5
The Elderly and Their Kin: Patterns of Availability and Access

Douglas A. Wolf

INTRODUCTION

In recent years the field of family demography has developed rapidly. These developments include theoretical and methodological advancements and an especially rapid growth of applied research driven by the availability of large, nationally representative household surveys, as well as several longitudinal data sources (for a survey of the field, see Bongaarts et al., 1987). This chapter addresses issues in what might be called the ''family demography of the elderly." First, and most fundamental, we consider the composition of families containing elderly. Under the heading "kin availability," we address the observability of kin structures, ranging from the simple—counts of living kin occupying specified relationships—to the complex—enumerations of individual surviving kin according to type of relationship, with each member of the kin group described by an array of attributes. The second major focus is summarized by the term "access" to kin, which here has two manifestations: either the face-to-face access implied by coresidence, or the less intense or sustained access implied by close spatial proximity

The author recognizes a debt to his collaborators on several papers—Rebecca Clark, Vicki Freedman, and Beth Soldo—whose efforts are reflected throughout this paper. Thanks also go to Linda Martin, Sam Preston, John Casterline, and Ron Lee for useful comments on an earlier draft of the chapter, and to Lena Rose Orlando for her help in preparing the manuscript.



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Demography of Aging 5 The Elderly and Their Kin: Patterns of Availability and Access Douglas A. Wolf INTRODUCTION In recent years the field of family demography has developed rapidly. These developments include theoretical and methodological advancements and an especially rapid growth of applied research driven by the availability of large, nationally representative household surveys, as well as several longitudinal data sources (for a survey of the field, see Bongaarts et al., 1987). This chapter addresses issues in what might be called the ''family demography of the elderly." First, and most fundamental, we consider the composition of families containing elderly. Under the heading "kin availability," we address the observability of kin structures, ranging from the simple—counts of living kin occupying specified relationships—to the complex—enumerations of individual surviving kin according to type of relationship, with each member of the kin group described by an array of attributes. The second major focus is summarized by the term "access" to kin, which here has two manifestations: either the face-to-face access implied by coresidence, or the less intense or sustained access implied by close spatial proximity The author recognizes a debt to his collaborators on several papers—Rebecca Clark, Vicki Freedman, and Beth Soldo—whose efforts are reflected throughout this paper. Thanks also go to Linda Martin, Sam Preston, John Casterline, and Ron Lee for useful comments on an earlier draft of the chapter, and to Lena Rose Orlando for her help in preparing the manuscript.

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Demography of Aging (e.g., that which accompanies residence in the same neighborhood or community). One of the more remarkable demographic trends of recent decades is a reduction in household size, a trend that has been noted for persons of all ages and in numerous countries. Although a number of underlying factors help explain this trend, one of particular importance with respect to older people is a post-World War II trend toward having fewer children with whom to coreside. As illustrated below, however, this trend has recently reversed (or will soon reverse) in many industrialized countries. Household structure (or "living arrangements") is thus in part a consequence of patterns of kin availability and is the second major topic addressed in this chapter. The third and final topic addressed is the spatial proximity of elderly and their kin, especially their adult children. Throughout, an effort is made to survey, albeit selectively, theoretical, methodological, and empirical contributions to the relevant literature. Some attention is also devoted to enumerating existing data sources that figure prominently in actual (or potential) research. KIN AVAILABILITY Demographers and other social scientists have a long history of interest in kinship. Lotka (1931), in an article on the relationship between mortality and orphanhood, developed methods for determining the probability that a person at a given age has a living parent. More generally, demographers have devoted efforts to describing kinship patterns and to the formulation of models that relate kin patterns to underlying demographic forces. These issues are the concern of the present section. Kin availability is of particular importance with respect to the elderly, since members of the kin group constitute a resource pool—with "resources" construed broadly to encompass space (i.e., shared residential space), time, and money—on which elders in need of care or assistance can call. The kin group also represents, of course, a set of potential claimants on similar resources held by the elderly. Thus the composition of a kin group defines a complex set of potential interpersonal linkages that are of substantive interest. Conceptual Issues Inclusiveness of Measures Before attempting to measure patterns of kin availability, it is necessary to establish the scope of the term "kin." Our concern is with kin groups

