Survey Of Income And Program Participation Research Articles

Material Hardship Among Immigrants in the United States: Variation by Citizenship, Legal Status, and Origin in the 1996–2008 SIPP

Previous literature has explored different dimensions of immigrant incorporation; however, no extant literature describes the extent to which migration status is associated with a comprehensive set of material hardship dimensions. Using data from the Survey of Income and Program Participation (SIPP) spanning more than a decade (1996–2008), we assess material hardship among the foreign-born by migration status, a unique contribution of this data. Trends over the study period reflect the persistent migration status gradient in material hardship. Multivariate models point to three important findings. First, unauthorized and legally resident non-citizens had significantly increased odds of hardship compared to the naturalized. Second, the magnitude of the migration status-hardship association varied depending on hardship with naturalized citizens generally having lower odds of each form of hardship than unauthorized and legally resident non-citizens. Finally, patterns of material hardship by US duration were not uniform. For example, for utility hardships, the unauthorized with 10 or more years of US duration have higher predicted probabilities than unauthorized of shorter durations. The results highlight the challenges of the immigrant experience in America for recent arrivals, the unauthorized, for legal immigrants, and immigrants who have resided in the US for more than 10 years.

Value of Sample Separation Information in a Sequential Probit Model

We illustrate the estimation and identification of multi-step sequential probit models with and without stepwise sample separation information. The likelihood functions are explicitly derived to ease experimentation with such models. We used data on health, activity limitations, demographic traits and work from the Survey of Income and Program Participation (SIPP) and exactly matched them with Social Security administrative records to showcase our theoretical points. Using a Monte Carlo simulation technique, our results suggest that the correlations in errors across equations may arise due to unobserved individual heterogeneity. Using a novel marginal likelihood approach, we also estimated the above sequential probit model without the sample separation information for the purpose of direct comparison. In terms of both in-sample and jackknife-type out-of-sample predictive analysis, the value of modelling the underlying sequential structure of the determination process in generating correct membership probabilities of belonging to a particular group is confirmed. JEL: C31, C34, C 35, I12, I18

Many of the kids are not alright: Material hardship among children in the United States

The material well-being of children has profound implications for a variety of social and health outcomes. This paper provides estimates of the prevalence and intensity of material hardship among children by various demographic groups and reveals stark disparities by race and educational attainment. According to a pooled sample of the nationally-representative Survey of Income and Program Participation (SIPP) 36.5% of children lived in households reporting at least one form of material hardship, such as food insecurity, inability to pay essential household bills, inability to access medical care due to cost, or substandard and overcrowded housing. This is well above the proportion considered to be below the income poverty line (18.4%). Children were more likely to live in households experiencing material hardship than seniors.

Accounting for the burden and redistribution of health care costs: Who uses care and who pays for it.

ObjectiveTo measure the burden of financing health care costs and quantify redistribution among population groups.Data SourcesA synthetic population using data combined from multiple sources, including the Survey of Income and Program Participation (SIPP), Medical Expenditure Panel Survey (MEPS), Kaiser Family Foundation (KFF)/Health Research Educational Trust (HRET) Employer Health Benefits Survey, American Community Survey (ACS), and National Health Expenditure Accounts (NHEA).Study DesignWe estimate two dollar amounts for each individual in the synthetic population: (a) payments to finance health care services, which includes all payments by a household and their employers to finance health care, including premiums, out‐of‐pocket payments, federal and state taxes, and other payments; and (b) the dollar value of health care services received, which equals the amount paid to providers for those services.Data Extraction MethodsWe linked the nationally representative survey data using statistical matching. We allocated health care expenditures from the NHEA to individuals and households based on expenditures reported in the MEPS.Principal FindingsWe show that higher‐income households pay the most to finance health care in dollar amounts, but the burden of payments as a share of income is greater among lower‐income households.ConclusionsAccounting for all sources of payments provides a clear picture of the burden of financing health care costs, and how that burden is spread under our current financing system.

