Analysis On Interprovincial Factors Of Elderly Migrants

The "China Mobile Population Development Report 2018" pointed out that China's floating population began to enter an adjustment period after experiencing long-term rapid growth.In recent years,the size of the floating population has been declining year by year,but the number of migrants in the elderly is still rising.Due to its own specificity,the elderly migrant population poses a major challenge to the economic development,consumption structure,infrastructure,and medical facilities.Due to the differences in economic level,medical security and ecological environment between provinces,the selection of inter-provincial migrants will encounter many obstacles.This paper uses Logistic regression model and classification tree after descriptive analysis of the status quo of individualized characteristics of elderly migrants.The model conducts empirical analysis,rationally and scientifically explores the factors affecting the flow of the elderly population across provinces,teaching students in accordance with their aptitude and adapting to local conditions,so that the elderly migrant population can achieve the old,the old and the old.In the logistic regression analysis,according to the analysis premise,the elderly migrant population is divided into four groups,namely gender and household registration status,and the research model is divided into individual-level variables in each group,and joined to the provincial level.Variables to complete the discussion of intra-group differences and individual provincial interactions.On the whole,the individual level variables,nationality,health status,cultural level,household registration nature,medical insurance social security management,flow reasons,number of former mobile cities,unemployment years,and average monthly household income expenditures all passed the significance test,but joined the provincial level.In the model of level variables,provincial-level variable economic indicators: per capita GDP,per capita disposable income,household consumption index,medical security indicators: number of primary medical institutions,public transportation indicators: number of buses per 10,000 people,demographic indicators: population Both the density and the degree of aging are tested by significantness,and under the influence of provincial variables,the individual monthly economic income of the individual-level variables,the unemployment rate,and other personal economic conditions have not passed the significant test,and the ability to interpret the health status and cultural level.There has been a decline.In the classification tree model,the interaction between the factors is fully considered,and the research object group can be directly focused.In the classification tree model with only individual level variables,six variables such as family monthly income,expenditure,social interaction category,ethnicity,mobility willingness,and medical insurance status are included in the model,but again,after adding provincial variables,only The average monthly income of the nation and the family,the degree of aging,the population density,and the per capita disposable income were screened out.There are no advantages and disadvantages between the two models.We only need to select or use both models according to the specific problems of the research to achieve the purpose of solving the problem.For the cross-provincial elderly population with different characteristics,government leadership and enterprise cooperation gradually achieve the goal of “healthy aging”.