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Demography of Aging containing at least one elderly person. The specific labels attached to linkages between individuals differ according to who in the kin group is taken to be the reference person, or "ego"—for example the relationship between two individuals may be "uncle" or "nephew" depending on who is ego. Furthermore it is clear that in common usage of the term, a person is likely to simultaneously be part of more than one kin group; this is especially true of married people. The range of relationship ties encompassed in the term "kin group" will differ across studies and across disciplinary lines. It should also be noted that descriptions of kin patterns are rarely of purely intrinsic interest; rather, of interest are the roles occupied, and the functions performed, by individuals in the network, and the dynamics through which these roles and functions develop. As has been demonstrated in numerous sociological and anthropological studies, the nature, composition, and functioning of kin groups differ considerably across cultural, ethnic, and/or racial lines, and the inclusiveness of kin groups can extend well beyond ties defined by blood and marriage (see, for example, the classic study of urban blacks in the United States by Stack, 1974). Nevertheless, this chapter adopts a narrowly demographic perspective, limiting its attention to relatives defined with respect to blood or marriage. This perspective reflects a desire to relate kin patterns to underlying demographic processes. It also reflects a concern with the ability to generalize from empirical findings, which leads to an emphasis on research based on population data or on data from large-scale surveys. Available data, in turn, tend to provide only a limited range of information on the composition of kin groups. In fact, the following discussion is generally restricted to immediate relatives—parents, siblings, and children—and only occasionally extends to more distant kin found along direct lines of ascent or descent, such as grandparents and grandchildren. Among the married elderly, the spouse is possibly the most important member of the kin group. Moreover, the death of a spouse is a key life course transition, experienced in most cases late in life, and is often accompanied by major shifts in economic circumstances. Nevertheless, this chapter devotes very little attention to spouses: data availability is considerably more problematic for kin relationships other than spouse; modeling issues are more complex for relationships such as child, parent, and sibling (where the number, not just the existence, of such kin is itself a variable); and the consequences considered here—coresidence and proximity—are the result of very different underlying processes for spouses and for other members of kin groups. Even with a narrow demographic conception of kinship, observed shifts or long-term trends in patterns of divorce, remarriage, and childbearing imply that the kin-availability patterns of successive cohorts of elderly will

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Demography of Aging become more and more complex. The "blended family" so prevalent in some contemporary societies, in which one or more spouses/partners are in second (or higher-order) marriages containing children from two or more marriages, is an example of a phenomenon that will increase the prevalence of half- and stepchildren and siblings (among others), in addition to own and in-law children and siblings, in the kin groups of the elderly. These considerations raise issues of measurement and analysis that have scarcely been addressed in the literature on old-age living arrangements and family support behavior. Demographic Forces Underlying Kin Availability It is evident that the essential demographic forces that determine the size, age structure, and gender mix of a population—patterns of birth and death, by age—underlie patterns of kin availability as well. To fertility and mortality rates we must add patterns by age of marriage, divorce, and remarriage as well, since marriage creates linkages among the parents, siblings, and offspring of married couples, whereas divorce and later remarriage modify and further widen the network of kin and the interrelationships between individuals in the kin group. At a specified age, the size and composition of one's kin group provide a partial record of one's demographic history. The survivorship and ages of parent(s), for example, reflect the parents' ages (and, therefore, their relative ages) at ego's birth—for any selected ego—as well as the specified age of ego and the relevant age- and sex-specific mortality rates. The same is true with respect to ego's spouse. The presence in ego's kin group of living siblings with specified characteristics depends on parental fertility history, ego's position in that history, and the relevant patterns of survivorship, while the number, ages, and gender mix of living children reflect ego's own childbearing history as well as survival patterns within the relevant cohorts. Finally, the presence and age/sex attributes of any in-laws, stepsiblings, stepparents, and/or stepchildren, all reflect the history of divorce, remarriage, and childbearing within specific marriages. Thus, indicators of the size and composition of kinship networks will be influenced by changes in age- and sex-specific mortality, fertility, marriage, divorce, and remarriage rates, as well as by age differences between spouses. It is beyond the scope of this chapter to attempt any characterization of the many and complex trends in any of these underlying demographic processes. Consider, however, an array of indicators of the size and composition of kin networks. For a randomly selected older woman, for example, we might wish to measure whether a spouse is present; the number of surviving sisters (brothers); the number of surviving married (unmarried) daughters (sons); the number of surviving parents; and so on. Analy-

