The Retirement and Disability Research Consortium (RDRC) was established by the U.S. Social Security Administration in 2018. The CRR receives support under the RDRC to conduct and disseminate research along with its partner organizations: Mathematica – Center for Studying Disability Policy, Syracuse University, the Urban Institute, and the Brookings Institution.
Other organizations funded through the RDRC include:
- Michigan Retirement Research Center
- National Bureau of Economic Research
- University of Wisconsin-Madison
Save the date for the annual meeting.
Our current projects:
1. “Will Women Catch Up to Their Fertility Expectations?”
by Anqi Chen and Anek Belbase, Boston College
This project will use data from the 1979 and 1997 cohorts of the National Longitudinal Survey of Youth (NLSY) to estimate completed fertility for women currently of childbearing age. This estimate will help answer a pressing demographic question: are today’s low fertility rates only temporary because women are having children later or will fertility remain low due to structural factors that depress childbearing? SSA has an interest in this topic, because fertility trends have a significant impact on projections for Social Security.
Despite current levels of low fertility, women ages 30-34 today – when first asked about their childbearing expectations in their early 20s – expected to have more than two children, similar to previous cohorts. However, so far, today’s 30-34-year-olds have had fewer kids compared to previous cohorts at the same ages. This project will address whether these women – from the 1997 NLSY cohort – are likely to “catch up” and what factors influence their ability to do so. The analysis will rely on an earlier group of women who have already completed their fertility – the 1979 NLSY cohort (currently ages 50-58).
2. “Do People Work Longer When They Live Longer?”
by C. Eugene Steuerle and Damir Cosic, Urban Institute
This project will use data from multiple publicly available sources, including the Current Population Survey (CPS), American Community Survey (ACS), and US Small-Area Life Expectancy Estimates Project (USALEP), to examine the relationship between life expectancy and retirement behavior. Understanding this relationship is of interest to SSA because it would inform and improve the Social Security Trustees’ long-term projections of labor force participation.
While researchers generally accept that living longer induces people to work longer, measuring the relationship between life expectancy and retirement age is difficult. Life expectancy and labor force participation at older ages have been increasing together since the 1990s, but that was not the case in the preceding decades when the retirement age was falling despite increasing life expectancy. To isolate the effect of life expectancy, we will use both temporal and spatial variation in life expectancy and labor force participation at older ages.
3. “What Are the Consequences of Current Benefit Adjustments for Early and Delayed Claiming?”
by Andrew Biggs, American Enterprise Institute and Alicia H. Munnell and Anqi Chen, Boston College
This project will use the Health and Retirement Study and recent SSA estimates on mortality by Average Indexed Monthly Earnings (AIME) quartile to determine whether the actuarial reduction and delayed retirement credit are still actuarially fair overall and across income groups, and then estimate the consequences of any deviations. SSA has an interest in understanding these deviations, since they could cost the program money and reduce progressivity by shifting lifetime benefits to high-income workers who live longer and claim later.
Deviations are likely to exist because the actuarial reduction for claiming before the full retirement age and the delayed retirement credit for claiming afterwards are based on assumptions that are decades old. During the intervening period, conditions have changed: interest rates are lower, lives are generally longer (recent years excepted), and inequality in mortality is greater. If the goal of these programmatic features is to maintain the expected present value of benefits regardless of claim age, do they? And, if not, what are the consequences for program costs and progressivity?
4. “Disability Insurance for State and Local Employees: A Lay of the Land”
by Anek Belbase and Laura D. Quinby, Boston College
This project will create a database of key facts about the 100 largest state and local disability insurance programs – covering 85 percent of state and local workers – and document recent trends in disability benefits. SSA has an interest in monitoring whether government workers who spend their careers outside of Social Security stand to receive adequate disability benefits and in creating new data that researchers can use to study how disability award rates respond to different insurance systems.
While state and local pensions have received a great deal of attention in recent years, it has been decades since researchers have examined the disability insurance offered by state and local government employers. Even basic facts, such as the eligibility rules, benefit formula, and take-up rate do not exist in a publicly available, national database. This project will shed light on three questions: 1) do career workers in systems not covered by Social Security receive comparable insurance to Social Security disability insurance (SSDI)?; 2) among covered workers, what disability benefits are “typical” and what is the range of insurance arrangements?; and 3) to what extent have state and local disability awards mirrored trends in SSDI awards?
