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Research On The Determinants Of Older People Living Arrangements In China

Posted on:2016-09-08Degree:MasterType:Thesis
Country:ChinaCandidate:X Y C h e u n g ZhangFull Text:PDF
GTID:2347330536450251Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Aging problem in China is intensified by the huge population of older people.Low economic development level further exacerbates the aging problem in China. Nowadays, the Chinese government pays attention to the rapidly increasing number of older people through publication of a wide range of measures. Among all, living arrangements of older people is highly affecting demands of older people towards government and society. This thesis discusses theoretical research and develops empirical analysis model to reveal major factors on older people living arrangements decision. Older people with agricultural and non-agricultural Hukou are compared to better understand the influential mechanism.Then, this study, on the one hand, suggestsfactors of changing choicesof older people living arrangements based on the matched data.On the other hand, the current studycontrasts preference and actual choice of older people living arrangements in China for further exploration in potential variables on preference of older people.National Censuses in 2000 and 2010 are introduced to statistically present the tendency of aging society in China. China Health and Retirement Longitudinal Study(CHARLS), conducted in 2010 and 2013, is employed in the empirical study. The first empirical analysis will start with major theoretical papersreview anda thorough discussion of China specific featuresto gain critical determinants of living arrangements. Logit regression analysis is aiming to find out factors of older people living arrangementsand differences in urban and rural areas in China. Personal characteristics, family features, financial conditions as well as policy legislation are proved to significantly affecting decision of older people. A robust test on investigating differences between urban and rural older people is also supporting theresult. Then, Logit regression is conducted to identify possible factors of changing living arrangements choice of older people. Furthermore, based on differences between preference and actual choice of living arrangements, another Logit regression on preference of older people is conducted for possible influential factors.There are three main conclusions and respective policy remarks. First of all, personal characteristics,family structure, financial condition as well as policy legislation are significantly affecting choice of older people in China. Bequeath tendency is the primary difference between urban and rural older people. As there are significantly effects of China specified factors on choice, it would be necessary for government to formulate policies based on China features but not indiscriminately adopt experiences from other countries. Secondly, changes of living arrangements are significantly influenced by medical affordability, housing structures as well as self-rated living standard of older people. Especially, person who is paying medical expenses of older people, existence of grandchildren, and self-rated living standard of older people are more likely to cause the change of current living arrangements. Therefore, government should focus on the sources of medical expense as well as living standard of older people. In order to encourage aging-in-place, Chinese government should promote community support network to ensure medical care accessibility. Thirdly,there is only a small part of older people who are able to live according to their preferences. Major constraint of living arrangements is health condition. Chinese government in this case should pursue adapted aging house which is able to raise living standard. In addition, government could encourage adult children to take responsibility in taking care of older people by introducing tax credit.
Keywords/Search Tags:older people, living arrangements, China, CHARLS, empirical
PDF Full Text Request
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