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Demography of Aging sis of the effects on each such indicator of changes in any of the underlying demographic forces—an upward or downward shift in fertility rates at all ages, or movement to the right of the age curve of first marriage, or a lowering of sex-specific and age-specific death rates, for example—leads to the following general conclusions. First, each of the underlying demographic forces will have consequences for many, if not all, of the selected indicators. Second, each indicator will tend to be affected by changes in many, if not all, of the underlying demographic forces. Finally, the net effect on any indicator of a change in any one of the underlying demographic factors will depend on levels and trends in all the other factors, as well as any interactions among them. Complexities of these sorts have been addressed by using a variety of demographic models; these models are discussed in more detail below. Empirical Issues Aggregate Measures of Kin Availability Population aging is an aggregate phenomenon, one revealed by a change in the age structure of a population. It is possible to construct simple measures of one aspect of kin availability—the availability of children—in the aggregate, by using population data. An early contribution to the modern literature is an often-cited study by Kobrin (1976), who showed that the path of a simple measure of kin availability—the ratio of "daughters" (women aged 35-44) to their unmarried "mothers" (widowed and divorced women aged 55 and over)—closely paralleled that of average household size in the United States during the period 1890-1973. Measures based on aggregate data, such as those used by Kobrin, have certain limitations. For example, it is impossible to align population counts exactly by age so that they delineate distinct generations. Furthermore, aggregate measures provide information only about the average of kin-availability patterns, omitting important features such as the extent to which the elderly are childless or to which adults are without living parents. Yet aggregate measures have the obvious virtues of demanding only minimal information—population counts by age and sex (and, in the case of Kobrin's series, marital status)—and of showing clearly the relationship between population aging and average kin-availability patterns. Figure 5-1 illustrates the time path of a variant of Kobrin's index (in particular, its reciprocal) for selected major regions of the world, using regional groupings and data produced by the Population Division of the United Nations.1 The underlying data reflect actual data (including esti- 1   The data are extracted from the series "Sex and Age 1950-2025" and are described fully in the United Nations (1993).

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Demography of Aging Figure 5-1 "Mother-daughter" ratio for selected regions of the world, 1950-2025. mates) for most countries through 1985 or 1990, and the United Nations' medium variant projections thereafter. The "mother-daughter ratio" shown is the ratio of women 65 and older to women 25 years younger, a rough approximation of the mean length of a generation.2 In both the northern European countries as a whole and North America (Canada and the United States), a distinctive pattern can be seen, in which the mother-daughter ratio has climbed steeply for much of the period 1950- 2   Specifically, the ratio is calculated as where nx is the number of women in the indicated age group, and N65+ is the total number of women 65 and older. That is, in each of four "mothers" age groups, the ratio of that group to women in the 5-year age group 25 years younger is calculated; then the weighted sum of these four ratios is obtained, with weights representing the proportions that the mothers' age range represents, relative to all women 65 and older.

