Aging and Housing Equity

Aside from Social Security and, for some, employer-provided pensions, housing equity is the principle asset of a large fraction of older Americans. Many retired persons have essentially no financial assets to support retirement consumption. We use data from the Health and Retirement Study (HRS), the Asset and Health Dynamics Among the Oldest Old (AHEAD), and the Survey of Income and Program Participation (SIPP) to understand the extent to which families use housing equity to support general consumption in retirement. The initial analysis is based on self-assessed home values reported by survey respondents. Because the self-assessments exaggerate actual home equity, much of the subsequent analysis is based on the selling price of recently sold homes, together with the reported equity in recently purchased homes. Homeowners can change home equity by either discontinuing ownership or by purchasing another home of lesser or greater value. We find that in the absence of a precipitating shock-death of a spouse or entry of a family member into a nursing home--families are unlikely to discontinue home ownership. And even when there is a precipitating shock, discontinuing ownership is the exception rather than the rule. On average, families that move and purchase a new home tend to increase home equity. We find, however, that income-poor and house-rich families are more likely to reduce equity when they move, while house-poor and income-rich households are more likely to increase housing equity. Overall, accounting for discontinuing ownership and moving to another home, housing equity increases with age until about age 75 and then declines slightly as households grow older. The overall decline among older households (surveyed in the AHEAD) is about 1.76 percent per year, and this decline is largely accounted for by a 7.84 percent decline among households who experience a precipitating shock. Families that remain intact reduce housing equity very little, about 0.11 percent per year for two-person households and 1.15 percent per year for one-person households. We conclude that, on average, home equity is not liquidated to support general non-housing consumption needs as households age.

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

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

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.

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.

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.

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.

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.

Undocumented status is widely recognized as an important social determinant of health. While undocumented immigrants have lower levels of health care access, they do not have consistently poorer physical health than the US-born or other immigrant groups. Furthermore, heterogeneity by race/ethnicity has been largely ignored in this growing literature. This paper used the 2001, 2004, 2008 panels of the restricted Survey of Income and Program Participation (SIPP), one of the only representative surveys equipped to adequately identify Asian undocumented immigrants, to compare health patterns between Asians and Latinos by immigration status. We examined three general measures of health/health access: self-rated health, disability, and current health insurance. Latino undocumented immigrants displayed some advantages in self-rated health and disability but had lower insurance coverage compared to US-born Latinos. In contrast, Asian undocumented immigrants did not differ from US-born Asians in any of the three outcomes. While undocumented status has been proposed as a fundamental cause of disease, we found no evidence that Latino and Asian undocumented immigrants consistently fare worse in health access or physical health outcomes than immigrants in other status categories. Different racial groups also appeared to have unique patterns between immigration status and health outcomes from one another.

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. …

Summary Review of Data Sources for School to Work Transitions by Youth with Disabilities - Policy Brief

Do panel surveys really make people sick? A commentary on Wilson and Howell (60:11, 2005, 2623–2627)

BackgroundEarlier research has documented an association between depressive symptomatology and heightened stroke risk. However, prior work largely assessed depressive manifestations at isolated time points and failed to differentiate symptom subtypes. This investigation seeks to characterize the longitudinal progression of depressive symptoms via repeated measurement and explore their link to stroke risk by considering total depressive symptoms alongside cognitive-affective and somatic dimensions.MethodsThis prospective cohort study included individuals aged ≥ 45 years from the Health and Retirement Study (HRS) in the United States and the English Longitudinal Study of Ageing (ELSA) in the United Kingdom, excluding those with a history of stroke during the exposure period. Depressive symptoms were measured using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D) across four biennial assessments. Individuals were categorized into five distinct depressive symptom trajectories: consistently low, decreasing, fluctuating, increasing, and consistently high, based on assessment scores. Over a subsequent decade of follow-up, incident strokes were identified through self-reported physician diagnoses. The analyses incorporated adjustments for demographic factors (sex, age, etc.), health-related behaviors (smoking, drinking, etc.), and health status covariates (hypertension, diabetes, etc.). Cox proportional hazards regression models generated hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate links between trajectories of total depressive symptoms, cognitive-affective and somatic subtypes, and stroke occurrence.ResultsThe final cohort included 10,011 participants (63.3% female; mean age 60.2 years). During the 10-year follow-up, 720 incident strokes were recorded. Analyses demonstrated that, after adjusting for the aforementioned demographic and health-related confounders, relative to the consistently low trajectory, participants with fluctuating (HR = 1.24, 95% CI: 1.01–1.52), increasing (HR = 1.31, 95% CI: 1.03–1.67), and consistently high (HR = 1.42, 95% CI: 1.03–1.97) total depressive symptom trajectories exhibited significantly elevated stroke risk. Conversely, the decreasing trajectory (HR = 1.11, 95% CI: 0.85–1.45) did not significantly impact stroke risk. Furthermore, an increasing trajectory of cognitive-affective depressive symptoms (HR = 1.43, 95% CI: 1.13–1.82), alongside fluctuating (HR = 1.27, 95% CI: 1.03–1.55) and consistently high (HR = 1.97, 95% CI: 1.42–2.74) somatic depressive symptom trajectories, were each significantly associated with heightened stroke risk. Critically, the consistently high somatic trajectory demonstrated the most robust association with stroke.ConclusionTrajectories of total depressive symptoms marked by escalation, instability, or sustained elevation exhibited significantly elevated stroke risk. In contrast, individuals displaying decreasing depressive symptoms exhibit stroke risk comparable to those maintaining consistently low levels. Specifically, an ascending trajectory of cognitive-affective symptoms, alongside unstable and persistently elevated trajectories of somatic symptoms, are linked to increased stroke risk. These findings emphasize the clinical importance of monitoring dynamic changes in depressive symptoms and their subtypes for stroke prevention. Future investigations should elucidate underlying mechanisms to refine identification and intervention strategies for high-risk populations.