中国区域全要素能源效率收敛性及影响因素分析——基于Malmqulist-Luenberger指数法

Influential Factors and Convergence of Total Factor Energy Efficiency in China Based on the Malmqulist-Luenberger Index

本文将能源和非期望产出二氧化碳纳入生产率分析框架中,基于序列DEA的方向性距离函数及Malmqulist-Luenberger指数测度了1999年-2010年我国28个省、市、区及东、中、西三大区域的全要素能源效率的动态变化及其分解变量。实证结果表明:不考虑碳排放约束下的全要素能源效率被高估,而考虑碳排放约束后我国的产业结构得到了优化调整,呈现出规模效率的提升。从区域差异来看,1999年-2010年间我国三大区域全要素能源效率东部最高、中部次之、西部最低,其中西部区域其收敛速度要高于中部、及东部区域,各区域的全要素能源效率存在趋同的趋势。影响因素分析结果可知:我国2000年后经济发展与全要素能源效率指数呈现"U"型趋势;技术效应对中部,西部区域的全要素能源效率具有促进作用;产业结构的调整对中、西部区域的全要素能源效率有显著的抑制作用;对外开放度、产权所有制结构、政府支持力度对全国的全要素能源效率的有显著的促进作用,并且对中、西部的贡献比例较大。

With the rising demands for energy and the impact of energy consumption and CO_2 emissions on our environment and climate, sustainable economic development faces new challenges across China. In this paper, we use input and output panel data from 28 provinces and cities in China from 1999-2010, and based on the sequence DEA-Malmquist-Luenberger （ML） productivity index measure total factor energy efficiency by considering the constraints of CO_2 emissions and decomposition. We found that the average total factor energy efficiency follows a growing trend and that technological progress is the source of this improvement. Without considering constraints on CO_2 emissions total factor energy efficiency is overestimate; when the constraints of CO_2 emissions are considered, industrial structure is optimized and adjusted, showing improvements in scale efficiency. Total factor energy efficiency shows regional differences： the best performance is in the eastern region, then central, followed by western China. The change in technical efficiency in the central region is greatest; the scale efficiency in western China is improved after 2000, and the western region has a positive impact on industrial structure optimization and configuration. The innovation provinces such as Tianjin, Liaoning, Shanghai, Fujian and Yunnan play a promoting role in energy efficiency. Absolute β convergence test shows total factor energy efficiency has a significant convergence at the 1% level in three regions. The western region convergence rate is higher than the central and eastern regions and the western region exhibits a catch-up effect and convergence trend. Fixed-effects panel regression results shows that economic development and total factor energy efficiency follow a U trend. The adjustment of industrial structure on total factor energy efficiency has been significantly inhibited in the central and western regions, but impact on the eastern coastal cities is not significant. We conclude that as a rapidly developing country, China needs to transform its mode of economic growth, improve energy consumption structure and optimize industrial structure in the western regions in order to achieve sustainable growth of green GDP.