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Demography of Aging 1980. During the years 1990 through 2005, the upward trend is expected to reverse, although in neither region is the ratio expected to fall to levels as low as those seen in 1950; after 2005 the trend is projected to reverse once again, with an even sharper increase to unprecedentedly high levels by 2025, when the projected series ends. These curves clearly portray the late-life consequences of being in generations that successively produced baby "booms" and baby "busts." The northern European and North American patterns just described are not repeated in the other parts of the world shown in Figure 5-1. However, a pronounced rise in the mother-daughter ratio can be anticipated in eastern Asia after 2010, paralleled by a gentler increase in South America. Africa, with an overall pattern of sustained high fertility, exhibits a near-level mother-daughter ratio throughout the period of historical and projected data. Measures Based on Individual-Level Data Censuses and sample surveys have for the most part failed to produce information with which to describe kin-availability patterns, since they have usually focused their questions on individual respondents and the households in which they live. In a typical household-based survey, one or more individuals serve as respondents, generally either enumerating the other individuals with whom they live or providing responses that summarize the composition of the household. This generates information about only the coresident parts of kin groups. Less systematic is the availability of information on the full set of living kin for even a limited set of kin types. The existence of a spouse, even if not coresident, can often be inferred from survey items on marital status, although nonmarital unions may be poorly measured. Problems grow as we consider children, the category of most interest for studies of the elderly population. The crudest measure of available children is number of children ever born. Several existing data sources include information on the preferred measure, a count of living children, while some go further, eliciting information on each living child. Even less common are questions pertaining to siblings, grandchildren, and more distant relatives. A Sample of Microdata Sources As part of its monthly Current Population Survey (CPS), in which a large rotating sample of U.S. households is interviewed, the Census Bureau has included questions on kin availability, asked of all adults in sample households, on four occasions: July 1987, June 1988, November 1989, and June 1991. In these surveys, respondents were asked how many living natural parents, brothers, sisters, and children they had. Some descriptive

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Demography of Aging material from the 1988 survey is reported in Woodrow (1990), whereas findings based on the 1989 survey can be found in Woodrow and Peregoy (1991). From a methodological standpoint, these data (and other data generated by comparable survey items) confront the analyst with the phenomenon of "multiplicity sampling." That is, individuals classified according to a particular kin relationship are represented in the sample in proportion to their multiplicity in the population. For example, "sibships" of size four (represented by a respondent who has three siblings) have four times the chances of being sampled as do only-child sibships. Researchers who wish to present results in which the kin group is the unit of analysis must adjust sampling weights accordingly (for a fuller discussion of this issue, see Woodrow and Peregoy, 1991). These CPS files, which have the potential to support a range of interesting demographic analyses, have received little attention to date. Highlights of other major sources of U.S. data on the members of kin groups are presented here in brief. The 1984 Supplement on Aging (SOA) to the National Health Interview Survey contained only limited information on kin: counts of living sons, daughters, brothers, and sisters. A subset of these respondents was reinterviewed in 1986, 1988, and 1990 as part of the Longitudinal Study of Aging (LSOA; see Kovar et al., 1992). The kinship questions were not repeated in 1986, although the number of son/daughter questions was repeated in 1988 and 1990. Shanas's 1962 and 1975 surveys of the aged in the United States obtained, for each living child, the sex, marital status, birth order, work status, and (if not coresident with respondent) distance (expressed in travel time) from respondent (Shanas et al., 1968; Shanas, 1982). 3 The enumeration of a full roster of living children has also been accomplished in the National Long-Term Care Survey (NLTCS) of 1982, 1984, and 1989. In the NLTCS moreover, additional items were obtained for each child: their age, the presence in their household of minor children, and several indicators of each child's helping activities on behalf of the elderly respondent. A limitation of the NLTCS is its restrictive coverage: only individuals with long-term functional limitations were selected for interviewing. The 1987-1988 National Survey of Families and Households (NSFH; Sweet et al., 1988) used a large (N approximately 13,000) nationally representative household sample, and provided an extensive array of cross-sectional measures of the kin networks of its respondents.4 For adult children 3   The questionnaire used by Shanas in 1962 was also administered to samples drawn in Denmark and the United Kingdom; extensive results from the three surveys are reported in Shanas et al. (1968). 4   A follow-up interview of NSFH respondents was conducted in 1992.

