%0 Report %D 2023 %T Using Administrative Data to Validate HRS Survey Responses on Application for DI and SSI Disability Benefits %A John Bound %A Charles Brown %A Fang, Chichun %K administrative data %K disability insurance %K Social Security %K Supplemental Security Income %X In this paper, we use administrative data from the Social Security Administration to validate survey responses for the Health and Retirement Study (HRS) regarding the application for disability benefits from Social Security Disability Insurance (DI) or Supplemental Security Income (SSI), focusing on applications that occurred after individuals entered the HRS. In our samples, amongst those that the administrative data identifies as having applied for DI or SSI, over 40% either do not report having applied or inaccurately identify whether or not the application was successful. We find some evidence that the less well educated, those with cognitive limitations, and those experiencing a health limitation on their capacity for work are more likely to misreport applications. We also explore the effect that reporting errors have on parameter estimates in a simple model of the application for DI benefits. Parameter estimates are qualitatively similar regardless of whether we use survey or administrative data to identify the application for DI benefits in our model. %I Michigan Retirement and Disability Research Center, University of Michigan %C Ann Arbor, MI %G eng %U https://mrdrc.isr.umich.edu/pubs/using-administrative-data-to-validate-hrs-survey-responses-on-application-for-di-and-ssi-disability-benefits/ %0 Report %D 2013 %T Estimates of the Potential Insurance Value of Disability Insurance for Individuals with Mental Health Impairments %A John Bound %A Caswell, Kyle J. %A Timothy A Waidmann %K Health Conditions and Status %K Public Policy %K Social Security %X Since the mid-1980s there has been dramatic growth in the number and fraction of DI and SSI beneficiaries with mental illness. With longer life expectancies and younger ages of disability onset than beneficiaries with physical impairments, their growth exerts added fiscal pressure on the programs. While not specifically focused on mental illness, fears of an increase in the duration (and thus prevalence) of disability claims that may result from this demographic shift have generated calls to tighten eligibility rules again. Using data from the Health and Retirement Study linked to SSA administrative records, we created statistically matched control groups of non-beneficiaries with severe mental illness. We then estimated the earnings, income, and health insurance coverage among rejected DI/SSI applicants with mental illness who have characteristics comparable to persons awarded benefits on the basis of mental impairments. We found that even after controlling for health and demographic characteristics, DI beneficiaries were substantially worse off than rejected applicants in terms of wealth and income. While these rejected applicants with mental illness were worse off than those with physical impairments, our findings suggests that the programs successfully select applicants with the greatest income needs,and that retrenchment could result in significant hardship. %I Ann Arbor, MI, University of Michigan Retirement Research Center %G eng %4 Social Security Disability Insurance/Supplemental Security Income/Mental illness/Public Policy/Disabilities %$ 69286 %0 Report %D 2013 %T Social Security Benefit Claiming and Medicare Utilization %A John Bound %A Helen G Levy %A Lauren Hersch Nicholas %K Medicare/Medicaid/Health Insurance %K Retirement Planning and Satisfaction %K Social Security %X Are early Social Security claimers too sick to work? We linked Health and Retirement Study data to Medicare claims to study health care utilization at ages 65 and 70. We find that Social Security Disability Insurance recipients use more health care on average than those who never received DI. At age 65, Medicare spending on SSDI recipients was 4,440 less than spending on retirees who claimed Social Security benefits prior to Full Retirement Age (FRA) and 4,727 less than those claiming at FRA. Differences in Medicare spending persist at all points of the spending distribution. They are robust to a variety of methodological approaches including general linear models, quantile regression, and reweighting, and in specifications limiting comparisons to beneficiaries claiming benefits at initial EEA. Our results suggest that poor health may contribute to EEA claiming decisions, though this group is considerably healthier than those who were too disabled to work and qualified for DI benefits. %I Ann Arbor, MI, University of Michigan Retirement Research Center %G eng %U http://www.mrrc.isr.umich.edu/publications/papers/pdf/wp281.pdf %4 social security/claiming behavior/claiming behavior/Medicare/Social Security Disability Insurance/early claiming %$ 999999 %0 Report %D 2010 %T The Social Security Early Retirement Benefit as Safety Net %A John Bound %A Timothy A Waidmann %A Michigan Retirement Research Center %K Demographics %K Disabilities %K Retirement Planning and Satisfaction %K Social Security %X In this paper we used the Health and Retirement Study to examine the health and economic status of those who collect Social Security retirement benefits prior to the full retirement age. We used a propensity score reweighting method to estimate the fraction of early retirees who uses early retirement benefits as a safety net against deteriorating health and who might be induced to apply for disability benefits (SSDI) or retire without income replacement if the generosity or availability of early retirement benefits were reduced. We find that while the majority of early retirees would likely not qualify for disability benefits, approximately one in five have health characteristics similar to SSDI beneficiaries, and thus might not be able to replace losses in benefit income with labor income. %I The University of Michigan, Michigan Retirement Research Center %G eng %4 socioeconomic Status/retirement benefits/disability benefits/early Retirement/earnings and Benefits File %$ 24300