1. Out-migration of Young Adults and Living Arrangements of the Elderly in Rural China: The Case of Chaohu Merril Silverstein Andrus Gerontology Center University of Southern California, USA Li Shuzhuo & Zhang Wenjuan Institute for Population and Development Studies Xi'an Jiaotong University, China

2. Background  Perspectives on Chinese rural elderly  Family support for old age  Rural-urban migration  Changing family structure and living arrangement

3.  Factors affecting living arrangements  Preference for living alone or with others  Economic resources to maintain an independent household  Health status for living independently  Availability of kin, especially children, with whom coresidence is possible  Western elderly and urban Chinese elderly

4.  Perspectives on living arrangements of rural Chinese elderly  Network-households and traditional marriage form  Son preference  House ownership and independent income  Reliance on children for financial and instrumental support

5.  Research questions  Does out-migration of young adults affect their elderly parents’ living arrangements in rural China? Family support for old age  Do gender, children’s status, parents’ economic resources and health status affect parents’ living arrangements, especially in the context of increasing out-migration of young adults in rural China?

6. Data & Methods  Data Source  Longitudinal Study of the Well-being of the Elderly in Anhui Province, China.  Random sampling of 1,800 people aged 60 and over living in rural townships within Chaohu city, using a stratified multistage sampling method.  Baseline survey conducted in April 2001 and follow-up survey in Oct. 2003, by the Institute for Population and Development Studies, Xi’an Jiaotong University, with technical support from USC.

7. Anhui Province, China Chaohu

8.  Samples  Our interest is the living arrangements between parents and children, the sample consists of 1,627 elderly with at least one living child from the 2001 baseline survey.  Method  Multinomial logistic regression

9.  Dependent variable living arrangements of the elderly  Empty-nest family (living alone or with spouse)  Stem family (living with children or spouses of children, with/without grandchildren)  Skip-generation family (living with grandchildren but not children)

10.  Independent variables  Living preference: Gender of parents and children  Status of children : Gender, whether within the village, marital status, and age of children’s offspring  Economic resources of the elderly: Occupation, educational attainment, independent income, and house ownership  Physical health status of the elderly : ADL, age  Control variable: Marital status of the elderly

11. Descriptive Information  Living arrangements of the elderly alone or with spouseskip-generationalstem-family Percent 60 50 40 30 20 10 Males Females

12.  Children’s status  The elderly living alone or with spouse are more likely to have sons in the same village than those in other groups. Variables Elderly in stem household % Elderly in skip- generation household % Elderly in empty-nest household % Sons in the village (sons living with them excluded): None 64.160.835.8 One son23.824.132.1 At least two sons12.115.032.0 Daughters in the village (daughters living with them excluded): None 71.874.8 71.9 One daughter22.621.322.2 At least two daughters 5.6 3.8 5.8

13.  The elderly in skip-generation household are more likely to have children outside the village than others Variables Elderly in stem household % Elderly in skip- generation household % Elderly in empty- nest household % Sons outside and not separated for job-related reason: None 65.216.142.9 One son24.741.635.7 At least two sons10.142.321.3 Daughters outside and not separated for job-related reason: None 32.920.622.2 One daughter33.235.034.6 At least two daughters33.944.443.2 Sons outside and separated for job-related reason: None80.575.581.4 At least one19.524.518.6 Daughters outside and separated for job-related reason: None 83.083.284.1 At least one17.016.815.9

14.  Percentage of elderly with juvenile grandchildren whose parents are outside the village is highest among the elderly in skip- generation households VariablesElderly in stem household % Elderly in skip- generation household % Elderly in empty-nest household % Sons outside with children 18 or younger: None67.915.749.7 At least one32.184.350.3 Daughters outside with children 18 or younger: None 52.924.835.1 At least one47.175.264.9 Sons divorced, widowed or never married: None71.777.683.5 At least one28.322.416.5 Daughters divorced, widowed or never married: None 88.492.089.7 At least one11.6 8.010.3

