Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
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|
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Article Number | 01021 | |
Number of page(s) | 5 | |
Section | Big Data Analysis Application and Energy Consumption Research | |
DOI | https://doi.org/10.1051/e3sconf/202021401021 | |
Published online | 07 December 2020 |
Population Age Structure, Social Security and Household consumption rate
School of Economics and Management Beijing Jiaotong University Beijing, China
a xiulin_ji@163.com
b mxshi@bjtu.edu.cn
This paper uses panel data from 31 provinces in China from 2005 to 2018, and examines the relationship between the age structure of the population, the level of social security, and the consumption rate of residents by establishing static and dynamic models. The study found that, the child dependency ratio and the elderly dependency ratio have a negative impact on the residents’ consumption rate. Child dependency ratio increased by 1%, resident consumption rate decreased by 7.4%. Elderly dependency ratio increased by 1%, resident consumption rate decreased by 13.7%. Pension coverage has no significant impact on household consumption rates. Moreover, the consumption of Chinese residents is inertia, that is, the current consumption of residents is affected by previous consumption habits, which is one of the reasons for the current low consumption rate of our residents. In addition, research shows that the per capita real GDP and real interest rate promote China’s residents’ consumption, and the inflation rate and urbanization level have a certain inhibitory effect on the residents’ consumption rate. Therefore, the development of distinctive children’s training courses and the elderly-related industries, the optimization of the elderly’s labor market, and the gradual change of residents’ consumption concepts are more effective ways to expand domestic demand.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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