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Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach

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  • Wang, Qunwei
  • Su, Bin
  • Zhou, Peng
  • Chiu, Ching-Ren

Abstract

Implementing the “common but differentiated responsibilities” principle for CO2 mitigation requires an understanding of CO2 emission performance and technology gaps in different countries. This paper uses a meta-frontier and non-radial directional distance function to propose an alternative three stage approach to measure total-factor CO2 emission performance and technology gaps. The first stage calculates the CO2 emission performance of the group frontier. The second stage uses these results to calculate the technology gap ratio. The third stage integrates data from the first two stages to calculate CO2 emission performance under the meta-frontier. This approach is easier to apply than other approaches in the literature, and effectively avoids the phenomenon of the technology gap ratio being greater than unity. The proposed approach can also decompose CO2 emission performance loss into two categories: management inefficiency and technical gaps. To demonstrate the method, an empirical analysis using data for 54 countries was conducted. The study highlighted three main findings. First, upper-middle income countries did not perform as well as high income countries and lower-middle income countries. Second, high income countries generally enjoy optimized production technology, whereas the lower-middle income countries generally had the lowest technological levels. Third, both management inefficiency and technical gaps negatively impacted CO2 emission performance, but management inefficiency played a dominant role.

Suggested Citation

  • Wang, Qunwei & Su, Bin & Zhou, Peng & Chiu, Ching-Ren, 2016. "Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach," Energy Economics, Elsevier, vol. 56(C), pages 475-482.
  • Handle: RePEc:eee:eneeco:v:56:y:2016:i:c:p:475-482
    DOI: 10.1016/j.eneco.2016.04.005
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    Cited by:

    1. repec:spr:nathaz:v:92:y:2018:i:3:d:10.1007_s11069-018-3265-4 is not listed on IDEAS
    2. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    3. Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    4. Chen, Weidong & Geng, Wenxin, 2017. "Fossil energy saving and CO2 emissions reduction performance, and dynamic change in performance considering renewable energy input," Energy, Elsevier, vol. 120(C), pages 283-292.
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    6. Zhang, Cheng & Wang, Qunwei & Shi, Dan & Li, Pengfei & Cai, Wanhuan, 2016. "Scenario-based potential effects of carbon trading in China: An integrated approach," Applied Energy, Elsevier, vol. 182(C), pages 177-190.
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    More about this item

    Keywords

    CO2 emissions; Technology gap; Meta-frontier; Directional distance function;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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