The problems of old age support are compounded by two other trends. First, increasing proportions of China’s elderly will be concentrated in rural areas, where old age dependency ratios are projected to rise sharply (Zeng et al 2008, Cai et al 2009). Given that rural areas are poorer than urban areas, this will further stress the resources available at both household and local government levels for elderly support.

Second, unmarried men will be concentrated in poor rural areas. Their prospects in old age are likely to be much bleaker than those of married men. Since men who are not as educated, healthy, and able to earn well tend to fail to attract a bride, they are likely to be heavily represented among those who are unable to save adequately for their old age, or labor heavily into their old age. They are the most vulnerable to income and illness shocks, since they cannot smooth fluctuations in household income by pooling earnings from spouses or children. Unmarried individuals are also more likely to be living without family to serve as caregivers (Table 5). For example, in the 2000 census, 65% of those aged 65-80 who had ever-married were co-residing with younger kin, compared with only 20% of those never-married. Moreover, levels of co-residence have dropped sharply in recent decades (Table 5), and this trend can be expected to continue. The men who fail to marry are among the least likely to be able to save for their old age, to work in their old age, and to have access to old age support from family members.

Even controlling for education, place of residence, and minority status, men who have never married have lower incomes and savings than those who have married, and also report themselves to be in poorer health (Table 6). While it is beyond our analysis here whether this disadvantage is due to selection into marriage or due to the direct impact of marriage on male earnings or ability to save (Korenman and Neumark 1991), the implication is clear that unmarried men are quite significantly financially disadvantaged compared with married men. Moreover, we find below that single men will tend to be clustered in the rural areas of poorer provinces, further disadvantaging them in terms of access to economic opportunities and social support. For a multiplicity of reasons, single men will represent a vulnerable population relative to married men.

# **4   Simulating China’s Marriage Market**

## **4.1 Assumptions**

The assumptions we make, and the sensitivity of our projections to these assumptions, are discussed in detail in the appendix. Key assumptions include the fertility rate, direction of change in the sex ratio of new births, the age preferences of men and women for their spouses, the age at which women enter the marriage market, and the criteria by which men and women choose their mate. Among these, our sensitivity analysis finds that the percent never marrying is most sensitive to the sex ratio of recent and future births and the age at which males and females debut on the marriage market. Most importantly, the sensitivity analysis confirms that correcting the sex ratio is not a panacea; the share of unmarried males will remain high well into the future even in the case of an immediate correction. Our baseline projections adopt the age-specific fertility schedule from the 2006 Sample Survey on Population Changes, with each rate adjusted 9