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Study On The Influence Of Urbanization On Electricity Consumption

Posted on:2019-10-17Degree:MasterType:Thesis
Country:ChinaCandidate:D X LuFull Text:PDF
GTID:2392330548954282Subject:Western economics
Abstract/Summary:PDF Full Text Request
There is a big gap in the level of electricity consumption in different provinces of China.Under the background of increasingly regional economic exchanges,electricity consumption in different regions has broken through the traditional independent mode,and the existence of spatial correlation has made spatial spillover effects of electricity consumption.Based on this reality,this paper selects 30 inter provincial panel data of China,taking the impact of urbanization on electricity consumption as the research object.Based on the classical econometric model and the spatial econometric model,it empirically studies the impact of urbanization on electricity consumption.First of all,the ArcGIS software is used to draw the spatial distribution map of Chinese 30 inter provincial urbanization and electricity consumption,in order to reveal the activity of urbanization and electricity consumption.Secondly,by constructing the classical econometric model,classical regression is used to analyze the impact of urbanization on electricity consumption.Thirdly,the Moran's I index is used to reflect the spatial correlation of the whole domain,and the Moran scatter plot is drawn to describe the local spatial correlation.Finally we construct the spatial econometric model for spatial econometric regression and do partial differential effect decomposition.The results are as follows:(1)The spatial distribution map of urbanization and electricity consumption shows that the urbanization and electricity consumption in the East are both higher than that in the West.(2)For the classical econometric model,by using mixed effects,fixed and random effects estimation method of regression,regression results show that the regression coefficients of three kinds of model of urbanization are positive,and have passed the test of significance.so we conclude that the urbanization has significant positive impact on the power consumption.(3)The Moran's I index and the Moran scatter plot show that the power consumption in different regions of China has significant spatial dependence and spatial heterogeneity in different spatial correlation models.(4)About the spatial econometric model,firstly,three spatial matrices are used to regress the SDM model,the regression results in Rho are not zero,so it should not be used directly in the regression results to explain the impact of urbanization on powerconsumption.Secondly,this paper decomposes the total spatial effect of urbanization into direct and indirect effects on electricity consumption.The empirical results show that,the regional spillover effects of urbanization on electricity consumption are positive and statistically significant under the three spatial weighting matrices.The inter regional spillover effects of urbanization are both positive and statistically significant under the three spatial weighting matrices.The total effect of urbanization on power consumption is positive under three kinds of spatial weight matrix,and it is statistically significant.From the above conclusions,whether in the estimation of classical econometric regression model results or in the estimation results of spatial econometric models,the development of urbanization will promote the power consumption to increase.The above findings coincide with the reality of Chinese economy: Chinese urbanization process and economic scale developed rapidly in 2000-2015.During this period,the urbanization level led to economic growth,industrial structure adjustment and improving people's living standards,a variety of transmission mechanism in the process of urbanization facilitated the residents to obtain power resources,which increased the power consumption of the whole society.
Keywords/Search Tags:Urbanization, Electricity Consumption, Spatial Correlation, Partial Differential Method Of Spatial Regression Mode
PDF Full Text Request
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