Aging and Housing Equity: Another Look

This chapter examines the change in the home equity of older families as they age, beginning at ages just before retirement. It uses data from the Health and Retirement Study (HRS), the Asset and Health Dynamics Among the Oldest Old (AHEAD) survey, as well as the Survey of Income and Program Participation (SIPP). It distinguishes changes in housing equity that might be thought of as part of a financial plan to use housing equity as a means of general support in retirement from changes in housing equity that are precipitated by family shocks—death or severe illness. The chapter extends the analysis in Steven Venti and David Wise, in which it was found that in the absence of changes in household structure, most elderly families are unlikely to move. The chapter also shows that even among movers, those families that continue to own typically do not reduce home equity.

Depressive symptomatology has been frequently conceptualized as an individual matter, but social contextual models argue that symptom levels are likely to covary in close relationships. The present study investigated correlation between spouses' depressive symptomatology in middle-aged and older married couples, the influence of gender and race/ethnicity in predicting variability in symptom level, and the importance of individual-level covariates (education, health, and age) and couple-level covariates (household income and net worth). Results were based on secondary analysis of Wave 1 interviews with White, Black, and Mexican American married couples (N = 5,423) from the Health and Retirement Study (HRS) and the Study of Asset and Health Dynamics Among the Oldest Old (AHEAD). Dyadic data from husbands and wives were analyzed with multilevel modeling. Husbands' and wives' depressive symptoms were moderately correlated, gender and race/ethnicity (and their interaction) predicted depressive symptoms, and both individual-level and couple-level characteristics were significant covariates. Similarities as well as differences are noted between the HRS and AHEAD results. Results highlight the importance of dyadic data and multilevel models for understanding depressive symptomatology in married couples. The influence of race/ethnicity merits greater attention in future research. Differences in findings between HRS and AHEAD suggest life-course, cohort, or methodological influences.

Enhancing the Quality of Data on the Measurement of Income and Wealth

Guardianship and the Representative Payee Program

The purchase of a home is the largest investment made by most American families, and home equity is the largest component of family wealth. Scholars have long documented the social and economic merits of homeownership and explored the factors that influence access to it. However, despite the abundance of literature on homeownership and housing tenure choice, we lack a study that focuses on whether and how debt and wealth influence a household’s decision to own or rent a home. Using 2004 and 2008 panel data from the Survey of Income and Program Participation (SIPP), this study attempts to identify the causal effect of household debt and wealth on a household’s decision to change tenure choice by examining what factors influence transition from homeowner to renter or from renter to homeowner. Data analysis shows that household secured debt, household wealth, and household income play a significant role in household’s change in tenure choice. While race is not a significant factor influencing the likelihood of a homeowner transitioning to a renter, it was a significant factor for a renter transitioning to a homeowner. Minority renters are significantly less likely to become homeowners compared with white renters, even when controlling for wealth and debt.

One of the methods of increased privacy protection is the creation of synthetic data sets. In this article we consider the differences that emerge between synthetic and nonsynthetic data in one of the very few attempts to create a synthetic data file for a major household survey data set, the Survey of Income and Program Participation (SIPP). The data we use are nonsynthetic and synthetic versions of the SIPP linked to administrative earnings histories, known as the SIPP Gold Standard File (GSF) and the SIPP Synthetic Beta (SSB), respectively. We present a set of results on short-run earnings dynamics estimated on both the SSB and the GSF, focusing on earnings volatility—the variance of short-run earnings growth rates—as well as an error components decomposition of inequality into permanent and transitory components. We find that short-run instability—both volatility and the transitory component of earnings inequality—is higher in the SSB than the GSF although the differences are somewhat dependent on modeling choices and the treatment of low earnings. Differences between the two data sets emerge both because cross-sectional inequality is higher in the SSB than in the GSF and because the dynamics of earnings over both shorter and longer periods appear to be different.

Research on economic need in the United States dates back at least to Jacob Riis's classic 1890 book, How the Other Half Lives. In the century since that publication, government efforts to reduce poverty have expanded enormously. Along with the expansion of anti-poverty programs, the demand for research on the nature of economic need in this country has mushroomed. A primary motivation for beginning the Survey of Income and Program Participation (SIPP) was to provide more and better information on families' level of eco­ nomic need and their use of government programs. This paper analyzes the ex­ tent to which SIPP has fulfilled that promise and presents recommendations for further changes and improvements in SIPP that might make it more useful to those who want to investigate poverty and anti-poverty programs. Data on income and program participation serve four basic functions in un­ derstanding poverty. First, income statistics are used to calculate measures of economic need, such as the official poverty rate, which are used as a measure of economic and social progress. Second, comparative measures of economic need across different subgroups of the population provide a measure of the relative progress and well-being of different groups in society, and help focus attention on those whose needs remain unmet. Third, data on program partici­ pation and family income provide information on who receives government transfer income and on how effective these programs are in reducing economic need. Fourth, repeated observations over time provide evidence on how all of these issues evolve. In particular, as anti-poverty programs and the macro

Are Homeownership Patterns Stable Enough to Tap Home Equity?

