Research On The Impact Of Population Structure On Carbon Emissions Based On Spatial Dubin And Threshold Regression Model

In the 21st century,global warming has become the most important international environmental issue facing mankind.Greenhouse gases are considered to be the main cause of global warming,especially carbon dioxide.Emissions of carbon dioxide have accelerated global warming due to the dramatic increase in energy consumption.According to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change（IPCC）,nearly 90%of greenhouse gas emissions since the mid-20th century have been caused by everyday human activities.Demographic factors have put enormous pressure on the environment and have become one of the main causes of environmental problems.China is the world’s largest developing country with a large population,and population growth has increased the burden on housing,transportation,water and electricity,education and health,leading to increasing energy demand and carbon emissions.Population has become a major driver of CO₂ emissions and energy footprint.It is thus important to explore the impact of demographic change on carbon emissions in China.Therefore,this thesis uses time series data from 2000-2019 to analyse the relationship between demographic change and carbon emissions in terms of dependency ratio,sex ratio and average household size.A spatial econometric model is constructed based on panel data from 30 provinces and cities in China to explore the impact of demographic structure on carbon emissions,and the level of urbanisation is further introduced as a threshold variable to use the threshold model to analyse in depth the threshold effect of demographic structure on carbon emissions.The findings of the study are as follows:Firstly,carbon emissions of major provinces and cities in China show significant positive spatial autocorrelation due to their regional differences.High-high aggregation is shown in the two regions of East and Central China,while low-low aggregation is shown in the western region.Secondly,in terms of total emissions,the carbon emissions of the 30 provinces and cities show a year-on-year increase within the study interval.From the spatial distribution,it can be seen that China’s carbon emissions are relatively low in the southern region as a whole,while high in the northern region.Looking at the eastern,central and western regions,carbon emissions are higher in the east,especially in the eastern coastal region,followed by the central region and the lowest in the west.Then,according to the results of the spatial Durbin model,there is a significant spatial spillover effect of carbon emissions between different provinces in China.In other words,the level of carbon emissions in neighbouring provinces is positively correlated with the level of carbon emissions in the province in which they are located.When other factors are taken into account,there are differences in the role of the three dimensions of population structure on carbon emissions.This is mainly reflected in the fact that the increase in the dependency ratio and the average household size have a dampening effect on carbon emissions,while the sex ratio has a boosting effect on carbon emissions.From the decomposition of the effects,it is found that an increase in the dependency ratio can reduce carbon emissions in both the region and the neighbouring provinces.The effect of sex ratio on carbon emissions in the region and neighbouring regions is not significant,but it also plays a contributing role.Average household size has a significant inhibiting effect on carbon emissions within both the region and neighbouring regions.By analysing the three regions of eastern,western and western China,the effects of the same explanatory variable on carbon emissions differed across regions.The effect of the dependency ratio on carbon emissions is positive in the eastern region,while in the other two regions it has the opposite effect.The elasticity of carbon emissions for both sex ratio and average household size is relatively low in western China,influenced by aspects such as geography and economic development.Next,in the threshold regression analysis,the article uses urbanisation level as the threshold variable and finds that urbanisation level has a single threshold effect on carbon emissions.Specifically,at urbanisation levels less than 3.8395,the dependency ratio has a dampening effect on the growth of carbon emissions,while at urbanisation levels greater than 3.8935,an increase in the dependency ratio promotes carbon emissions;at different thresholds of urbanisation levels,the effect of the sex ratio on carbon emissions is always positively correlated.In contrast,average household size exhibits a suppressive effect on carbon emissions at urbanisation levels below the3.8044 threshold and a facilitating effect above the 3.8044 threshold.Finally,based on the findings of the study,recommendations are made to optimise the age structure,promote gender equality,advocate low-carbon lifestyles and low-carbon consumption patterns,promote industrial upgrading and industrial structure optimisation,and build low-carbon cities,with a view to providing a practical reference basis for China’s population development and low-carbon construction.