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 and Disability Research Center
- NBER Retirement and Disability Research Center
- University of Wisconsin-Madison Center for Financial Security
Learn more about the Consortium’s funding opportunities.
The Annual Meeting was held virtually on August 5-6, 2021.
1. “How Will COVID Affect the Completed Fertility Rate?”
by Anqi Chen, Nilufer Gok, and Alicia H. Munnell, Boston College
Fertility rates will likely decline in the wake of the COVID pandemic, much like they did after prior recessions and crises. If COVID-related declines in fertility are temporary and completed fertility remains unchanged, the impact will be minimal for pay-as-you-go programs such as Social Security. However, a more permanent decline – on top of today’s already low levels of fertility – would have important implications for Social Security.
To identify whether any decline is temporary, the project will use a two-pronged approach. First, it will examine declines in births by age in 2020 using an event study with heterogeneous treatment effects, relying on data from the National Vital Statistics System (NVSS), to isolate COVID’s impact. To the extent that the dips occur among women in their mid-30s or older, completed fertility may be lower. Second, the project will examine changes in fertility expectations. For younger women, temporal dips may not be a concern since they have time to catch up. Instead, the impact on these women is the extent to which their expectations themselves change. This project will examine changes in expectations among women in their 20s, pre- and post-pandemic. For context, all results will be compared to the Great Recession.
2. “How Does COVID-Induced Early Retirement Compare to the Great Recession?”
by Anqi Chen, Alicia H. Munnell, and Siyan Lu, Boston College
COVID has been uniquely challenging for older workers. They have not only faced job loss from a weakened economy but have also been particularly vulnerable to the virus itself. During this difficult period, the ability to claim Social Security benefits early provides a potentially important safety net. But claiming early comes at a significant loss in monthly benefits, and – due to relatively large actuarial adjustments – lower lifetime benefits. If early claiming has occurred due to COVID, who are the early claimers? How much has early claiming cost them? And do they differ from early claimers in the Great Recession? Social Security has an interest in identifying early claimers because, to the extent these losses fall on disadvantaged groups, they undermine the system’s progressivity.
The project will first use the Health and Retirement Study to estimate a hazard model to identify who claims early when the economy weakens. The second step involves calculating lifetime benefits foregone and how they differ by income and race/ethnicity. The final step compares claiming and losses during COVID with the Great Recession.
3. “What Are the County-Level Drivers of DI and Early OASI Benefit Claims During COVID?”
by R. Vincent Pohl and David Mann, Mathematica Policy Research and Kai Filion, U.S. Social Security Administration
The COVID pandemic constitutes a health and economic shock that might lead to higher rates of long-term disability and affect applications for disability-related or early retirement benefits. This project will assess how the pandemic and its economic consequences affected DI applications and awards and early retirement claims.
We will construct a county-month-level dataset of: DI application and initial award rates and early retirement claims; COVID cases and related factors, such as deaths and health care use; and employment rates. We will start by documenting changes in DI applications and awards and early retirement claims during the pandemic and how the changes varied across regions. The project will then use geographic differences in infection rates and economic activity to descriptively document the correlation between severity of the pandemic and new DI applications and initial awards and early retirement claims in 2020 and 2021.
This analysis will shed light on an important consequence of the pandemic for Social Security benefits and contribute to a broader understanding of the factors that determine DI take-up and early retirement claims.
4. “Does the Drop in Child SSI Applications and Awards During COVID Vary by Locality?”
by Michael Levere and David Wittenburg, Mathematica Policy Research and Jeffery Hemmeter, U.S. Social Security Administration
This project will assess local-level variation in the decline of child SSI applications and awards during COVID. It will link data from the Supplemental Security Record (SSR) with publicly available sources to explore the correlation between SSI applications and awards and local-level COVID experiences, demographics, and economic characteristics. The results will help SSA identify particularly vulnerable areas that may need post-COVID outreach.
Nationwide, child SSI awards fell by more than 30 percent during COVID (U.S. Social Security Administration 2021a) with a large drop in applications (Emanuel 2021). Based on past research on how office closures impact SSI participation (Deshpande and Li 2019), the closure of all field offices likely affected both applications and awards. Other factors that varied locally – e.g., social, educational, and medical service responses; demographics; reductions in economic activity; and COVID cases and deaths – could also contribute to the decline in applications and awards. It is critical for SSA to understand these patterns in local decline to identify areas with the strongest future need to conduct outreach and encourage equitable program growth.
5. “Does Broadband Access Affect DI Award Rates?”
by Barbara Butrica and Jonathan Schwabish, Urban Institute
The proposed project examines the relationship between broadband internet access and DI awards. If data become available, the project will also examine DI applications, the preferred metric. This topic is important to SSA because the share of DI applications filed through the internet has remained relatively flat since 2012 (U.S. Social Security Administration 2021), despite an increase in broadband access and internet use. The reach of Social Security’s DI program may be limited if adults with disabilities are disproportionally represented among the 14 million Americans without broadband access.