5. “Do State and Local Government Employees Save Outside of Their Pensions When They Need To?”
by Laura D. Quinby and Geoffrey T. Sanzenbacher, Boston College
This project will link the Survey of Income and Program Participation (SIPP) to the Public Plans Database (PPD) to assess whether public employees save for retirement outside of their defined benefit (DB) pensions and, if so, whether their saving rate correlates with the DB plan’s generosity and financial stability. SSA has an interest in this project because the results will reveal whether public employees who are not covered by Social Security earn sufficient employer benefits, and whether covered workers would be more reliant on Social Security in the event of a pension cut.
A quarter of state and local employees are not covered by Social Security, and their employer pensions are becoming less generous as governments grapple with rising costs. A few trust funds could be exhausted within the next decade, risking a default on promised benefits (Quinby, Aubry, and Munnell 2018). Consequently, state and local workers who do not save outside of their DB plans – for example through an employer-sponsored 457 plan – could end up vulnerable to retirement insecurity. If workers are well informed about their pensions, then those with less generous benefits, those whose pensions are in financial difficulty, and those without Social Security coverage should be more likely to accrue private retirement savings.
6. “Understanding the Local-Level Predictors of Disability Program Applications, Awards, and Beneficiary Work Activity”
by Jody Schimmel Hyde, Mathematica Policy Research, Jonathan Schwabish, Urban Institute, and Paul O’Leary, U.S. Social Security Administration
This project will document the local-area predictors of flows onto the DI and SSI programs and flows out of those programs due to work, using combined data from SSA’s Disability Analysis File (DAF) and other national sources. The results of this study will inform SSA’s understanding of trends in disability and the drivers of disability benefit application, benefit receipt prevalence, and beneficiary employment milestones. The project will also produce a public use file of local-area data to facilitate future research and policy analysis.
Numerous studies have documented that local-level factors contribute to the share of working-age adults reporting a disability, the employment rate of workers with disabilities, and disability benefit receipt (e.g., Rupp 2012; Nichols, Schmidt, and Sevak 2017; Sevak et al. 2018; Gettens et al. 2018). Yet, research to date has not comprehensively assessed how these factors predict flows into and out of DI and SSI.
7. “Financial Security at Older Ages”
by Barbara A. Butrica and Stipica Mudrazija, Urban Institute
This proposal uses data from a major credit bureau to examine the financial health and indebtedness of older adults. SSA has an interest in this topic because as Americans have become increasingly indebted over time, understanding the factors influencing indebtedness can help policymakers design policies that discourage debt, thus enhancing private retirement savings so that retirees become less dependent on Social Security benefits.
The proposed project will examine financial security at older ages, including how financial security changes as people approach retirement, the factors associated with changes in financial health, how long it takes for older adults to recover from financial distress, the factors associated with recovering from declines in financial health, whether recovery time differs depending on the source of debt, and how patterns of financial security differ between older and younger adults.
8. “Intended Bequests and the Role of Housing Equity as a Source of Income in Older Age”
by Gary V. Engelhardt, Syracuse University
Along with wealth from Social Security and employer-provided retirement plans, housing equity is one of the largest assets in the portfolios of older Americans. Future retirees could use that equity to supplement their retirement income. However, the willingness to tap housing equity may be limited to the extent that older individuals have strong bequest motives, especially for housing. SSA has an interest in knowing the extent to which housing equity can supplement existing resources as policymakers consider benefit cuts as well as tax increases to close Social Security’s long-term funding gap.
This project uses data from the 1998-2018 waves of the Health and Retirement Study to examine the role of intended bequests of housing and tenure transition decisions, following cohorts of older Americans into old age and death. It will estimate the flow of annual intergenerational and inter-vivos housing transfers from older to younger generations, examine changes in bequest intentions across birth cohorts, and provide new estimates of the stock of housing wealth that might be available to supplement retirement income if bequest intentions are actualized.