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Demography of Aging outside the household and for living parents, information on age, sex, marital status, and distance from respondent is available; for parents, the respondent's assessment of parental health is also provided. Only limited information on respondents' siblings, however, was obtained. The spouses of married respondents were asked a parallel set of questions, thus allowing analysis of kin networks containing in-laws and stepchildren. The NSFH has been used in numerous studies on kin relationships involving the elderly, some of which are cited below. The Panel Study of Income Dynamics (PSID) is an ongoing annual survey of a sample originally containing about 5,000 families in 1968. Individual household members are tracked and interviewed if they depart from a previous sample household, so that over time the sample has grown to include about 7,000 families (Hill, 1992). In 1988, supplementary questions were added to the questionnaire, producing data on the existence and characteristics of nonresident parents and parents-in-law, and on time and money resource flows between the respondent's household and nonresident relatives. Analyses of the resource-flow data have recently begun to appear (Altonji et al., 1992; Furstenberg et al., 1993; Hill et al., 1993). The Health and Retirement Survey (HRS) is a prospective longitudinal study of a cohort of people approaching retirement age, the first interview of which took place in late 1992 (Juster, 1992). The HRS will provide, albeit for a sample restricted to the age range 51-61 in 1992, the most extensive array of information on kin networks for a large, representative household sample in the United States to date. For all living children, researchers will know age; sex; educational, work, and marital status; own children (i.e., respondent's grandchildren); and (if not coresident) distance from respondent. For all siblings and siblings-in-law, age, sex, and marital status will be recorded; for as many as four each of siblings and siblings-in-law, additional items on work, financial status, and household arrangements will be obtained.5 Similarly detailed information on each of the respondents' living parents and parents-in-law is also being collected. A parallel longitudinal study of the "oldest-old" is also planned, with many questionnaire items replicated from the HRS and a first wave of interviewing scheduled to occur in late 1993. This Asset and Health Dynamics (AHEAD) survey will, like the HRS, provide unusually detailed information about the kin networks of the elderly. The preceding survey indicates that existing and anticipated data from surveys of the U.S. elderly offer a variety of detail on respondents' kin networks. While some offer an extraordinary degree of detail, none are 5   If the respondent has more than four living siblings (siblings-in-law), interviewers select a random subset of four, for which the additional items are recorded.

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Demography of Aging complete. For example, none of the data sources reviewed provide information on linkages across kin groups, e.g. information on the in-laws of the respondents' married children. In addition to the sources discussed above, there are several other existing public-use data sources containing at least some information with which to study kin patterns. There are also several sources of microdata from other countries, particularly in Europe and Asia. Many of these additional data sources are used in applied studies cited later in this chapter; readers interested in details of the data sources should consult the references cited. Selected Results from Microdata Information about kin groups containing elderly can be provided by elderly survey respondents who enumerate their living kin, or it can come from nonelderly survey respondents who report the presence of elderly (e.g., parents) in their kin networks. The way in which the data are collected influences the way in which kin networks can be portrayed. Descriptive data on kin networks, drawn from data sources such as those enumerated above, have appeared in several places. The following discussion concentrates on findings from the most recent sources. A time series of information on kinship patterns for the United States can be assembled by combining data from several surveys. Crimmins and Ingegneri (1990) combined Shanas's 1962 and 1975 National Survey of the Aged (NSA) data with data from the 1984 SOA. Some of their findings, further augmented by data from the 1987-1988 NSFH, are displayed in Table 5-1. These data indicate that between 1962 and 1975, the proportion of elderly with no living children grew, while the proportion with many living children fell. From 1975 to 1984, the percentage childless fell, while the percentage with large numbers of surviving offspring rose slightly.6 As noted before, these figures tell a story of the demographic histories of successive cohorts of elderly. Table 5-1 presents data provided by elderly respondents. Such data can tell us, for example, the distribution by number of children (including zero) of kin groups containing elderly parents. What these data cannot reveal is the extent to which elderly parents appear in the kin groups of the nonelderly. 6   Comparisons between figures for 1984 and 1987 must be made with great caution because of limits on their comparability. As noted in the table, the 1987 figures pertain only to older women, whereas the earlier figures are for older men and women. Furthermore, the NSFH used a very detailed sequence of questions about children, obtaining separate counts of biological, step- and adopted children; this questionnaire detail may have produced higher (and, presumably, more accurate) levels of reported counts of children than did previously administered surveys.

