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基于非径向BML-DEA模型的中国地区工业环境绩效测度

机译:基于非径向BmL-DEa模型的中国地区工业环境绩效测度

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摘要

Combining the characteristics of BM direction distance function, non- radial DEA model and Luenberger productivity indicators, we develop a non-radial BML-DEA model to measure Environmental Performance. And by using the panel data of 30 provinces from 1997 to 2011 in China, we measure and analysis the regional industrial eco-efficiency. The results show that the overall growth of industrial Environmental Performance of the region comes mainly from technological progress rather than efficiency improvements, the highest average annual growth rate of areas are Beijing, Shanghai, Jiangsu and Guangdong. The effect from three pollutants on industrial Environmental Performance by descending is SO2, CO2 and Smoker, and the contribution of the three pollutants deal more balanced. There are significant differences among industrial Environmental Performance and its decomposition ingredients in different regions. The growth rate of industrial Environmental Performance in east is significantly higher than other regions, but the growth rate of efficiency is not superior to the center and west, and even slightly lower than the center. Therefore, regions need to enhance the efficiency in using the resources.
机译:结合BM方向距离函数,非径向DEA模型和​​Luenberger生产率指标的特征,我们开发了非径向BML-DEA模型来测量环境绩效。并利用1997年至2011年中国30个省的面板数据,对区域工业生态效率进行了测度和分析。结果表明,该地区工业环境绩效的总体增长主要来自技术进步而不是效率的提高,北京,上海,江苏和广东的年平均增长率最高。三种污染物对SO2,CO2和Smoke的影响对工业环境绩效的影响呈下降趋势,而这三种污染物的贡献更为平衡。不同地区的工业环境绩效及其分解成分之间存在显着差异。东部地区工业环境绩效的增长速度明显高于其他地区,但效率增长速度却不及中西部地区,甚至略低于中部地区。因此,区域需要提高资源利用效率。

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