The Poverty Reduction of Social Security and Means-Tested Transfers

This article is the fourth in a series to celebrate the 70th anniversary of the ILR Review. The series features articles that analyze the state of research and future directions for important themes this journal has featured over many years of publication. Starting with Survey of Income and Program Participation (SIPP) data from 2008 to 2013, the authors link administrative data from Social Security and five large means-tested transfers—Supplemental Security Income (SSI), Supplemental Nutrition Assistance Program (SNAP), public assistance (PA), the Earned Income Tax Credit (EITC), and housing assistance—to minimize errors within the SIPP data. Social Security cuts the poverty rate by a third—more than twice the combined effect of the five means-tested transfers. Among means-tested transfers, the EITC and SNAP have the largest effects. All programs except for the EITC sharply reduce deep poverty. The relative importance of these programs differs by family subgroup. SSI, PA, and housing assistance have the highest share of benefits going to the pre-transfer poor, whereas the EITC has the lowest. Finally, the SIPP survey data alone provide fairly accurate estimates for the overall population at the poverty line, though they understate the effects of Social Security, SNAP, and PA. Differences in effects are striking, however, at other income cutoffs and for specific family types.

Disability Saliency and Discrimination in Hiring

Theory suggests that disability discrimination protections may adversely affect the hiring of individuals with disabilities by making them more expensive. Using SIPP data, we explore how the ADA Amendments Act (ADAAA), which expanded disability discrimination protections, affected the relative hiring rate of individuals with disabilities. We employ new categorizations of disability type: salient physical conditions, non-salient physical conditions, mental retardation and developmental disability, and other mental conditions. We find that the ADAAA had no effect other than increasing hiring for those with non-salient physical conditions. These results suggest that condition saliency may mediate the effects of discrimination protections on hiring.

Some Evidence on the Importance of Sticky Wages

We present evidence on the frequency of nominal wage adjustment using SIPP data adjusted for measurement error. The SIPP is a representative sample of the US population. Our main results are: (i) The average quarterly probability of a nominal wage change is between 21.1 and 26.6 percent, depending on the assumptions used. (ii) Wage changes are much more likely when workers change jobs. (iii) The frequency of wage adjustment does not display significant seasonal patterns. (iv) The hazard of a nominal wage change first increases and then decreases, with a peak at 12 months. (JEL E24, E32, E52, J31)

Medicaid and Wealth: A Re-Examination

Do public insurance programs crowd out private savings? I examine the relationship between Medicaid and wealth and make a contribution to the literature on this issue in two primary ways. First, I apply the instrumental-variables approach developed by Gruber and Yelowitz (1999) to a different dataset, the National Longitudinal Survey of Youth, 1979 (NLSY79), while at the same time examining an alternative instrument. The results turn out to differ depending on the instrument and, for one of the instruments, to be sensitive to assumptions needed to identify Medicaid’s effects. Second, I make use of the SIPP data employed by Gruber and Yelowitz themselves, and examine the sensitivity of their conclusions to omitted factors that may be related to both Medicaid eligibility and to wealth accumulation. While more robust than the results using the NLSY79, the SIPP estimates are found to depend both on the sample used and on certain specification restrictions. Taken together, the results suggest caution in making inferences about the impact of Medicaid on wealth.

Immigrant–native differences in employment-based retirement plan participation

This paper examines differences between immigrant and native employees in retirement plan participation using SIPP data. We find that the participation rate among natives is 60 percent, while the native-immigrant participation gap ranges from 10.9 percentage points for naturalized citizens to 35.4 percentage points for non-permanent residents. Controlling for demographic and job characteristics can explain up to half of the gap. Decomposing the overall immigrant-native difference into differences in employer offers, plan eligibility, and plan take-up shows that the likelihood of working for an employer that offers a plan is the primary driver of the overall gap.