Abstract
At present, the contradiction between economic development and resource and environmental sustainability has become increasingly acute in China. Improving the quality of the ecological environment has become an important strategic goal for China’s national economic and social development. In this paper, we used the panel data of 30 provinces in China from 1986 to 2016 to measure the eco-efficiency and its decomposition indexes based on a non-radial metafrontier Malmquist-Luenberger data envelopment analysis model. The results showed that the eco-efficiency grows at an annual rate of 0.7% on the whole, with the technical efficiency decreasing at an annual rate of 0.6%, the innovation effect increasing at an annual rate of 2.3%, and the technical leadership effect decreasing at an annual rate of 1%. In the sample study period, the cumulative growth rates of eco-efficiency change index, technical efficiency change index, innovation effect, and technical leadership effect were 20.4%, − 19.4%, 70.5%, and − 30.7%, respectively. It was also found that regional eco-efficiency decreased from east to west. Furthermore, convergence test results showed that there were four convergence clubs and three divergent individuals in terms of eco-efficiency. Areas with high eco-efficiency tended to converge with areas with high eco-efficiency and vice versa.
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Notes
For eases of expression, the distance function \( \overrightarrow{\mathrm{D}}\left(v,\boldsymbol{p};-\boldsymbol{p}\right) \) was expressed as \( \overrightarrow{\mathrm{D}}\left(v,\boldsymbol{p}\right) \).
Eastern provinces are Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan; central provinces are Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Guangxi, and Hunan; western provinces are Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang.
Through the Monte Carlo simulation experiment, PS (2007) recommended that r = 0.3 be an appropriate choice when T < 50.
It is to note that all the eco-efficiency is less than one, and its absolute value will grow larger with low eco-efficiency after taking the logarithm, so that we have seen hit decreasing with higher eco-efficiency in clubs (or individuals) and increasing with lower eco-efficiency in clubs (or individuals).
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Funding
We acknowledge the financial support from the Social Science Foundation of Hunan Province (No. 16YBA284), Social Science Foundation of Zhuzhou (No. ZZSK19152), and National Natural Science Foundation of Hunan Province (No. 2018JJ3353, No. 2019JJ50131), Social Science Achievement Evaluation Committee Foundation of Hunan Province (No. XSP20YBC347), Humanity and Social Science Foundation of Ministry of Education of China (No. 20YJCZH145, No. 17YJCZH195), China Scholarship Conncil (No. 201906725035).
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Tang, J., Tang, L., Li, Y. et al. Measuring eco-efficiency and its convergence: empirical analysis from China. Energy Efficiency 13, 1075–1087 (2020). https://doi.org/10.1007/s12053-020-09859-3
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DOI: https://doi.org/10.1007/s12053-020-09859-3