9. “How Much Taxes Will Retirees Owe on Their Retirement Income?”
by Anqi Chen and Alicia H. Munnell, Boston College
This project will use the Health and Retirement Study (HRS) linked to restricted state-level data, the detailed Master Earnings File, and TAXSIM to estimate the tax burden households will likely face once they retire. SSA has an interest in helping households understand their retirement resources – net of taxes – to enable them to make well-informed decisions about how much to save, when to retire, and how to draw down their assets.
While replacement rate studies implicitly incorporate taxes, analyses of absolute income and wealth in retirement often do not consider taxes, despite the fact that the typical household will be taxed on retirement income. In fact, only one study has estimated the size of the tax burden in retirement, and it found that about half of families will owe federal tax on their Social Security benefits. This estimate does not include other taxes that older households may face – such as taxes on pension income and traditional 401(k)/IRA distributions. This project will estimate the federal and state income tax burden that households will face in retirement and how it varies across the income distribution.
10. “Employment Outcomes for DI Applicants Who Use Opioids”
by April Yanyuan Wu and Denise Hoffman, Mathematica Policy Research and Paul O’Leary, U.S. Social Security Administration
This project will use SSA administrative data to examine the relationship between opioid use and employment outcomes among DI applicants. The study will provide SSA with information about the work capacity and post-adjudication economic well-being of DI applicants who use opioids, a notable share of the pool of DI applicants. The results will indicate the extent to which this population would be receptive to services that could facilitate return to work after entry, and the extent to which services delivered to similar workers before DI entry would keep them in the labor force instead.
Although recent studies suggest that opioid use can have negative consequences for economic outcomes (Krueger 2017; Franklin et al. 2014; Savych, Neumark, and Lea 2018), little is known about this relationship among DI applicants. This study will build on the results of an ongoing RDRC project that uses a supervised machine learning method to classify medication information and identify opioid use among DI applicants.
11. “How Do Reductions in Early Retirement Benefits Affect Retirement Behavior?”
by C. Eugene Steuerle and Damir Cosic, Urban Institute
This project will use Current Population Survey (CPS) and Health and Retirement Study (HRS) data to examine how increases in Social Security’s early-retirement reductions and full retirement age from the 1983 reforms affected the likelihood to retire. Understanding how older workers respond to benefit reductions is of interest to SSA for both projecting future labor force participation and evaluating policy proposals that affect its benefits.
Economic theory predicts that benefit reductions increase work incentives at older ages and reduce retirement rates, but data limitations and confounding factors complicate tests of this prediction. Indeed, estimates in the literature vary greatly. This project aims to improve on previous estimates by using the most recent available data and applying several methodological advances. We will apply the difference-in-difference framework while addressing the potential problems it can create, such as correlation among members of the same group and correlation between observations over time. Our preliminary findings suggest that early retirement benefit reductions reduce men’s likelihood of retiring at age 62 but not at ages 63 to 65.
12. “Comparative Regression Discontinuity and Regression Discontinuity as Alternatives to Randomized Control Trials: Evidence from BOND”
by Duncan Chaplin and Denise Hoffman, Mathematica Policy Research and John Jones, U.S. Social Security Administration
This project will use data from the evaluation of the Benefit Offset National Demonstration (BOND) to assess the efficacy of comparative regression discontinuity (CRD) and regression discontinuity (RD) relative to each other and to randomized controlled trials (RCTs). RD is known as a relatively rigorous non-experimental method but produces imprecise results that apply to small populations. CRD addresses these issues. The findings will support interpreting CRD and RD studies on DI and related programs. They might also help SSA decide whether to consider these methods for testing impacts of proposed rules, using criteria such as duration of benefit receipt and beneficiary age to define those eligible and ineligible for the new rules. The CRD and RD methods are potentially attractive because they can avoid many of the challenges and costs of an RCT, but only if their validity is high.
We will estimate CRD and RD models using simulated assignment to the BOND treatment group based on cut-points on duration of benefit receipt at the start of the BOND program. We will compare those estimates to each other and to RCT estimates for the treated group, for CRD, and to RCT estimates for those near to the cut-point, for RD.
