Spatial Correlation Of Chinese Industrial Production Efficiency Under The Constraint Of Carbon Emission

The development of industry plays a leading role in the development of the national economy.Along with the improvement of industrial efficiency,it has also had a major impact on the transformation of China's industrial structure,and has led the development direction of China's resource-saving society.However,with the gradual improvement of industrial development,industrial production efficiency has begun to receive widespread attention.The “extensive” input of resources such as non-renewable resources and human and financial resources needs to shift to “intensive”,and the environment-friendly “green industry” begins promote.How to make resource input and industrial output reach higher efficiency values and control non-desirable outputs that are harmful to the environment is very important.Therefore,it is necessary to use scientific methods to influence the efficiency of industrial production and related impacts.Research to maximize industrial efficiency.Based on the research literature on industrial production efficiency,this paper takes the panel data of industrial production in 30 provinces and cities in China from 1995 to 2015 as the research object,and uses the SBM model in the data envelope method to calculate China's inter-provincial industrial production efficiency value under the carbon emission constraints,and the use of global and local Moran index on the spatial correlation analysis of provincial industrial production efficiency.The idea of the article is as follows: First,the carbon emissions of fossil fuels consumed by industrial production in various provinces and municipalities were measured;second,the spatial correlation analysis of the overall Moran index and the local Moran index was performed on the measured industrial production efficiency;Purely technical efficiency(vrste)and scale efficiency(scale),further explore the impact of technological level and scale on industrial efficiency.In addition,this article will also compare the industrial production efficiency under the condition of no carbon emission constraint,so as to explore The impact of carbon emission constraints on industrial production efficiency.Finally,the differences in industrial production efficiency in eastern,central and western regions of China were analyzed,and the influencing factors of regional efficiency differences were explored.The research in this paper shows that under the constraint of carbon emissions,the inter-provincial industrial production efficiency in China shows a trend of “decrease and then increase.” By 2015,the industrial production of all provinces and cities is on the efficiency front;before 2013,the “1 value unit” provinces Mainly in the east,and the “1 value unit” provinces show an increasing trend with the increase of the year,which means that the higher industrial production efficiency is mainly concentrated in the eastern coastal provinces and cities,and the lower is mainly concentrated in the western provinces and cities;The provinces with higher and lower production efficiency are not random spatially.From a global perspective,there is a positive correlation between the industrial production efficiency of various provinces and urban areas.From the perspective of local spatial correlation,the eastern provinces mainly exhibit high and high aggregation characteristics.Western provinces have low-low accumulation characteristics;from the perspective of efficiency split,carbon emission constraints have an impact on the pure technical efficiency in the central region,regardless of the carbon emission constraints,the highest efficiency of pure technology is the central region,with the highest scale efficiency.In the eastern region,considering the carbon emission constraints,the highest pure technical efficiency and scale efficiency are in the eastern region.The main factors leading to the regional differences in industrial production efficiency are internal factors,and the factors most affected are the regional differences in industrialization levels and the industrial industrial structure differences.