A Study Of The Influence Of Population Structure Changing On China's Consumption Upgrade

The essence of consumption upgrade is the optimization and upgrading of the consumption structure,which is a direct reflection of the good life of the people,and it also reflects the development of our economy and society.Clarifying the influencing factors of consumption upgrade can not only help us implement more accurate and effective supply and promote the equilibrium of demand and supply in the society,but also can implement more precise supply to meet people's growing needs of better life,improve the quality of people's life,and promote economic development.Among the many influencing factors of consumption upgrade,the demographic structure is supposed to be a major influential factor?The population is the main body of social and economic activities and the ultimate consumer of goods and services.Population differences in age,gender,urban and rural areas,occupation,family,etc,which leads to people have different demands for the same types of products and services,and the consumption structure will be adjusted appropriately according to changes in the population structure.Considering the impact of demographic changes on consumption upgrade,the demographic structure of this thesis is subdivided into the natural structure of the population and the social structure of the population.At the same time,the thesis will combine theoretical analysis with empirical analysis,qualitative analysis with quantitative analysis,and study the influence of population structure change on consumption upgrade from the macro level in China.This article first combines the current situation of China's population structure with relevant research conclusions at home and abroad,and conducts a theoretical analysis of the impact of China's population structure changes on consumption upgrading,and takes the obtained conclusions as the theoretical basis for the empirical analysis of this paper.In the empirical analysis,this thesis uses principal component analysis to reduce the dimensions of variables and eliminate multidisciplinary,which is for obtaining a principal component of comprehensive population,specific population,and control variable principal component.The main component of the comprehensive population consists of the old-age dependency ratio,the proportion of employees in the secondary and tertiary industries,the urbanization rate,and the proportion of three-person households.Among the principal components of the special population,the principal component coefficient of the sex ratio of the male and female accounted for the largest of 0.92,and the second principal component mainly contains information on the sex ratio of men and women?Therefore,it is positioned as the population specific principal component.The main component of the control variable consists of per capita disposable income and the consumer price index.Then,the vector auto-regressive model is used to study the dynamic relationship between population structure and consumption upgrade index.In this paper,the co-integration test,Granger causality test and impulse response function analysis are conducted on the comprehensive population principal component,special population principal component,control variable principal component and consumption upgrade obtained in the principal component analysis.Combining theoretical analysis and empirical analysis,this article believes that in the natural population structure,China should didactically view the impact of population aging on consumption upgrading,and the changes in China's gender structure have little effect on China's consumption upgrading.In the social structure of the population,the urbanization of the population and the proportion of employees in the secondary and tertiary industries will all promote consumption upgrading to a certain extent.Although the miniaturization of the family size also has a certain role in promoting consumption upgrades,it cannot blindly pursue small families,and the"degree" of family size should be grasped.