Austin Nichols

Tracking the Household Income of SSDI and SSI Applicants

Using panel data from the Survey of Income and Program Participation linked to Social Security Administration disability determination records we trace the pattern of household income and the sources of that income from 38 months prior to 39 months following application for Social Security Disability Insurance (SSDI) and Supplemental Security Insurance (SSI). We find that the average applicants labor earnings declines dramatically beginning six month before application but the average applicants household income drops much less dramatically both in the months just before or just after application and over the next three years, and does so even for those denied benefits. However, we also found substantial heterogeneity in household income outcomes in both the SSDI and SSI applicant population. Our quantile regressions suggest that higher income households experience greater percentage declines in their post-application income. Such results are consistent with the lower replacement rate for higher earners established in the SSDI program and the low absolute level of protection provided to all SSI applicants regardless of income prior to application.

Expansion of Invasive Cardiac Services in the United States

Background— The number of hospitals offering invasive cardiac services (diagnostic angiography, percutaneous coronary intervention, and coronary artery bypass grafting) has expanded, yet national patterns of service diffusion and their effect on geographic access to care are unknown. Methods and Results— This is a retrospective cohort study of all hospitals in fee-for-service Medicare, 1996 to 2008. Logistic regression identified the relationship between cardiac service adoption and the proportion of neighboring hospitals within 40 miles already offering the service. From 1996 to 2008, 397 hospitals began offering diagnostic angiography, 387 percutaneous coronary intervention, and 298 coronary artery bypass grafting (increasing the proportion with services by 3%, 11%, and 4%, respectively). This capacity increase led to little new geographic access to care; the population increase in geographic access to diagnostic angiography was 1 percentage point; percutaneous coronary intervention 5 percentage points, and coronary artery bypass grafting 4 percentage points. Controlling for hospital and market characteristics, a 10 percentage point increase in the proportion of nearby hospitals already offering the service increased the odds by 10% that a hospital would add diagnostic angiography (odds ratio, 1.102; 95% confidence interval, 1.018–1.193), increased the odds by 79% that it would add percutaneous coronary intervention (odds ratio, 1.794; 95% confidence interval, 1.288–2.498), and had no significant effect on adding coronary artery bypass grafting (odds ratio, 0.929; 95% confidence interval, 0.608–1.420). Conclusions— Hospitals are most likely to introduce new invasive cardiac services when neighboring hospitals already offer such services. Increases in the number of hospitals offering invasive cardiac services have not led to corresponding increases in geographic access.

The Impact of Temporary Assistance Programs on Disability Rolls and Re-Employment

Workers who lose their job draw from temporary assistance programs in order to buffer their income losses. They are also more likely to apply for Disability Insurance (DI) and Supplemental Security Income (SSI). Whether participating in temporary assistance programs influences the application decision for DI and SSI, however, is largely unknown. We address this question using panels from the Survey of Income and Program Participation (SIPP) matched to administrative records on DI and SSI applications. We distinguish between four temporary insurance programs: Temporary Assistance for Needy Families (TANF), Supplemental Nutrition Assistance Program (SNAP), Unemployment Insurance (UI), and Temporary Disability Insurance programs (TDI). For each of these programs, we construct instruments based on state policies in order to address endogeneity concerns. Our results indicate that workers select into temporary assistance and disability programs by income and health status. When controlling for selection bias, we find evidence that increased access to UI benefits reduces applications for DI, while increased access to SNAP benefits increases applications for SSI. These results suggests that (i) applications for DI and SSI are sensitive to participation in temporary assistance programs; (ii) the strength of the net effect depends on the overlap between target populations; and (iii) the direction of the net effect depends on benefit levels or on institutional and population characteristics.

Tax-Transfer Policy and Labor Market Outcomes

The Earned Income Tax Credit provides nearly

Rural Hospital Ownership: Medical Service Provision, Market Mix, and Spillover Effects

40 billion to low-income families with children. A potential unintended consequence of the credit is lower pretax wages, in which case only part of the subsidy would accrue to workers. We examine the extent to which EITC expansions lower the pretax wages of working parents. Our findings are inconclusive. The gross hourly wages of less-skilled single women are found not to vary by the number of children, as does the EITC. In addition, the wages of black single mothers track the minimum wage for nearly the entire time period.

