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The Influence Of Population Structure On The Scale Of Long-term Care Insurance In China

Posted on:2024-03-29Degree:MasterType:Thesis
Country:ChinaCandidate:Z X LinFull Text:PDF
GTID:2557307133468914Subject:Finance
Abstract/Summary:
According to data released by the National Bureau of Statistics,in2021,the number of elderly people aged 65 and above exceeded 200 million for the first time,accounting for 14.2% of the national population.It is estimated that by 2035,the total number of elderly people over 60 years old in China may exceed 400 million,entering a severely aging society.In addition,the current number of disabled elderly people in China has exceeded 42 million,and the disability risk of the elderly population has become a social problem that needs to be solved urgently,and the traditional model of long-term care for the elderly is facing great challenges.In 2016,in response to the severe problems of population aging and disability,the Chinese government issued relevant policies to officially pilot long-term care insurance,which has covered 49 cities across the country,with 145 million participants and a total of 1.65 million people enjoying benefits.In February 2022,the State Council issued the 14 th Five-Year Plan for the Development of the National Elderly Cause and the Old-age Service System,which put forward clear requirements for the steady establishment of a long-term care insurance system in China.However,after nearly seven years of pilot development,long-term care insurance is still facing a development bottleneck that is difficult to break through in China,and the gap between the supply side and the demand side is increasingly prominent,which is caused by problems such as imperfect system design,incomplete coverage,unprofessional nursing institutions and teams,and inadequate residents’ cognition.The important premise of the development of long-term care insurance is professional nursing institutions and teams,perfect financing channels and fund use channels,residents’ understanding and trust in long-term care insurance,the effective improvement and smooth operation of the entire top-level design to the underlying logic,etc.,and the population structure has a significant impact on the pilot and promotion effect of long-term care insurance from various characteristics of service objects.Based on the perspective of population structure,based on the natural,socio-economic and spatial attributes of the population,taking the time span from 2001 to 2021 in China and the spatial span of 31 provinces,autonomous regions and municipalities directly under the central government,this paper selects the characteristics of age structure,gender structure,income structure,education structure,family structure,urban and rural structure in different times and regions,establishes a Pearson correlation coefficient model,and explores the impact of population structure on the scale of long-term care insurance in China.It is found that age,income,education and urban-rural structure have positive effects on long-term care insurance,while family structure has a negative impact on long-term care insurance.It is inferred that the portrait of the target group of long-term care insurance is more concentrated in provinces and cities with developed economy,higher income,higher education level,small family size,large single population,high urbanization level,and serious aging,and relevant policy suggestions are put forward from the perspective of population structure to improve the institutional system of long-term care insurance policy and insurance cooperation.This paper innovatively starts from the perspective of population structure,combines the characteristics of long-term care insurance scale in the national population structure,and theoretically describes the specific path of accurate delivery of long-term care insurance user portraits under the government-insurance cooperation model,so as to provide new ideas and new solutions for long-term care insurance optimization and policy promotion.
Keywords/Search Tags:Long-term Care Insurance, Demographics, Correlation Coefficients, Cooperation Between Government and Insurance
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