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Analysis About The Determinants Of Long-term Care Insurance

Posted on:2019-07-25Degree:MasterType:Thesis
Country:ChinaCandidate:M XuFull Text:PDF
GTID:2429330545454408Subject:Insurance
Abstract/Summary:PDF Full Text Request
The ageing population is receiving significant attention from both academic researchers and policy makers.As the World Population Prospect 2017 shows,the percentage of the senior citizen(age 65 and above)of the world is projected to rise from 6.9%in 2000 to 15.8%in 2050,which approximately reach to 1,546,066 thousand population.As the most populous country-China,is ageing so rapidly that by 2050,there may be 26.3%senior citizen of the total population compared with only 6.3%in 2000,which means that there will be one senior citizen for every four people in China at that time.By 2016,there are over 150 billion elderly people in China,accounting 10.8%of the total population.What matters most is that China gets old before it gets rich and prepares,that the per-capital GDP does not reach the level of the developed country.As long as China has refined the existing pension system,there are imbalances of the pension program over different districts and shortage capital in the long term.Besides,the aged service industry and health care industry develop slowly,which could not meet the need of the aged population in China.There are only 28000 nursing homes in 2016,which supply 3.58 billion rehabilitation nursing bed in total.It is predicted that there will be 255 billion elderly people in China in 2020,which will account 17.8%of the total population.What's more,the population of the elderly living alone will increase to 118 billion.As the baby-boom generation approaches retirement and the increasing fiscal pressure,concerns about long-term care are increasingly heated in the recent years.Private long-term care insurance focuses on covering the expenditure of service of long-term care,which plays an important role in sharing the burden of supporting the elderly and guaranteeing the later life for the aged.In older to solve the increasing nursing need of the old,China is pushing the pilot project of long term care insurance over 15 districts.We start our research on analyzing the systems of long-term care in abroad,especially in the USA and Japan.The advanced successful experience of long-term care insurance system shows that the government should combine the social pension system with private long-term care insurance market.Having figured out the urgent challenge of supporting the elderly,we stress emphasis on the factors influencing the long-term care insurance market in China.Owing to the lack of data in the individual level,I use the data from the China Statistic Yearbook(the data of which is accessible to the public)from 2010to 2016 to measure the factors on a macro level.The factors are classified as economic factors,social factors and public insurance crowd-out.The dependent variable in this dissertation is the income of nursing institution?The paper focus on two parts:in the first part we divide the data into urban level and rural level;and in the second part we estimate the models separately over eastern and western regions.The results of the urban model show that:(1)the economic factors have significant effect on the dependent variable;(2)the social insurance has significant crowd-out effect over the long-term care insurance,while health insurance do not;(3)the social factors(like family structure and education level)show significant effect on the model.The results of the rural model show that:(1)the economic factors affect the model significantly;(2)the social insurance and health insurance have significant crowd-out effect on the long-term care insurance;(3)the support rate and sex ratio are significantly affect the model.In terms of the regional differences,the results show that the factors have more significant influence on the dependent variable in the model of eastern area than in the other areas.
Keywords/Search Tags:Long-term care insurance, Factor analysis, Urban-rural differences, Regional difference
PDF Full Text Request
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