Income Risk in 30 Countries

OBJECTIVE To test whether nonprofit, for-profit, or government hospital ownership affects medical service provision in rural hospital markets, either directly or through the spillover effects of ownership mix. DATA SOURCES/STUDY SETTING Data are from the American Hospital Association, U.S. Census, CMS Healthcare Cost Report Information System and Prospective Payment System Minimum Data File, and primary data collection for geographic coordinates. The sample includes all nonfederal, general medical, and surgical hospitals located outside of metropolitan statistical areas and within the continental United States from 1988 to 2005. STUDY DESIGN We estimate multivariate regression models to examine the effects of (1) hospital ownership and (2) hospital ownership mix within rural hospital markets on profitable versus unprofitable medical service offerings. PRINCIPAL FINDINGS Rural nonprofit hospitals are more likely than for-profit hospitals to offer unprofitable services, many of which are underprovided services. Nonprofits respond less than for-profits to changes in service profitability. Nonprofits with more for-profit competitors offer more profitable services and fewer unprofitable services than those with fewer for-profit competitors. CONCLUSIONS Rural hospital ownership affects medical service provision at the hospital and market levels. Nonprofit hospital regulation should reflect both the direct and spillover effects of ownership.

The Impact of Changing Earnings Volatility on Retirement Wealth

We present a measure of income risk that decomposes income dynamics into long-run inequality, volatility (inter-temporal variability around individual-specific growth rates), and mobility risk (variation in individual-specific growth rates). We measure these income risk components in panel data from 30 rich democracies. We use this comprehensive collection of panel data to analyze long-terms trends in income dynamics for four countries (Canada, Germany, Great Britain, and the United States), and cross-national patterns of income dynamics for an additional 26 countries. We find that tax and transfer systems lower income risk, but less so in the United States than in other comparable countries. We find that higher incomes tend to grow faster and to be more volatile than lower incomes. We find that the United States is exceptional in its level of, and increase in, each type of income risk. Various other measures of mobility are positively correlated with mobility risk.

Disability Benefits as Social Insurance: Tradeoffs between Screening Stringency and Benefit Generosity in Optimal Program Design

Over the last several decades, the volatility of family income has increased markedly, and own earnings volatility has remained relatively flat. Volatility may affect retirement wealth, depending on whether volatility affects accrued pension contributions or withdrawals or earnings credited toward future Social Security benefits. This project assesses the effect of the volatility of individual and family earnings on asset accumulation and projected retirement wealth using survey data matched to administrative earnings records.

Using Preferred Applicant Random Assignment (PARA) to Reduce Randomization Bias in Randomized Trials of Discretionary Programs

The Social Security Disability Insurance (SSDI) system is designed to provide income security to workers in the event that health problems prevent them from working. In order to qualify for benefits, applicants must pass a medical screening that is intended to verify that the individual is truly incapable of work. Past research has shown, however, that the screening procedures used do not function without error. If screening were error-free, it has can be demonstrated that it is socially optimal to distinguish the disabled non-worker from the non-disabled, providing benefits to the disabled. In this paper we first demonstrate that if the errors in the medical screening are too large, it will not be optimal to distinguish the disabled from the non-disabled. Then, we use data on the actual quality of screening to determine first, if segmenting the non-working population is desirable, and second whether the current SSDI system relies too heavily on screening than is justified. Our preliminary conclusion is that while screening is good enough to justify some distinction in benefits, it may not be good enough to justify the size of the benefit offered.

Economic Conditions and SSI Applications

Randomization bias occurs when the random assignment used to estimate program effects influences the types of individuals that participate in a program. This paper focuses on a form of randomization bias called “applicant inclusion bias,†which can occur in evaluations of discretionary programs that normally choose which of the eligible applicants to serve. If this nonrandom selection process is replaced by a process that randomly assigns eligible applicants to receive the intervention or not, the types of individuals served by the program—and thus its average impact on program participants—could be affected. To estimate the impact of discretionary programs for the individuals that they normally serve, we propose an experimental design called Preferred Applicant Random Assignment (PARA). Prior to random assignment, program staff would identify their “preferred applicants,†those that they would have chosen to serve. All eligible applicants are randomly assigned, but the probability of assignment to the program is set higher for preferred applicants than for the remaining applicants. This paper demonstrates the feasibility of the method, the cost in terms of increased sample size requirements, and the benefit in terms of improved generalizability to the population normally served by the program.