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Measuring the Green Efficiency of Ocean Economy in China: An Improved Three - Stage DEA Model

Author

Listed:
  • Lili DING

    (School of Economics, Ocean University of China, China.)

  • Haihong ZHENG

    (College of Economics and Management, Shandong University of Science and Technology, China.)

  • Wanglin KANG

    (College of Economics and Management, Shandong University of Science and Technology, China.)

Abstract

This paper aims to explore the true green efficiency of ocean economy in 11 coastal regions of China over 2004–2014. An extended three-stage DEA is proposed to improve the efficiency assessment of ocean economy. Malmquist–Luenberger productivity indexes are introduced into three-stage DEA model, which can simultaneously account for the impacts of undesirable outputs, environmental variables, and statistical noise. The results show that the environmental variables have significant impacts on regional ocean efficiency. Comparing with Malmquist productivity indexes, the average Malmquist–Luenberger productivity indexes of ocean economy have deteriorated over the past ten years. After eliminating the influences of environmental variables and statistical noise, the efficiency change and technical change of regional ocean economy are lower than the unadjusted case and technology inefficiency is the major cause of the inefficiency in China. Finally, a clustering matrix of the green efficiency of the regional ocean economy is presented to illustrate spatial refraction among 11coastal regions.

Suggested Citation

  • Lili DING & Haihong ZHENG & Wanglin KANG, 2017. "Measuring the Green Efficiency of Ocean Economy in China: An Improved Three - Stage DEA Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-22, March.
    • Handle: RePEc:rjr:romjef:v::y:2017:i:1:p:5-22
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    References listed on IDEAS

    as
    1. Avkiran, Necmi K. & Rowlands, Terry, 2008. "How to better identify the true managerial performance: State of the art using DEA," Omega, Elsevier, vol. 36(2), pages 317-324, April.
    2. Ching-Cheng Chang, 1999. "The Nonparametric Risk-Adjusted Efficiency Measurement: An Application to Taiwan's Major Rural Financial Intermediaries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 902-913.
    3. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    4. Po‐Chi Chen & Ming‐Miin Yu & Ching‐Cheng Chang & Shih‐Hsun Hsu, 2007. "Productivity change in Taiwan's farmers' credit unions: a nonparametric risk‐adjusted Malmquist approach," Agricultural Economics, International Association of Agricultural Economists, vol. 36(2), pages 221-231, March.
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    Citations

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    Cited by:

    1. ZHAO Xin & XUE Yue-mei & KANG Wang-lin & DING Li-li & ZHU Lin, 2018. "Measuring Efficiency of Ocean Economy in China Based on a Novel Luenberger Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-21, June.
    2. Zeng, Juying & Škare, Marinko & Lafont, Juan, 2021. "The co-integration identification of green innovation efficiency in Yangtze River Delta region," Journal of Business Research, Elsevier, vol. 134(C), pages 252-262.
    3. Jiandong Chen & Ping Wang & Jixian Zhou & Malin Song & Xinyue Zhang, 2022. "Influencing factors and efficiency of funds in humanitarian supply chains: the case of Chinese rural minimum living security funds," Annals of Operations Research, Springer, vol. 319(1), pages 413-438, December.
    4. Nano Prawoto & Agus Tri Basuki, 2020. "Effect of Macroeconomic Indicators and CO2 Emission on Indonesian Economic Growth," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 354-358.

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    More about this item

    Keywords

    ocean economy; three-stage DEA model; Malmquist-Luenberger index;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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