| Evaluation indicator that takes into account both the economy and the environment is very important to establishing and improving the economic system of green,lowcarbon and circular development.In the past ten years,with the advancement of the lowcarbon development process,scholars have made numerous studies on carbon emission efficiency.However,as far as the current research subjects are concerned,most of them focus on the macro-regional level or the enterprise level,and there are very few studies on the meso-level.Industrial production activities are the main source of carbon emissions.Under the background of "dual carbon",analyzing the carbon efficiency of industrial sub-sectors in various regions and studying the influencing factors behind it can not only provide theoretical support for the macro path design of energy conservation and emission reduction,but also it provides a powerful reference for formulating specific lowcarbon development policy plans.Based on this,this paper uses the fixed-effect stochastic frontier model to evaluate the carbon efficiency of industrial sub-sectors in the Yangtze River Delta region,which is a highland of domestic economic development,a region with strong industrial development,and a region with high carbon emissions.First,the IPCC calculation method was used to calculate the total carbon emissions of regions and industrial sectors,and the current situation of low-carbon development in the Yangtze River Delta region was analyzed;then,the stochastic frontier model was used to calculate the carbon efficiency of 37 industries in three provinces and one city from 2014 to 2019.,and analyzed the dynamic changes of industrial carbon efficiency in various regions;later,based on the results of the one-step stochastic frontier model,the influencing factors of carbon efficiency are explored,also the differences in the degree of various influencing factors among different regions and different industry types are further explored.Finally,in order to further prove the robustness of the model,different production function forms and the method of removing extreme values are used for verification;at the same time,the results of the stochastic frontier method without considering individual heterogeneity are compared,and the difference in the results reflects the improvement of this model.This study has the following findings:(1)From the overall dynamic change,the high carbon efficiency industry cluster in the Yangtze River Delta has expanded in recent years,but the development trend is different in different regions.The carbon efficiency of Shanghai and Jiangsu provinces has improved in groups,while Zhejiang and Anhui have experienced loss of high carbon efficiency industries.(2)The representative high carbon efficiency industries vary from region to region.The industries with high carbon efficiency in Shanghai are concentrated in high-tech industries;Jiangsu Province is concentrated in the manufacturing of equipment and chemical fibers;The light industries in Zhejiang Province generally have high carbon efficiency;The mining industry,metal smelting and processing industry and waste resource utilization industry in Anhui Province have high carbon efficiency.(3)The impact of industry specialization on carbon efficiency is very significant(4)Regional studies find out the improvement of industrial specialization has a strong effect on the improvement of carbon efficiency in Jiangsu Province;the improvement of state-owned assets has significantly promoted the industrial carbon efficiency of Anhui Province;environmental regulation can boost carbon efficiency in Anhui and Shanghai relatively faster.(5)Further research by industry type finds out environmental regulation of heavy industry can improve the carbon efficiency of the industry in time,and more state-owned assets will play a role in promoting the carbon efficiency of heavy industry.Based on the above results,this paper puts forward relevant policy suggestions for the green and low-carbon development of the industrial sector in the Yangtze River Delta region. |
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