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Demography of Aging TABLE 5-1 Percent Distribution of Population by Number of Surviving Children, Persons 65 and Older, United States (in percent) Number of Children 1962 1975 1984 1987a 0 18 21 14 21 1 15 20 18 16 2 17 21 25 22 3-5 27 28 31 }41 6+ 14 10 9   Total 100 100 100 100 a Women 65 and older only. SOURCE: Derived from data presented in Crimmins and Ingegneri (1990) and Wolf et al. (1991b). Table 5-2 considers the issue of kin groups containing elderly parents and their children, but uses data provided by adult respondents in the NSFH, of all ages. Table 5-2 should be read by column; in each column we find first the percentage of an age group with a living mother aged 65-84, classified by number of siblings, then the corresponding percentages with a mother 85 or older, followed by those whose mother is either under 65 or dead. The latter group constitutes a majority of all three age groups shown in the table. Of the three age groups shown, people 40-64 years old have the highest percentage with a living elderly mother, 44.6 percent. It is interesting to note that among those in this age group with a living mother, a substantial proportion has no siblings (11.7 percent). Children without siblings are likely to bear a larger burden of parental-care than those with siblings. Note that whereas Table 5-1 tells us that 16 percent of women 65 and older have exactly one living child, Table 5-2 tells us that only about 4 percent of the population simultaneously has no living sibling and a living mother 65 or older. That is, the sibships of size one that are attached to 16 percent of older women represent only about 4 percent of all extant only-child sibships. These distinctions, which illustrate the importance of the ''perspective" from which kin relationships are examined (Freedman et al., 1991), must be borne in mind when considering the distribution of familial links within the population, and must be made clear when presenting data on the size and composition of kin groups. As mentioned earlier, changes in cohabitation, divorce, remarriage, and childbearing lead to changes in the nature of kin networks, lending prominence to distinctions involving half- and stepsiblings/children/parents. Over

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Demography of Aging specialized sample, one containing 432 English couples (at least one member of which is of pensionable age), each of which has exactly two living children. The data measure current proximity and also provide unusually complete migration histories. Several regression results are presented, in which the dependent variable is the (log) distance between parents and children; a consistent result is that moves made by the child increase the distance between parents and children. The NSFH data, already described, include information on distance to nonresident parents and children. These data have been used in proximity models by Clark and Wolf (1992) and by Rogerson et al. (1993). Clark and Wolf use only those NSFH observations in which the respondent is 60 or older. In using this subsample, two types of logistic regression analysis are performed: the first uses as its dependent variable an indicator of whether the respondent has any nearby children (i.e., an indicator of whether the nearest child is "near"; defined as living within 10 miles of the respondent); the second uses the same underlying data but treats each parent-child pair as a separate observation. In each such parent-child pair, the dependent variable is an indicator of whether the child in question lives near the respondent. In this case, each child's proximity to his or her parent is treated as an independent outcome. The first model allows for simultaneity in children's proximity outcomes, without explicitly specifying the form of any such simultaneity, whereas the second model implicitly assumes away any simultaneity, and thus is restricted to providing inferences concerning the correlates of a child's marginal probability of living close to his or her parent. Finally, in Clark and Wolf (1992) the proximity measure studied is a binary indicator: coresident parent-child households are included in the near category. The findings reported by Clark and Wolf (1992) can be summarized as follows: parents with more resources—whether these resources are relative youth, high levels of educational attainment, or a living spouse—are less likely to live near a child than parents with fewer such resources. The more children an older respondent has, the more likely it is that he or she will live near at least one child. Having a married child—who presumably has competing obligations—reduces the likelihood of living near at least one child. Parents with never-married children are more likely to live near a child than those without, but this appears to be the result of the relative youthfulness of unmarried children, rather than their marital status, per se. Among the young-old, migrants are less likely than nonmigrants to live near a child, but by age 77 those who have moved within the last 5 years are more likely to live near a child than those who have not migrated. Children's characteristics are important in determining which child an elderly person lives near. In general, as children age and marry, they are less likely to live near their parents. However, a reversal occurs when the children them-