6. “How Might Workers Respond If Social Security’s Revenue Base Were Broadened?”
by Melissa Favreault, Karen Smith, and Richard Johnson, Urban Institute
This project will use restricted IRS statistics of Income (SOI) data to analyze the amount and distribution of workers’ compensation that is excluded from the Social Security contribution base. It will describe the characteristics of workers with excluded compensation and estimate how much additional Social Security tax revenue could be collected under alternate treatment of excluded income. The longitudinal feature of the data will enable us to estimate potential behavioral responses to any changes in the Social Security wage cap, payroll tax rate, or taxability of excluded compensation.
7. “How Do Racial Disparities in Lifetime Earnings Shape Social Security and SSI Benefits?”
by Melissa Favreault, Urban Institute and Tokunbo Oluwole, Gayle L. Reznik, and Christopher R. Tamborini, U.S. Social Security Administration
This project will use pooled data from the Current Population Survey matched to administrative records on earnings, program participation, immigration status, and mortality to examine how earnings differences affect future Social Security benefits. We will document long-range earnings disparities by race, Hispanic origin, nativity, sex, and education simultaneously and show how long-range earnings inequities affect key Social Security policy parameters. Our estimates can help improve SSA and Urban Institute distributional projections of OASDI and SSI proposals, thus bolstering capacity for racial equity scoring.
8. “What Is the Risk to OASI Benefits from Unpaid Student Loans?”
by Gal Wettstein and Siyan Lu, Boston College
This project will use the Survey of Consumer Finances (SCF) to examine the extent to which OASI benefits are at risk of being garnished due to delinquent student debt. SSA has an interest in this question because rising student loan delinquency, particularly among older adults, may threaten the economic security of OASI beneficiaries.
Student debt has been rising over the past few decades, including among older adults. While the magnitude of student debt held by those over 65 is not large, both the share holding such debt and the mean amount of debt have risen rapidly since 1990, with the pace of growth faster for Black borrowers than for whites. Defaults on student loans have similarly been rising among older debt holders, particularly for loans for education at Minority Serving Institutions. Education loans are unusual in that they cannot be discharged through bankruptcy. Relatedly, federal payments, including OASI benefits, can be withheld by Treasury to pay for delinquent loans. This project will estimate how much student debt is held by OASI beneficiaries, and how much of their benefits are at risk of being withheld due to loan delinquency.
9. “How Do Cost-of-Living Differences Affect Retirement for Low and Moderate Earners?”
by Robert L. Siliciano and Laura D. Quinby, Boston College
This proposal will use the Health and Retirement Study to analyze how differences in local costs of living affect three retirement decisions – how much to save, when to claim, and whether to move after retiring – with a focus on low-skilled workers. SSA has an interest in knowing the extent to which benefits can support retirement – particularly for low-skilled workers – in expensive locations.
U.S. cities have large and growing differences in the cost of living, where housing costs in coastal metropolitan areas are multiple times the national average. Labor and housing markets have adjusted so that housing prices have moved with wages, with high-cost areas offering higher wages to compensate workers. However, workers in high-cost, high-wage areas see lower replacement rates in their OASI benefits relative to similar workers in low-cost, low-wage areas, due to the program’s progressive formula. As a result, these same workers in the high-cost area may be less prepared for retirement and may need to work longer, save more, or move to a cheaper destination once they stop working.
10. “How Has COVID Affected Household Balance Sheets?”
by Andrew G. Biggs, American Enterprise Institute and Anqi Chen and Alicia H. Munnell, Boston College
In 2019, about 40 percent of households said they would have trouble paying for a $400 unexpected expense. This percentage would have likely increased during the COVID pandemic if not for the stimulus checks. When households are operating under such tight budgets, saving for long-term goals such as retirement can be challenging. SSA has an interest in households’ ability to save and their reliance on Social Security.
During the pandemic, most households received stimulus checks totaling several thousand dollars, regardless of employment status. For those who lost their jobs, the payments likely went to cover basic expenses. But for those who remained employed, the money could have provided precautionary savings. Full information about the longer-term impact of the stimulus payments on household balance sheets will not be available until the 2022 Survey of Consumer Finances (SCF) is released. This project aims to provide an early assessment of what those 2022 numbers might look like using all available evidence, including the Household Pulse Survey, Survey of Household Economics and Decisionmaking, Panel Study of Income Dynamics, and Consumer Expenditure Survey.
11. “How Have COVID Experiences Varied by Race Among Older Adults with Disabilities?”
by Amal Harrati and Marisa Shenk, Mathematica Policy Research
This project will study disparities in the experiences of older adults during the COVID pandemic using data from the COVID module of the 2020 Health and Retirement Study. The research will inform SSA’s understanding of the disproportionality of negative COVID outcomes among vulnerable populations, the intersectionality of disability with race and ethnicity among Americans over age 50, and opportunities for targeting supports to underserved communities most impacted by COVID.
The pandemic has highlighted vulnerabilities in both economic security and physical health among older adults, people with disabilities, and people of color. We will explore the effects of the intersectionality of these identities, as well as examine the ways in which they are influenced by the structural forces that both contribute to and exacerbate these inequalities.
The HRS fielded a COVID module with a representative sample of older adults that includes information on self-reported effects of COVID on work, finances, and physical health, including COVID diagnoses and receipt of health care.
