Abstract: Adhering to and improving the overall planning of the urban and rural livelihood security system is an important part of the 13 systems proposed by the Fourth Plenary Session of the 19th Central Committee of the Communist Party of China,and the analysis of the level and influencing factors of peoples livelihood security construction is the key to an in-depth understanding of the function of Chinas livelihood security to promote social equity and share the fruits of development.Constructing an indicator system for measuring the level of peoples livelihood securiey,based on the panel data of 31 provinces in China from 2013 to 2022,and the entropy weight TOPSIS model,this paper uses three complementary research methods of Kernel density estimation and spatial measurement to comprehensively investigate the development trend of Chinas livelihood security level from a dynamic perspective,and identify and reveal the spatiotemporal evolution characteristics,spatial correlation and main influencing factors of Chinas livelihood security development level.The results show that:(1)the level of peoples livelihood security in China has shown a steady upward trend during the study period,but there are obvious regional differences.(2)From 2013 to 2022,there was a significant spatial correlation between the level of peoples livelihood security in China,with most provinces in the first and third quadrants,and the eastern region was significantly higher than that in the central and western regions.(3)From the regression results,GDP,the urbanization rate,local fiscal expenditure and industrial structure of the province will promote the development of the people s livelihood security level in the province,that is,the above four elements have a positive direct effect on the development of the peoples livelihood security level.(4)From the results of spatial effect decomposition,the influence of variables on the province is different from that on the neighboring provinces under the spatial economic geography matrix and the spatial adjacency matrix,and even the opposite situation occurs.As far as each variable is concerned,the degree of impact of each variable on the province,the provinces with similar spatial and economic geographical distances and neighboring provinces,and the whole country as a whole is also different.

Key words: peoples livelihood security, entropy weight TOPSIS, Kernel density estimation, spatial measurement