Who Needs Medicare? Health Insurance Sources for Disability Insurance Recipients Before and after Medicare Eligibility

2014 ◽  
Author(s):  
Kathryn Anne Edwards
2020 ◽  
Vol 53 (3) ◽  
pp. 341-352 ◽  
Author(s):  
Kara Contreary ◽  
Todd Honeycutt

BACKGROUND: The U.S. government has implemented several programs to reduce federal expenditures on Social Security Disability Insurance (DI) and help beneficiaries return to work, but the limited success of these efforts has raised interest in approaches that help workers with disabilities remain in the workforce. OBJECTIVE: This paper provides information on individuals at risk of applying for DI benefits to help build the evidence base for policies that provide workers with disabilities support to eliminate the need to apply for and receive DI benefits. METHODS: Using three panels of the Survey of Income and Program Participation matched to SSA administrative data, we describe the employment characteristics of seven groups at risk of applying for DI benefits before and after application, as well as the outcomes of their DI applications. RESULTS: New private disability insurance recipients were more likely to apply for and receive DI than members of other at-risk groups. However, individuals with high healthcare expenditures made up the largest proportion of successful applicants across the at-risk groups considered here. CONCLUSION: While it seems plausible that individuals within an at-risk group who are likely to apply for DI benefits can be identified and provided supports to help them maintain employment, focusing on a specific group to promote employment over DI benefits may have a limited effect on the DI program because applicants come from multiple groups.


Sci ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 25
Author(s):  
Jesse Patrick ◽  
Philip Q. Yang

The Affordable Care Act (ACA) is at the crossroads. It is important to evaluate the effectiveness of the ACA in order to make rational decisions about the ongoing healthcare reform, but existing research into its effect on health insurance status in the United States is insufficient and descriptive. Using data from the National Health Interview Surveys from 2009 to 2015, this study examines changes in health insurance status and its determinants before the ACA in 2009, during its partial implementation in 2010–2013, and after its full implementation in 2014 and 2015. The results of trend analysis indicate a significant increase in national health insurance rate from 82.2% in 2009 to 89.4% in 2015. Logistic regression analyses confirm the similar impact of age, gender, race, marital status, nativity, citizenship, education, and poverty on health insurance status before and after the ACA. Despite similar effects across years, controlling for other variables, youth aged 26 or below, the foreign-born, Asians, and other races had a greater probability of gaining health insurance after the ACA than before the ACA; however, the odds of obtaining health insurance for Hispanics and the impoverished rose slightly during the partial implementation of the ACA, but somewhat declined after the full implementation of the ACA starting in 2014. These findings should be taken into account by the U.S. Government in deciding the fate of the ACA.


2005 ◽  
Vol 8 (1) ◽  
Author(s):  
John H Cawley ◽  
Mathis Schroeder ◽  
Kosali Ilayperu Simon

There is tremendous interest in understanding the effects of welfare reform enacted by the Personal Responsibility and Work Opportunity Reconciliation Act of 1996. Our interest lies in one possible consequence of welfare reform: the loss of health insurance.This paper advances the literature by utilizing the 1992-1996 panels of the Survey of Income and Program Participation, matching type of insurance coverage to the presence of waivers from AFDC or TANF implementation in each state in specific months. We utilize a difference in differences method. Specifically, we estimate the difference before and after welfare reform in the insurance coverage of women and children who were likely to be eligible for welfare compared to those who were likely to be ineligible for welfare.We find that AFDC waivers prior to 1996 and the implementation of TANF after 1996 raised the probability that welfare-eligible women lack health insurance coverage. Specifically, TANF implementation is associated with a 7.8 percent increase in the probability that a welfare-eligible woman was uninsured. Welfare reform had less of an impact on the health insurance coverage of children. We find no evidence that AFDC waivers increased the probability that welfare-eligible children were uninsured. However, TANF implementation was associated with a 2.8 percent increase in the probability that a welfare-eligible child lacked health insurance.


2014 ◽  
Vol 104 (5) ◽  
pp. 336-341 ◽  
Author(s):  
Michelle Stegman Bailey ◽  
Robert R. Weathers

We use data from the Accelerated Benefits demonstration to estimate the impacts of providing newly entitled disability insurance (DI) beneficiaries with health insurance and additional services during the DI program's 24-month Medicare waiting period. While health insurance alone did not increase employment, the additional employment services appeared to have positive short-term impacts on labor market activity. We find a statistically significant increase in employment and earnings in the second calendar year after random assignment; although these findings disappear in the third calendar year. Our results may have implications for disability reform proposals and provisions within the Affordable Care Act.


2015 ◽  
Vol 105 (5) ◽  
pp. 137-141 ◽  
Author(s):  
Andreas Ravndal Kostøl ◽  
Magne Mogstad

Two key questions in thinking about the size and growth of the disability insurance program are to what extent it discourages work, and how valuable the insurance is to individuals and families. These questions motivate our paper. We begin by describing the earnings, disposable income, and consumption of awarded and rejected DI applicants, before and after the disability onset and the allowance decision. Next, we discuss how these descriptive results can be interpreted through the lens of alternative empirical approaches. Our analysis uses a Norwegian population panel data set with detailed information about every individual and household.


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