‘Home is where the health is’: Housing quality and adult health outcomes in the Survey of Income and Program Participation

Nearly a quarter of the homes in the United States were considered unhealthy or inadequate, but whether these housing characteristics have direct effects on health or whether they are driven by other contextual housing and neighborhood characteristics remains unclear. The purpose of this study was to quantify the independent associations between poor housing quality and adult health outcomes, adjusting for socioeconomic factors (e.g. income to poverty ratio, food insecurity) and other contextual housing characteristics (e.g. rental status, number of people per household, unsafe neighborhood). Using in-person household interview data from wave 1 of the 2014 Survey of Income and Program Participation (SIPP), a secondary analysis was performed using a series of logistic regression models. The 2014 SIPP sample is a multistage stratified sample of 53,070 housing units designed to represent the civilian, noninstitutionalized population of the United States (N = 55,281 adults ages 18 and older). Our results indicate that each additional poor housing characteristic was associated with poorer health status (OR: 1.17, CI [1.11, 1.23]), higher medical utilization (OR: 1.11 CI: [1.06, 1.16]), and a higher likelihood of hospitalization (OR: 1.07, CI [1.02, 1.12]). Non-housing-related government assistance, food security, and safe neighborhoods only partially explained associations between housing quality and health outcomes. Evaluating current local, state, and federal policy on housing quality standards may help determine if these standards decrease the number of Americans residing in inadequate homes or result in improvements in health and reductions in healthcare costs. Simply put, the home is where [we suggest] the health is.

Reconciling Trends in Volatility: Evidence from the Sipp Survey and Administrative Data

As part of a set of papers using the same methods and sample selection criteria to estimate trends in male earnings volatility across a number of survey and administrative datasets, we conduct a new investigation of trends in male earnings volatility from the 1980s to 2014 using data from the Survey of Income and Program Participation (SIPP) survey and the SIPP Gold Standard File (SIPP GSF), which links the SIPP survey to administrative data on earnings. We find that the level of volatility is higher in the SIPP GSF than in the SIPP survey but that the trends are similar. Specifically, over the period where the datasets overlap between 1984 and 2012, volatility in the SIPP survey declines slightly while volatility in the SIPP GSF increases slightly but the differences are small in magnitude. Because the density of low earnings differs considerably across datasets, and volatility may vary across the earnings distribution, we estimate trends in volatility in the SIPP survey and SIPP GSF where we hold the earnings distribution fixed to resemble that in the Panel Study of Income Dynamics (PSID). We find that differences in the underlying earnings distribution explains almost all of the difference in the level of volatility between the SIPP survey and SIPP GSF and it somewhat reduces the small differences in trends.

Family job search and wealth: The added worker effect revisited

We propose and estimate a model of family job search and wealth accumulation with data from the Survey of Income and Program Participation (SIPP). This dataset reveals a very asymmetric labor market for household members who share that their job finding is stimulated by their partners' job separation. We uncover a job search‐theoretic basis for this added worker effect, which occurs mainly during economic downturns, but also by increased nonemployment transfers. Thus, our analysis shows that the policy goal of increasing nonemployment transfers to support a worker's job search is partially offset by the spouse's cross effect of decreased nonemployment and wages. The added worker effect is robust to having more children and more education in the household and does not just result as a composition of heterogeneous individuals. We also show that the interdependency between household members is understated if wealth and savings are not considered. Finally, we show that gender equality in the labor market not only improves women's labor market performance, but it also increases men's accepted wages and nonemployment rates.

From Invisible to Visible to Valued: Improving Population Health of People With Intellectual and Developmental Disabilities.

From Invisible to Visible to Valued: Improving Population Health of People With Intellectual and Developmental Disabilities.

Setting Expectations for Claimant Ability to Work: Investigating the Occupational Requirements and Functional Capacity of Workers with Early Onset Health Conditions

When determining a claimant’s eligibility for Social Security Disability Insurance (SSDI) benefits, the Social Security Administration (SSA) assesses whether his/her health condition (e.g., back/spine problems) sufficiently impairs his/her functional capacity (e.g., ability to lift/carry weight) so that the he/she is unable to meet the requirements (e.g., need to lift/carry 25 pounds) of his/her previous occupation and other possible occupations. Using data from the Survey of Income and Program Participation (SIPP) and Occupational Requirements Survey (ORS), we compare the occupational requirements of workers with and without a given health condition in order to understand what to expect from claimants with that health condition. Although sample sizes are limiting and ORS data collection is not yet complete, we find some evidence that workers’ occupational requirements accommodate their health conditions. This evidence suggests that claimants with these health conditions may be able to fulfill the requirements in these occupations. We do find some evidence of the opposite causality: Workers may experience health conditions later in life from occupational requirements that may have caused their health conditions. This evidence is a caution against using data without onset information to inform claimant-ability expectations. Overall, this report provides evidence that national surveys with occupation, health, and function questions have the potential to inform revisions to the SSA disability determination process by providing information on people with health conditions who are working and meeting the requirements of a variety of occupations.

