CAJ | 학술논문

本文运用基于共同前沿分析框架的Metafrontier．Malmquist．Luenberger指数，测度了能源与碳排放约束下地区工业绿色TFP指数及其分解成分的动态变化，结果显示：（1）地区工业绿色TFP整体上呈现不断增长的趋势，但东部省区工业绿色TFP指数高于中部与西部省区，工业低碳生产技术的地区差距整体上呈现先扩大后缩小的趋势，尤其是2004年以来，西部工业低碳生产技术水平已经超越中部；（2）东部地区工业绿色TFP增长对工业增长的贡献率显著高于中部与西部地区，地区工业绿色TFP增长动力主要来自技术进步，技术效率整体上拖累了绿色TFP增长，在发挥技术进步对地区工业低碳转型的促进作用的同时，更需要重视技术效率改进对工业低碳转型的积极作用；（3）东部省区工业绿色TFP增长表现出俱乐部收敛特征，中部与西部省区工业绿色TFP增长只显示条件β收敛，需要因地制宜地推进低碳工业转型。
본문운용기우공동전연분석광가적Metafrontier．Malmquist．Luenberger지수，측도료능원여탄배방약속하지구공업록색TFP지수급기분해성분적동태변화，결과현시：（1）지구공업록색TFP정체상정현불단증장적추세，단동부성구공업록색TFP지수고우중부여서부성구，공업저탄생산기술적지구차거정체상정현선확대후축소적추세，우기시2004년이래，서부공업저탄생산기술수평이경초월중부；（2）동부지구공업록색TFP증장대공업증장적공헌솔현저고우중부여서부지구，지구공업록색TFP증장동력주요래자기술진보，기술효솔정체상타루료록색TFP증장，재발휘기술진보대지구공업저탄전형적촉진작용적동시，경수요중시기술효솔개진대공업저탄전형적적겁작용；（3）동부성구공업록색TFP증장표현출구악부수렴특정，중부여서부성구공업록색TFP증장지현시조건β수렴，수요인지제의지추진저탄공업전형。
Industrial sectors occupy an important position in China＇s economic growth, energy consumption and carbon emissions and show obviously extensive growth characteristics. In response to global climate change and transformation of economic growing mode, China＇s industrial growth must steer from input-driven mode to innovation- driven mode, enhance the contribution of green TFP growth to industrial growth, and make green TFP growth play a central role in the low-carbon industrial transition. Total factor productivity （TFP） growth has been the academic focus, but the traditional TFP calculation method has two drawbacks. Firstly, it does not consider the impact of undesirable outputs such as environmental pollution on TFP growth. Most studies analyze total factor productivity （TFP） by estimating average production functions based on the data of capital, labor and desirable output. Without considering energy consumption and environmental pollution, the parametric estimation results have inevitable bias. In addition, it cannot meet the requirement of sus- tainable development under the constraint of energy and environment. Secondly ,typical TFP calculations usually assume that all of production decision making units （DMUs） are al- ways perfectly efficient producers. It is to say that all DMUs can achieve the optimal production based on the pro- duction frontier. Obviously, this assumption is so harsh that the non-fulfillment of this assumption would affect the parametric estimation results. However,in the presence of inefficiency, the accounting estimation of TFP would in- evitably be biased. In order to avoid such bias, it is necessary to use production frontier approach which considers the possible existence of inefficiency. Production frontier analysis typically includes stochastic frontier analysis （SFA） and data envelopment analysis （DEA）. In comparison, DEA does not impose any strong assumption on the form of production function and normal distribution of random interference item but can incorporate environmental pollution into linear programming model as an undesirable output. Moreover, DEA approach allows the TFP growth to be decomposed into both efficiency change and technical change. Due to these methodological merits, DEA has been regarded as an effective approach and has been frequently utilized for calculating the green TFP which is known as Malmquist-Luenberger index. However, when ML index is used to calculate the green TFP growth of DMUs, the heterogeneity among groups is usually ignored which maybe bring out a biased calculating result. To overcome this shortcoming of ML index, in this study we use meta-frontier analysis approach to measure provincial industrial green TFP growth from 1998 to 2010 in China. The meta-frontier is regarded as the envelope of the commonly conceived group production frontiers. The proposed index is named as Meta-frontier Malmquist-Luenberger index （MML）. MML index provides an effec- tive tool to solve the incomparability problem in the performance measurement of various groups operating under dif- ferent technologies. In this paper, under the framework of meta-frontier analysis, MML index considering group heterogeneities is applied to measure industrial green TFP growth and its decomposed components in presence of energy＂ consumption and carbon dioxide emissions. The main finding is that most eastern provinces have taken the lead in meta-frontier technology. Provincial green TFP shows a growing trend on the whole, but the eastern industrial green TFP growth is significantly faster than that of the central and western. Industrial green TFP growth is mainly driven by technologi- cal progress but drawn back by efficiency change. Technological progress should be strengthened to accelerate low- carbon industrial transition, while more attention should be paid to exert the role of technical efficiency in promoting low-carbon industrial transition in the future. Eastern provincial industrial green TFP growth demonstrates a trend of club convergence, while both the central and western region just shows a trend of conditional convergence.