15.  Economic resources  Economic resources of the elderly living with children are worse than those of other two groups VariablesElderly in stem household % Elderly in skip- generation household % Elderly in empty-nest household % Occupation: Agricultural97.193.794.5 Non-agricultural 2.9 6.3 5.5 Education: At least some formal education19.121.022.1 No formal education80.979.077.9 Economic income: No impendent income63.429.037.4 Yes36.671.062.6 House ownership: Rent or in other ’ s house 77.860.143.3 Owner13.532.553.0 Joint ownership 8.7 7.3 3.7

16.  Health Status  The elderly in skip-generation households have better physical health status than those in other groups VariablesElderly in stem household % Elderly in skip- generation household % Elderly in empty-nest household% Number of ADL disability: 031.457.349.0 113.410.814.7 2 7.2 8.7 5.6 3 and over48.023.130.6 Age: 60-7448.280.464.0 75+51.819.636.0

17. Regression Results  Gender preference  The elderly have significant son preference when choosing children for coresidence.  The elderly show no gender difference when choosing living arrangements Variables Odds ratios Stem-householdSkip-generational household Gender: Male Female0.8781.000 Sons in the village (sons living with them excluded): None One son0.241***0.466*** At least two sons0.096***0.382*** Daughters in the village (daughters living with them excluded): None One daughter0.8531.179 At least two daughters0.8680.834

18.  Status of children  The elderly with more out-migrating sons are more likely to be in skip-generational households and less likely to live with children.  Additional sons separated for job-related reason increase likelihood of the elderly living with children.  Additional sons in the same village decrease parents’ likelihood in stem and skip-generational households, and increase their likelihood to live alone or with spouses.  The elderly with sons in marriage crisis are more likely to live with children.

19. Regression results of children’s status Variables Odds ratios In stem-householdIn skip-generation household Sons in the village (sons living with them excluded): None One son0.241***0.466*** At least two sons0.096***0.382*** Daughters in the village (daughters living with them excluded): None One daughter0.8531.179 At least two daughters0.8680.834 Sons outside and not separated for job-related reason: None One son0.315***1.299 At least two sons0.122***1.541 Daughters outside and not separated for job-related reason: None One daughter0.688+.804 At least two daughters0.614*.832 Sons outside and separated for job-related reason: None At least one1.176+1.015 daughters outside and separated for job-related reason: None At least one1.0090.888 Sons outside with children 18 or younger: None At least one0.8852.950*** Daughters outside with children 18 or younger: None At least one0.9371.423 Sons divorced, widowed or never married: None At least one4.886***1.442+ Daughters divorced, widowed or never married: None At least one1.0900.877

20.  Economic resources  The elderly without any formal education are more likely to stay in skip-generational household  The elderly with independent income or house ownership are more likely to live alone or with spouses Variables Odds ratios Stem-householdSkip-generation household Occupation: Agricultural Non-agricultural0.7491.444 Education: At least some formal education No formal education0.9071.643* House ownership: Rent or in other ’ s house Owner0.146***0.401*** Joint ownership1.1181.136

21.  Health status The elderly in relative good health status are more likely to live alone or in skip-generation household. Variables Odds ratios In stem-household In skip- generation household ADL 0.954***1.029 Age 0.9900.969*

22. Conclusions  Out-migration of young adults has significant influences on their parents’ living arrangements.  Gender, children’s status, parents’ economic resources and health status significantly affect parents’ living arrangements.  Elderly’s need for support has become the primary cause for their coresidence with adult children, which is different from the Western elderly and the Chinese urban elderly.

23.  Need of children (i.e. child-care) also affects the living arrangements of the elderly, when the parents are in good physical health status.  The elderly show strong son preference in selecting coresidence or providing grandchild care in skip-generational household.  The skip-generational household is a special arrangement mostly caused by the out-migration of adult children, in which parents provide daily care for grandchildren.

24. Thank you!