The dynamics of participation in government programs can be studied using longitudinal data from the Survey of Income and Program Participation (SIPP). This paper examines some of the issues involved in such analysis, focusing first on the kinds of analysis that SIPP data allow. The second section discusses the major problems with the SIPP that complicate longitudinal analyses. A concluding section suggests changes that could simplify and improve the data.

This chapter documents the trends in the life-cycle profiles of net worth and housing equity of older persons. During the 1993-2004 period, older households' net worth rose significantly, yet net worth grew by more than housing equity, in part because other assets also appreciated at the same time. Moreover, the younger elderly offset rising house prices by increasing their housing debt and used some of the proceeds to invest in other assets. The chapter considers how much of their housing equity older households could actually tap using reverse mortgages. It shows that this fraction is lower at younger ages, such that young retirees can consume less than half of their housing equity. Their results imply that consumable net worth is smaller than standard calculations of net worth.

We propose a new methodology that does not assume a prior specification of the statistical properties of the measurement errors and treats all sources as noisy measures of some underlying true value. The unobservable true value can be represented as a weighted average of all available measures, using weights that must be specified a priori unless there has been a truth audit. The Census Bureau's Survey of Income and Program Participation (SIPP) survey jobs are linked to Social Security Administration earnings data, creating two potential annual earnings observations. The reliability statistics for both sources are quite similar except for cases where the SIPP used imputations for some missing monthly earnings reports.

Although a vast amount of literature on the characteristics of public assistance recipients exists, little is known about the characteristics of the clientele of nonprofits that provide material assistance. This study examines the question of who receives material assistance from nonprofits. Three panels of the Survey of Income and Program Participation (1996, 2001, and 2004) adult well-being module were used to see if the use of nonprofit assistance is associated with individual and household characteristics, type of material hardship, and the use of other sources of assistance. Results show that poverty status, education, area of residence, and public program participation have a significant association with nonprofit material assistance, regardless of the type of material hardship and the use of other sources of assistance. These associations stayed relatively stable during the years of observation. It is interesting that households headed by an individual with college education were more likely than those headed by an individual without a high school diploma to receive material assistance from nonprofits. These findings may help nonprofits develop appropriate assistance programs and reach target populations. KEY WORDS: low-income households; material assistance; material hardship; nonprofits; social service ********** Material hardship is a condition of failure to meet the minimum levels of very basic goods and services, such as food, housing, and medical needs (Beverly, 2001, p. 143). In the United States, one in every 10 people lives in material hardship (Beverly, 2001). To help those with material hardship, government at various levels and nonprofit groups provide a wide range of material assistance. During the recent economic downturn, the need for material assistance rose and an increasing number of people turned to nonprofits for assistance (Ducey, 2009). Despite the important role of nonprofits in social assistance historically and currently (for example, Allard, 2008; Lipsky & Smith, 1989; Young, 1999), little is known about the clientele of the nonprofit sector (Allard, 2008). Two reasons may account for this. First, nonprofit assistance is still small in size and scope relative to public assistance, although this is changing as the partnership between government and nonprofits grows (Salamon, 1995; Young, 1999). Second, as noted by Allard, the local nature of service providers poses a challenge to research on nonprofit groups, and this is partly reflected by the lack of nationally representative data on the use of nonprofit assistance by individuals. Despite how little we know about the clientele of the nonprofit sector, a huge gap can be seen in the extent of material hardship and the availability of material assistance to the needy. Because of this, nonprofits are expected to play a larger role in social assistance to the needy (Alexander, Nank, & Stivers, 1999; Salamon, 1995). For this to happen, we need to look closely at who receives material assistance from nonprofits and what factors are associated with the use of nonprofit assistance. An inquiry into these questions will not only benefit nonprofits as they try to develop appropriate assistance programs and reach target populations, but also inform policymakers of the similarities and differences between the clientele of the nonprofit sector and that of the public sector. The Survey of Income and Program Participation (SIPP), which incorporates questions regarding nonprofit assistance, makes it possible to closely study the clientele of nonprofit assistance. Three panels of the SIPP (1996, 2001, and 2004) were used by the current study to examine the characteristics of nonprofits' clients and the determinants of the use of nonprofit assistance by families with material hardship. BACKGROUND Theoretical Perspectives As is widely recognized, nonprofit assistance is distinct from other sources of assistance, such as government, family, and friends. …

