest targets and minimum distance to the Pareto-efficient frontier in DEA," Journal of Productivity Analysis, Springer, Springer, vol. 28(3), pages 209-218, December.
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