The Influence Of Digital Economy On Carbon Emission Intensity

In the context of the sweeping global revolution of Industry 4.0 represented by digital economy,digital economy has exerted extensive influence on all aspects of social and economic life.In addition,under the background of the "30·60" two-carbon target,the policy arrangement that focuses on carbon intensity control and is supplemented by carbon total control has been formed.Energy conservation and emission reduction have become the inevitable requirements of sustainable economic and social development in the future.Studying the impact of digital economy on carbon emission intensity has strong theoretical value and significance of The Times.Since the influence of digital economy on carbon emission intensity may be characterized by both spatial effect and threshold effect,this study systematically deduces the parameter estimation method and parameter test method of the spatial threshold model,and studies the influence of digital economy on carbon emission intensity through this model.In terms of models,this study constructed the spatial threshold autoregressive model,spatial threshold error model,spatial threshold Dubin model and generalized spatial threshold model,systematically derived the parameter estimation methods of the above models under the framework of maximum likelihood estimation method,and derived the parameter test method and confidence interval estimation method of the model through LR statistics and Monte Carlo simulation.It is found in the numerical simulation that:(1)Under the model parameter estimation method and parameter test method in this study,the model parameter estimation results are consistent with the values set by the numerical simulation parameters,and the threshold value test results in the model show that the estimated number of threshold values is consistent with the values set by the numerical simulation.(2)When comparing the estimation results of spatial econometric model,panel threshold model and spatial threshold model,it is found that if there are both spatial effects and threshold effects in the model estimation,ignoring either effect in the model estimation will increase the bias of model parameter estimation.(3)After the estimation of a large number of simulated data of different sample sizes,it is found that with the continuous expansion of the sample size,the deviation of the model’s estimation results is decreasing,and the mean square error of the estimation parameters is also decreasing,and the estimated values of the model parameters gradually converge to the true values.The parameter estimation method in this study has a good large sample property.(4)After different Settings of the actual values of the model parameters,it is found that the deviation of all the estimated results in the model fluctuates within a small range under the Settings of various real values.The parameter estimation method in this study has certain generality and universality.Empirically,this study constructs an evaluation index system of the development level of digital economy through 30 specific indexes under the four first-level indexes of digital economy development carrier,digital industrialization,industrial digitalization and digital economy development environment,and calculates the digital economy development level index of each province from 2011 to 2020.The carbon emission coefficient method was used to calculate the total carbon emission data of each province from 2011 to 2020 by combining the consumption of eight major energy sources,and the data was divided by the actual gross regional product of 2011 as the base period to obtain the carbon emission intensity data for empirical analysis.The study found:(1)The digital economy index of provinces maintained a high growth rate from 2011 to 2020,but the development of digital economy among provinces is extremely unbalanced,which is mainly reflected in the high development level of eastern regions and the low level of central and western regions,and the convergence of digital economy development among provinces.The more backward the digital economy development of the region,the higher the growth rate of digital economy index.(2)The distribution characteristics of carbon intensity in provinces show that the carbon intensity in the economically developed regions is lower,while the carbon intensity in the economically underdeveloped regions is higher.From 2011 to 2020,the carbon intensity of provinces shows a downward trend on the whole,and the higher the carbon intensity,the slower the decline,and the carbon intensity of provinces shows a development trend on the whole.(3)The influence of digital economy on carbon emission intensity has both spatial effect and threshold effect.In general,the influence of digital economy on carbon emission intensity is positive.When considering the spatial effect,the results of the digital economy not only inhibits the local carbon emission intensity,but also inhibits the local carbon emission intensity from surrounding areas due to the spatial spillover effect of carbon emission and digital economy.When considering the threshold effect,panel threshold model and spatial threshold Durbin model show that the impact of digital economy on carbon emission intensity has obvious structural change characteristics.When the development of digital economy is low,digital economy can promote carbon emission intensity,while when the development level of digital economy exceeds the threshold,digital economy can inhibit carbon emission.(4)In the mechanism analysis,this study divides the impact of digital economy on carbon emission intensity into two aspects: total carbon emission and actual gross regional product.The results show that the structural variation characteristics of digital economy on carbon emission intensity are mainly as follows:when the development level of digital economy increases to the threshold,the inhibition effect of energy efficiency on total carbon emission becomes stronger,and the promotion effect of technological progress on actual gross regional product also becomes stronger.Finally,the improvement of the development level of digital economy is conducive to the control of carbon emission intensity.Based on the above conclusions,this study puts forward the following policy recommendations:(1)Formulate digital economy development policies according to local conditions,give more preferential policies to regions with backward digital economy development level,remove industrial barriers and regional restrictions,give play to the driving role of the eastern region to the central and western regions,and narrow the digital economy development gap between different regions.Regions with a high level of digital economy will be further encouraged to develop new models and new forms of business that are conducive to reducing carbon emission intensity,and strengthen the role of digital economy in controlling carbon emission intensity.(2)Attach importance to the role of digital economy in improving energy efficiency,encourage industries with high energy consumption to speed up the digitization process and accelerate the digital transformation of relevant industries.We will encourage research and development of carbon emission reduction technologies such as carbon capture and sequestration,and increase investment in research and development related to energy conversion efficiency.(3)Constantly improve the infrastructure of digital economy in all regions,fully release the development dividends of digital economy,and give play to the role of digital economy in technological progress.We will continue to introduce talents,encourage technological innovation in enterprises,give full play to the role of technological innovation in economic growth,and reduce carbon emission intensity.