Work-limiting health, earnings, and employment: an analysis with SIPP data

ABSTRACTThis study examines the role of work-limiting health conditions on employed people’s earnings, employment status, and working hours, and distinguishes between the different degree and severity of predictable shocks. Using data from the 2004 Survey of Income and Program Participation (SIPP), we evaluate the impact of any work-limiting health condition as well as a subset of health conditions that appear to arrive largely exogenously on post-onset earnings, employment, and working hours. We find that people who report being employed and later experience the onset of any work-limiting health condition tend to have lower subsequent earnings, a reduced probability of being employed, and fewer working hours per month compared to those who remain healthy. The adverse impact is even greater for people with health conditions that arrive less predictably. We use a difference-in-differences regression model with person and year fixed effects as the primary estimation method.

Entry and Stability of Cross-National Marriages in the United States

As more and more people move across borders, marriage is becoming an increasingly global affair. Yet cross-national marriage (CNM) migration has not received the scholarly attention it deserves. The present study examines the characteristics and marital stability of unions between U.S. nationals and their foreign-born (FB) spouses residing in the United States. Two data sources were used in the analysis—the American Community Survey (ACS) and the Survey of Income and Program Participation (SIPP). Our results indicated that, after controlling for race/ethnicity, socioeconomic background and marital history, marriages between U.S. nationals and their FB spouses who entered the United States as adults were less stable than unions between two native-born (NB) spouses. Compared with non-Hispanic Whites, Asian and Hispanic U.S. nationals were more prone to marry FB spouses. We also found that husband NB–wife FB marriages seemed to fare better than wife NB–husband FB types.

Multi-outcome longitudinal small area estimation – a case study

ABSTRACTA recent paper [Thibaudeau, Slud, and Gottschalck (2017). Modeling log-linear conditional probabilities for estimation in surveys. The Annals of Applied Statistics, 11, 680–697] proposed a ‘hybrid’ method of survey estimation combining coarsely cross-classified design-based survey-weighted totals in a population with loglinear or generalised-linear model-based conditional probabilities for cells in a finer cross-classification. The models were compared in weighted and unweighted forms on data from the US Survey of Income and Program Participation (SIPP), a large national longitudinal survey. The hybrid method was elaborated in a book-chapter [Thibaudeau, Slud, & Cheng (2019). Small-area estimation of cross-classified gross flows using longitudinal survey data. In P. Lynn (Ed.), Methodology of longitudinal surveys II. Wiley] about estimating gross flows in (two-period) longitudinal surveys, by considering fixed versus mixed effect versions of the conditional-probability models and allowing for 3 or more outcomes in the later-period categories used to define gross flows within generalised logistic regression models. The methodology provided for point and interval small-area estimation, specifically area-level two-period labour-status gross-flow estimation, illustrated on a US Current Population Survey (CPS) dataset of survey respondents in two successive months in 16 states. In the current paper, that data analysis is expanded in two ways: (i) by analysing the CPS dataset in greater detail, incorporating multiple random effects (slopes as well as intercepts), using predictive as well as likelihood metrics for model quality, and (ii) by showing how Bayesian computation (MCMC) provides insights concerning fixed- versus mixed-effect model predictions. The findings from fixed-effect analyses with state effects, from corresponding models with state random effects, and fom Bayes analysis of posteriors for the fixed state-effects with other model coefficients fixed, all confirm each other and support a model with normal random state effects, independent across states.

Item Response Rates for Composite Variables

Abstract Item response rates frequently serve as indicators of data quality and potential nonresponse bias. However, key variables from surveys, such as total household income or net worth, are often composite variables constructed from several underlying components. Because such composite variables do not have clearly identifiable response rates, inference on the data quality of these key measures is more difficult. This article proposes three new methods for aggregating data on response rates across questions to create a measure of item response for composite variables. To compare the three methods and illustrate how they can be used (both individually and collectively) to investigate data quality, I analyze item response for net worth in the Survey of Income and Program Participation (SIPP) and the Survey of Consumer Finances (SCF). These new measures provide detailed information about net worth estimates that would be difficult to assess without an item response aggregation method. Overall, these new item response rate methods provide a new way of describing data quality for key measures in surveys and for analyzing changes in data quality over time.