13. “What Is the Extent of Opioid Use among Disability Insurance Applicants?”
by April Yanyuan Wu and Denise Hoffman, Mathematica Policy Research and Paul O’Leary, U.S. Social Security Administration
This study will use data from SSA’s Structured Data Repository (SDR) to document trends in opioid use among applicants to disability insurance (DI) and the extent to which opioid use is predictive of initial award, an award within five years, and mortality. The findings will inform SSA’s projections about future program entry based on aggregate trends in opioid use. The rise in opioid use nationwide – coupled with the numerous DI applicants who have conditions associated with opioid use, such as musculoskeletal problems – suggests that opioid use may be common and increasing among DI applicants. Beneficiaries cannot qualify for DI on the basis of drug addiction, but opioid use may exacerbate the effects of other conditions that meet DI qualifications. This study will address a major data issue that limits what is known about opioid use among DI applicants. Applicants are required to report their medications, but medications are recorded as a combination of coded and open-ended text fields. This study will capitalize on a previously developed supervised machine-learning algorithm to identify opioids recorded in freeform text and combine that information with opioids identified in populated medication codes.
14. “How Can Behavioral Insights Reduce Overpayments from Disability Insurance?”
by Denise Hoffman and Jonah Deutsch, Mathematica Policy Research
This project will use insights from behavioral science to diagnose process problems and suggest evidence-based interventions to reduce disability insurance (DI) overpayments. The project will inform SSA’s efforts to meet its strategic targets and maintain the public trust. Overpayments are prevalent among DI beneficiaries engaged in substantial gainful activity (SGA) and are undesirable for both program administrators and beneficiaries. Among those at risk of a work-related overpayment in 2010-2012, 71 percent were overpaid (Hoffman et al. 2018). Anecdotal evidence suggests that overpayments can be traumatic for beneficiaries, who have to pay them back, and may discourage work (Kregel 2018). They can also compromise program integrity, create administrative challenges for SSA, and are not always recovered. This study will help SSA design processes that improve beneficiary compliance with earnings reporting requirements, which is one of the root causes of overpayments. First, the study team will conduct a process analysis to identify shortcomings in the current system that lead to this failure to report earnings. The team will then draw on behavioral science insights to identify promising options to improve communications.
15. “Does Employer Concentration Affect Labor-Force Participation?”
by Anqi Chen, Laura D. Quinby, and Gal Wettstein, Boston College
Labor-force participation (LFP) of prime-age workers – an important factor in the actuarial projections of the OASI program – has declined secularly since 2000. Simultaneously, an accumulation of evidence suggests that the concentration of employers in local labor markets has increased, giving firms greater bargaining power in employment negotiations and potentially driving down LFP. The aim of this project is to examine whether markets with higher employer concentration have substantially lower LFP, and whether the relationship is stronger for employees with less bargaining power, such as the less-educated and the non-unionized.
Although a large literature examines the factors affecting prime-age LFP, the recent decline is not fully understood. Simultaneously, a parallel line of research suggests that employer concentration slows real wage growth, but the effect of employer concentration on LFP itself has been understudied. By linking these two phenomena, this project will promote a better understanding of the drivers of prime-age LFP. To analyze the relationship between employer concentration in local labor markets and prime-age LFP, this project will combine data from the Longitudinal Business Database, the Local Area Employment Database, and the American Community Survey.
16. “Examining Mortality and Receipt of Benefits Administered by SSA as Reasons for Desistance from Homelessness among Older Adults”
by Matthew S. Rutledge, Boston College, Dennis Culhane, University of Pennsylvania, and Thomas Byrne, Boston University
The study links data from the emergency shelter systems in several large American cities with SSA data to investigate the pattern of desistance from homelessness among those in the age cohort who have been disproportionately impacted by homelessness for over 20 years and who are now approaching retirement age. The specific research questions to be addressed by the study are as follows: 1) To what extent does mortality contribute to the observed pattern of desistance from homelessness among older adults?; 2) How does premature death impact the ability of persons with a history of homelessness to receive Social Security retirement benefits? To what extent do individuals with earnings histories that would render them eligible for Social Security retirement benefits die prior to reaching the statutory age for claiming these benefits?; and 3) To what extent do older homeless adults receive Social Security retirement benefits, SSDI and SSI? Does receipt of these benefits help facilitate exits from homelessness?