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Demography of Aging selves have children: having two or more children has a positive effect on proximity to parents that outweighs the negative effect of being married. In contrast to the Clark and Wolf study, Rogerson et al. (1993) use NSFH respondents who have living parents and thus analyze proximity of parent-child pairs using information provided by the child. Instead of a categorical indicator of proximity, Rogerson et al. use the natural logarithm of distance (in miles) from the respondent to the relevant parent, reporting separate analyses of those with (1) both parents alive and married to each other, (2) mother only alive, (3) father only alive, and (4) both parents alive, but not married to each other. For the latter group, separate regressions for distance to father and distance to mother are reported. Rogerson et al. also exclude from their analyses respondents who are coresiding with their parent. Although the same variables are not always significant in the five regressions reported, several patterns emerge from the findings. For example, respondents currently enrolled in college generally live farther from their parent(s) than others, and residents of the West consistently live farther from their parents. Migration history plays a role here as well: the greater is the distance of the child's most recent move, the greater is the distance to the parent (consistent with the result reported in Warnes, 1986). Offsetting this is a timing effect: the longer the time spent at the current address, the less is the distance to the parent or parents. In three of the five regressions, age (of respondent) has a significant effect: older children live farther from their parents than younger children, on average. The latter finding agrees with those in Clark and Wolf. Other points of comparability are more difficult to establish, due to differences in model specification and variable coding. Taken together, the Clark and Wolf (1992) and Rogerson et al. (1993) findings suggest an image of children who make geographic moves that remove them from close proximity to their parents; later, the parents make moves that again bring them into closer proximity. Whether parents indeed chase their children from location to location (and the prevalence of such a pattern, if it does occur) is an issue that must be addressed by using linked migration histories of parents and children; it cannot be addressed satisfactorily by using current proximity data. A final comment concerns the use of proximity as a covariate. Several studies have used proximity as one of several covariates in multivariate analyses of outcomes such as intergenerational resource flows (Eggebeen, 1992; Hoyert, 1991) and the provision of care by adult children to elderly parents (Lee et al., 1993). The preceding discussion suggests that proximity is itself an outcome, one resulting from the combined behavioral choices of parents and their children, and one motivated in part by the desire to facilitate intergenerational contact and/or resource flows. If so, then proximity