When debating the effect of undocumented immigrants on the economy, scholars often presume that undocumented immigrants are wage laborers rather than business owners. This study imputes the legal status of Mexican and Central American immigrants (MCAs) in the Survey of Income and Program Participation (SIPP) between 1996 and 2008 to evaluate how legal status affects business ownership patterns. From 1996 to 2008, the SIPP asked a series of questions about business ownership and migration history that make it uniquely suited to an investigation of undocumented MCA business owners. Instrumental variables regressions reveal that undocumented immigrants had a lower likelihood of owning a business than documented immigrants, but undocumented and documented business owners derived similar incomes from their businesses. A lack of legal status may hold back potential entrepreneurs. MCA business owners of both legal statuses clustered into similar low-paying, low-growth industries, however, so regardless of legal status, there are likely limits to how much business ownership can promote economic mobility among MCAs. All told, scholars should do more to acknowledge the existence of undocumented immigrant business owners, measure their impact on the economy, and examine their influence on immigrant incorporation patterns.

Federal survey data collection identifies people with disabilities predominantly by using a 6-question sequence asking about different functional impairments known as the American Community Survey-6 (ACS-6). However, little is known about the specific diagnoses identified by the ACS-6 or whether they vary across demographic subgroups. To characterize the disability diagnoses identified by the ACS-6 and assess to what extent they identify a consistent population across demographic subgroups. This cross-sectional study among people with disabilities responding to the 2023 or 2024 Survey of Income and Program Participation (SIPP) assessed the prevalence of 36 different diagnosis groupings in the ACS-6 as a whole and within each of the individual questions, as well as how the identified diagnoses varied by age group, race and ethnicity, sex, and educational attainment, with further disaggregation by cognitive disability status. Data were analyzed between August 1 and September 15, 2025. Identification as people with disabilities using the ACS-6. Diagnoses reported by survey respondents as causing the functional impairments they listed in the SIPP. A total of 13 341 people with disabilities (52.2% female; mean [SD] age, 53.0 [23.0] years) responding to the SIPP were included. Among people with disabilities aged 22 to 64 years, the most common diagnoses were anxiety or obsessive-compulsive disorders (prevalence, 15.6%; 95% CI, 14.5%-16.9%), depression (15.3%; 95% CI, 14.1%-16.5%), unspecified musculoskeletal issues (13.5%; 95% CI, 12.5%-14.6%), back or spinal problems (11.6%; 95% CI, 10.6%-12.6%), and unspecified neurologic disorders (10.8%; 95% CI, 9.8%-11.8%). The most common disability diagnoses reported by respondents identified by the ACS-6 were different across age groups but similar across demographic groups defined by sex, race and ethnicity, and educational attainment. The results of this cross-sectional study suggest that the ACS-6 identifies a similar population across demographic subgroups not characterized by age but highlight substantial heterogeneity in the population of people with disabilities within these subgroups and across age groups. Contemporary debates regarding future revisions to disability data collection in federal population surveys should address the ability to account for this heterogeneity in survey design.

Time limits are among the most fundamental of recent welfare reforms. Whereas welfare benefits were an entitlement under the old Aid to Families with Dependent Children (AFDC) program, the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA), which replaced AFDC with the Temporary Aid to Needy Families (TANF) program, restricts most families to 60 months of federally funded benefits. Although the states are free to extend benefits further using their own funds, almost all have incorporated some sort of time limit into their TANF programs. Time limits may affect welfare receipt in two distinct ways. The most obvious effect is mechanical, reducing welfare use once recipients exhaust their benefits. However, time limits may also reduce welfare receipt before recipients reach the limit. If families are forwardlooking, they may reduce their current welfare use in order to preserve their benefits for the future. The purpose of this paper is to provide evidence on such anticipatory, or behavioral, effects of time limits. I use data from the Survey of Income and Program Participation (SIPP) to replicate my earlier estimates based on the Current Population Survey (CPS). I also exploit the SIPP to relax some of the restrictive assumptions that were implicit in my previous work.