Job Mobility and Sorting

Abstract Motivated by the canonical (random) on-the-job search model, I measure a person’s ability to sort into higher ranked jobs by the risk ratio of job-to-job transitions to transitions into unemployment. I show that this measure possesses various desirable features. Making use of the Survey of Income and Program Participation (SIPP), I study the relation between human capital and the risk ratio of job-to-job transitions to transitions into unemployment. Formal education tends to be positively associated with this risk ratio. General experience and occupational tenure have a pronounced negative correlation with both job-to-job transitions and transitions into unemployment, leaving the risk ratio, however, mostly unaffected. In contrast, the estimates suggest that human-capital concepts that take into account the multidimensionality of skills, e.g. versatility, play a prominent role.

Which one? What kind? How many? Types, causes, and prevalence of disability among U.S. adults

BackgroundQuantifying the number of people with and types of disabilities is helpful for medical, policy, and public health planning.Objective/Hypothesis: To update prior estimates on types, prevalence, and main causes of disability among U.S. adults using the Survey of Income and Program Participation (SIPP) data. MethodsWe used cross-sectional data from the SIPP 2008 Panel Wave 6 interviews collected May–August 2010. Analyses were restricted to non-institutionalized adults ages ≥18 years (n = 66,410). Disability was ascertained via five non-mutually exclusive components: 1) specific activity difficulties, 2) selected impairments, 3) use of an assistive aid, 4) household work limitations, and 5) paid work limitations. Prioritized main cause of disability was established for the 95% of respondents with a disability type eligible for health condition questions. We generated weighted population estimates (number and percentage, with 95% confidence intervals (CIs)), accounting for the complex sample survey design. Results50 million U.S. adults (21.8%) experienced a disability in 2010. Mobility-related activity limitations were the most prevalent disabilities across all five components. The most common main causes of disability were arthritis/rheumatism, 9.1 million (19.2%, 95% CI = 18.4–20.0) and back or spine problems, 8.9 million (18.6%, 95% CI = 17.9–19.3). ConclusionsA growing population with disabilities has the potential to put considerable and unsustainable demand on medical, public health, and senior service systems. Strengthening clinical community linkages and expanding the availability of existing evidence-based public health interventions to prevent, delay, and mitigate the effects of disability could improve health and outcomes for people with disabilities.

Failure to Contribute: An Estimate of the Consequences of Non- and Underpayment of Self-Employment Taxes by Independent Contractors and On-Demand Workers on Social Security

Over the past ten years, companies such as Uber, Etsy, Lyft, Airbnb, Care.com and Rover.com have become household names by connecting service providers and sellers with consumers online and through app-based programs. And this work is projected to continue to grow, along with the technology-enabled convenience of accessing goods and services through apps on smartphones in this new sector of the economy (referred to as the “On-Demand Economy” in this Report). Although it is not new that self-employed workers have tax compliance and reporting issues, the existing reporting rules applicable to most workers earning income working with On-Demand Economy platforms (e.g., Uber, Airbnb, Etsy) substantially increase the likelihood that these taxpayers fail to contribute to Social Security and Medicare through payment of Self-Employment tax (SE tax). This Report sheds light on the Social Security implications of the current federal tax rules for independent workers generally, and in particular, workers earning income through occupations occurring in the On-Demand Economy through estimating the population and earnings of these workers using the U.S. Census Bureau redesigned Survey of Income and Program Participation (SIPP). Ultimately, we found that: • According to SIPP, approximately 7.1 million individuals were Independent Contractors and 3.12 million individuals were On-Demand Workers in 2014. • Using SIPP data, we estimate the collective earnings of Independent Contractors were approximately $204.1 billion dollars 2014, while On-Demand Workers collectively earned approximately $35.97 billion dollars in 2014. • Based on our review of SIPP data and existing measures of misreporting self-employment income, we estimate at least 3.1 million Independent Contractors underreported self-employment income in 2014. This underreporting would result in approximately $4.84 billion in unpaid SE tax, with approximately $3.92 billion constituting non-payment of Social Security contributions. • Using SIPP as well as existing research on tax compliance and information reporting for On-Platform workers and the self-employed, we estimate that as much as $2.51 billion in unpaid SE tax by On-Demand Workers in 2014. This translates to approximately $2.03 billion not paid into Social Security in 2014. • Our estimates of likely additional SE Tax owed by Independent Contractors generally and, more specifically by workers in the On-Demand Economy due to current information reporting rules, directly undermines efforts to fund Social Security and could translate to lower Social Security benefits for these workers upon retirement. While our estimates are illustrative rather than definitive, they are intended to highlight the immediate need for (i) additional research on the tax compliance of these workers; and (ii) legislative action to combat extensive underreporting of SE tax by these populations. The research on measuring these workers is dynamic, but there appears to be consensus that On-Demand Workers are a population that is hard to measure in terms of size, composition and earnings. However, even with conservative estimates on the underpayment of SE tax, there remains a significant—if not multi-billion dollar—probability that millions of the workers we estimated are not paying into Social Security. This a particularly acute problem for women, who tend to have greater dependency on Social Security and lower contributions over the course of their working lives. And this problem will continue to grow along with the digitizing of the cash economy. However, there are limited steps Congress can take to modernize information reporting, update quarterly-estimated payment requirements and to require distribution of tax guidance to help address these issues and further support the solvency of Social Security.