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Demography of Aging should not be treated as an exogenous covariate, but rather as an outcome jointly determined with the resource flow being examined. CONCLUSION At various points in this chapter, assorted deficiencies in the existing literature concerning kin availability, living arrangements of the elderly, and spatial proximity of elderly and their kin have been noted. These are not repeated here; rather, it is noted that they constitute a familiar litany: there is a need for more powerful theories, better data, improved methodologies, and more comprehensive empirical research. The foregoing review does suggest a number of areas in which future research could make useful contributions. For example, despite the limitations of existing data, the data in hand have not been utilized fully. For purposes of description, the development of new indices or other ways to represent the composition of kin networks—including, perhaps, graphical methods—would be of great value. From a methodological standpoint, existing data could be used to support more complex and detailed representations of the linkages between kin availability (as determinants) and living or proximity outcomes (as consequences). Indeed, complexity is a recurring theme in the literature on kinship patterns and their consequences, suggesting that efforts to promote and enhance the use of methods appropriate for complexities such as these would be of great value. The development of theoretical tools for analyzing kin networks would also be welcome. Of particular value would be the development of models of decision making in diffuse kin networks. Microeconomic theories have, for example, been extended beyond simple models of individual choice to more complex models placed in a household setting, including models in which individual preferences may be in conflict. Decisions involving potential migratory behavior, in combination with coresidence or close spatial proximity of an elderly parent and one or more of their children, are more complex still and require consideration of a broader array of preferences and constraints. I will close with a question not previously addressed, one that is entirely speculative in nature. In particular, trends over time in living arrangements (and, for that matter, in kin proximity) are readily analyzed as the consequence of other, more fundamental, trends such as changing family size (i.e., changing fertility patterns in earlier times), rising income, and possibly improved health. The observed trends could easily be thought to be the result of choices that reflect fixed preferences (or, alternatively, behavioral "propensities") in combination with a changing composition of the population making those choices. A larger, and considerably more difficult, issue is the question of feedback effects: As the age structure of the popu-

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Demography of Aging lation (an aggregate phenomenon) changes, becoming more aged, will the decision parameters of the elderly (or of their children) change? Will a greater prevalence of older people translate into altered norms governing intergenerational relations at the individual-, kin network level? These are questions that lend themselves less readily to empirical research of the sort given most attention in the present paper, but are offered as a potentially fruitful area for future research. REFERENCES Abbott, M., H. Abbey, D. Bolling, and E. Murphy 1978 The familial component in longevity: A study of offspring of nonagenarians. III. Intrafamilial studies . American Journal of Medical Genetics 2:105-120. Altonji, J., F. Hayashi, and L. Kotlikoff 1992 The Effects of Income and Wealth on Time and Money Transfers Between Parents and Children. Paper presented at the RAND Conference on Economic and Demographic Aspects of Intergenerational Relations, Santa Monica, Calif. Anderton, D.L., N.O. Tsuya, L.L. Bean, and G.P. Mineau 1987 Intergenerational transmission of relative fertility and life course patterns. Demography 24(4):467-480. Angel, R.J., J.L. Angel, and C.L. Himes 1992 Minority group status, health transitions, and community living arrangements among the elderly. Research on Aging 14(4):496-521. Aquilino, W.S. 1990 The likelihood of parent-adult child coresidence: Effects of family structure and parental characteristics. Journal of Marriage and the Family 52:405-419. Avery, R., A. Speare, and L. Lawton 1989 Social support, disability and independent living of elderly persons in the United States. Journal of Aging Studies 3:279-293. Ben-Akiva, M., and S.R. Lerman 1985 Discrete Choice Analysis. Cambridge: MIT Press. Beresford, J., and A. Rivlin 1966 Privacy, poverty and old age. Demography 3:247-258. Bishop, C.E. 1986 Living arrangements choices of elderly singles: Effects of income and disability. Health Care Financing Review 7(3):65-73. Bongaarts, J. 1987 The projection of family composition over the life course with family status life tables. Pp. 189-212 in J. Bongaarts, T. Burch, and K. Wachter, eds., Family Demography: Methods and Their Applications. Oxford: Clarendon Press. 1989 The demographic determinants of the duration and incidence of widowhood. Pp. 55-65 in E. Grebenik, C. Höhn, and R. Mackensen, eds., Later Phases of the Family Cycle. Oxford: Clarendon Press. Bongaarts, J., T. Burch, and K. Wachter, eds. 1987 Family Demography: Methods and Their Application. Oxford: Clarendon Press. Brass, W. 1983 The formal demography of the family: An overview of the proximate determinants. Pp. 37-49 in The Family. British Society for Population Studies (OCPS) Occasional Paper, No. 31. London: Office of Population Censuses and Surveys.

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