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Comparisons of individual life expectancies over time and across demographic groups provide information for individuals making retirement decisions and for policy makers. For couples, analogous measures are the expected years both spouses will be alive (joint life expectancy) and the expected years the surviving spouse will be a widow or widower (survivor life expectancy). Using individual life expectancies to calculate summary measures for couples is intuitively appealing but yields misleading results because the mortality distribution of husbands and wives overlap substantially. To illustrate, consider a wife aged 60 whose husband is 62. In 2010, her life expectancy was 24.4 years and his 20.2 years. The intuitions that the spouses will die at about the same time (e.g., within 5 years of each other) and that she will not live for a long time after his death are incorrect. The probability that the wife will outlive her husband is 0.63 and, if she does, her survivor life expectancy is 12.5 years. Using 2010 data, we investigate differences in joint and survivor life expectancy by race and ethnicity and by education. We then calculate trends and patterns in joint and survivor life expectancy in each census year from 1930 to 2010.

Using data from the Health and Retirement Study (HRS), we make two contributions to the literature on end-of-life transfers. First, we show that unequal bequests are much more common than generally recognized, with one-third of parents with wills planning to divide their estates unequally among their children. These plans for unequal division are particularly concentrated in complex families, that is, families with stepchildren and families with genetic children with whom the parent has had no contact (e.g., children from previous marriages). We find that in complex families past and current contact between parents and children reduces or eliminates unequal bequests. Second, although the literature focuses on the bequest intentions of parents who have made wills, we find that many elderly Americans have not made wills. Although the probability of having a will increases with age, 30 percent of HRS respondents aged 70 and over have no wills. Of HRS respondents who died between 1995 and 2010, 38 percent died intestate (i.e., without wills). Thus, focusing exclusively on the bequest intentions of parents who have made wills provides an incomplete and misleading picture of end-of-life transfers.

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Since 1950 the sources of the gains from marriage have changed radically. As the educational attainment of women overtook and surpassed that of men and the ratio of men's to women's wage rates fell, traditional patterns of gender specialization in work weakened. The primary source of the gains to marriage shifted from the production of household services and commodities to investment in children. For some, these changes meant that marriage was no longer worth the costs of limited independence and potential mismatch. Cohabitation became an acceptable living arrangement for all groups, but cohabitation serves different functions among different groups. The poor and less educated are much more likely to rear children in cohabitating relationships. The college educated typically cohabit before marriage, but they marry before conceiving children and their marriages are relatively stable. We argue that different patterns of childrearing are the key to understanding class differences in marriage and parenthood, not an unintended by-product of it. Marriage is the commitment mechanism that supports high levels of investment in children and is hence more valuable for parents adopting a high-investment strategy for their children.

In this paper we provide an overview of the patterns of intergenerational proximity and coresidence of adult children and their mothers in the U.S., using data from the National Survey of Families and Households (NSFH) and the U.S. Census. We highlight the importance of three specification and sample choices in the analysis. First, most previous studies consider coresidence to be the limiting case of proximity, using Tobit, ordered logit, or ordered probit specifications. We argue that proximity and coresidence are qualitatively different, and show that the multinomial logit provides a better representation of the patterns in the data. Second, we argue that substantial differences in the correlates of proximity by gender and marital status indicate the importance of modeling these categories separately. Third, the NSFH allows us to consider the proximity of couples to both his mother and her mother. This information is rarely available in survey data but is important for complete analyses. Our results show that education and age are the most robust predictors of proximity: college graduates are less likely to live near their mothers and older children live further from their mothers. Other demographic variables such as race, ethnicity and only child status also affect the probability of close proximity and coresidence. However, characteristics indicating adult children's current need for transfers (e.g. grandchildren) are not correlated with either close proximity or coresidence, while characteristics indicating mothers' current needs for transfers (e.g., disability) are correlated with coresidence but not close proximity.

In this paper we provide an overview of the patterns of intergenerational proximity and coresidence of adult children and their mothers in the U.S., using data from the National Survey of Families and Households (NSFH) and the U.S. Census. We highlight the importance of three specification and sample choices in the analysis. First, most previous studies consider coresidence to be the limiting case of proximity, using Tobit, ordered logit, or ordered probit specifications. We argue that proximity and coresidence are qualitatively different, and show that the multinomial logit provides a better representation of the patterns in the data. Second, we argue that substantial differences in the correlates of proximity by gender and marital status indicate the importance of modeling these categories separately. Third, the NSFH allows us to consider the proximity of couples to both his mother and her mother. This information is rarely available in survey data but is important for complete analyses. Our results show that education and age are the most robust predictors of proximity: college graduates are less likely to live near their mothers and older children live further from their mothers. Other demographic variables such as race, ethnicity and only child status also affect the probability of close proximity and coresidence. However, characteristics indicating adult children's current need for transfers (e.g. grandchildren) are not correlated with either close proximity or coresidence, while characteristics indicating mothers' current needs for transfers (e.g., disability) are correlated with coresidence but not close proximity.