Parental Mortality and Outcomes among Minor and Adult Children

In this paper, I take advantage of newly available data in the Survey of Income and Program Participation (SIPP) to document outcomes among individuals with deceased parents. I focus first on minors and find that about 2 million children in the United States have a biological mother or father who is deceased. This is the first direct estimate of the size of the orphan population in the United States. Relative to children with both parents living, these maternal and paternal orphans have less favorable educational and health outcomes but similar levels of economic well-being. I find the Social Security program provides extensive (but not universal) support to the child survivor population, with participation in the program potentially affected by the earnings of deceased parents prior to death and by awareness of benefit eligibility by adult members in the child’s household. Similar to outcomes for child survivors, I find adult respondents who have deceased parents at the time of the SIPP have less favorable educational and health outcomes. In contrast to child survivors, adults with deceased parents – across a wide range of age groups – are more likely to have low levels of economic well-being. I also find, by examining a past legislative change in Social Security student benefits that would have affected several cohorts in the SIPP, that financial resources available to young adult survivors have effects on educational attainment and effects on income much later in life.

Labor Market Frictions and Moving Costs of the Employed and Unemployed

This paper examines the role of labor market frictions and moving costs in explaining the migration behavior of US workers by employment status. Using data on low-skilled workers from the Survey of Income and Program Participation (SIPP), I estimate a dynamic model of individual labor supply and migration decisions. The model incorporates a reduced-form search model and allows for migration for non-market reasons. My estimates show that moving costs are substantial and that labor market frictions primarily inhibit migration of the employed. I use the model to study migration responses to local labor market shocks and to a moving subsidy. Workers' preferences for non-market amenities, coupled with substantial moving costs and employment frictions, grant market power to incumbent employers. Large moving costs also likely affect employers' recruiting behavior.

Nonparametric Inference on State Dependence in Unemployment

This paper is about measuring state dependence in dynamic discrete outcomes. I develop a nonparametric dynamic potential outcomes (DPO) model and propose an array of parameters and identifying assumptions that can be considered in this model. I show how to construct sharp identified sets under combinations of identifying assumptions by using a flexible linear programming procedure. I apply the analysis to study state dependence in unemployment for working age high school educated men using an extract from the 2008 Survey of Income and Program Participation (SIPP). Using only nonparametric assumptions, I estimate that state dependence accounts for at least 30–40% of the four‐month persistence in unemployment among high school educated men.

The effect of homeownership on the option value of regional migration

This paper estimates a lifecycle model of consumption, housing choice, and migration in the presence of aggregate and regional shocks, using the Survey of Income and Program Participation (SIPP). The model delivers structural estimates of moving costs by ownership status, age, and family size that complement the previous literature. Using the model, I first show that migration elasticities vary substantially between renters and owners, and I estimate the consumption value of having the option to migrate across regions when there are regional shocks. This value is19%of lifetime consumption on average, and it varies substantially with household type.