12. “What Factors Drive Racial Disparities in Housing Wealth Accumulation?”
by Robert L. Siliciano and Gal Wettstein, Boston College
For most households, their home is the largest source of wealth at retirement, and homeownership provides a key tool for households to build wealth. However, a long history of discrimination in the housing market has constrained the ability of Black households to accumulate housing wealth. The two reasons limiting Black housing wealth are that Black households are less likely to own houses and, when they do, they see lower wealth accumulation compared to similar white homeowners. This study will focus on the second reason and will quantify the extent to which disparities in the housing market limit the ability of Black homeowners to accumulate housing wealth for retirement. SSA has an interest in this question because an inability for Black households to accumulate wealth makes them more dependent on Social Security benefits when they retire.
This study will use the Panel Study of Income Dynamics and the Survey of Consumer Finances to estimate the extent to which three factors – not receiving parental assistance with down payments, slower appreciation, and higher mortgage interest rates – contribute to the housing wealth gap at retirement.
13. “How Do Health and Marital Shocks Affect Disparities at Older Ages?”
by Richard Johnson and Melissa Favreault, Urban Institute
This project will use Health and Retirement Study data, including exit interviews and links to administrative earnings records, to measure the incidence of health and marital shocks after age 70, assess their impact on household wealth, and compare outcomes by race/ethnicity and other characteristics. SSA has an interest in identifying those factors, especially the need for long-term services and supports (LTSS), that contribute to economic hardship at older ages and understanding disparities by race/ethnicity.
The analysis will measure how LTSS needs, chronic health conditions, health care and LTSS use, widowhood, and divorce affect the level of and changes in household wealth and the probability that older adults have depleted their household wealth at the time of death. Although past studies have documented the deleterious effect of later-life health shocks, no consensus has emerged on how often LTSS needs cause older adults to exhaust their savings and how that risk varies by lifetime earnings and by race/ethnicity.
14. “Is the Scarring from Unemployment Worse for Black Workers?”
by Laura D. Quinby and Gal Wettstein, Boston College and Glenn Springstead, U.S. Social Security Administration
This project will use the Continuous Work History Sample (CWHS) and the Panel Study of Income Dynamics (PSID) to examine whether unemployment’s “scarring” of future earnings affects Black workers more than otherwise similar white workers. SSA has an interest in this question as Black workers experience more frequent and longer unemployment spells than white workers, a trend recently exacerbated by the COVID pandemic.
While it is well known that job loss hurts the long-run earnings of displaced workers, recent research does not emphasize how the effect might vary by race. Displaced Black workers may have a harder time recovering earnings than similar white workers because of discrimination in hiring. However, a simple analysis could miss this dynamic because – due to continuing differences in education and employment opportunities – Black workers are less likely to hold the type of “career ladder” jobs that offer large wage premiums, and therefore have less to lose. This study will use regression analysis to consider how job loss affects the subsequent earnings of Black and white workers who are similar along many dimensions, including education and prior earnings.
15. “How Has BOND Affected Work Outcomes by Race?”
by Amal Harrati and Denise Hoffman, Mathematica Policy Research and John Jones, U.S. Social Security Administration
We propose to re-examine impacts from the Benefit Offset National Demonstration (BOND) to explore racial differences in outcomes. Specifically, we will examine: 1) whether racial differences in program impact exist; and 2) the extent to which differences can be traced to community-level racial inequities in economic conditions. This research can highlight structural forces that contribute to racial disparities in return to work and inform future SSA efforts to tailor program implementation to help alleviate these disparities.
Racial inequalities in local labor market conditions and opportunities may have limited the reach of the BOND intervention for some or all participants. This analysis will identify characteristics of participants’ communities that may hinder employment opportunities by race. We will pair data from the BOND impact analysis with four well-validated measures of racial inequalities in employment and economic conditions for participants’ county of residence.
16. “How Will COVID Affect the Mortality of Older Adults?”
by Gal Wettstein, Anqi Chen, and Alicia H. Munnell, Boston College
This project uses data from the American Community Survey, the Health and Retirement Study, and the National Vital Statistics System to approximate the medium-term mortality rate of the post-COVID population of older adults in the United States. SSA has an interest in knowing how the pandemic will affect mortality rates to estimate program liabilities and trust fund depletion in the near term, and to separate the effect of COVID from general trends in mortality for long-term actuarial projections.
COVID has caused the deaths of many older adults, which reduces total Social Security spending, all else equal. But the victims are disproportionately older, sicker, and from racial and ethnic minorities – groups with generally high mortality rates. Thus, mortality experience over the next few years will likely be lower than it would have been absent COVID. This project will account for the demographic and health characteristics of the COVID victims to estimate mortality rates among older adults, after the acute phase of the pandemic.
17. “How Has the Evolving Nature of Work Affected Health and Disability?”
by Stipica Mudrazija and Barbara Butrica, Urban Institute
The nature of work and job-related health requirements has changed dramatically over time, largely due to the shift from goods-producing jobs to service jobs as well as technological change and automation. As the nature of work has evolved, so have job-related health requirements. What is less understood is whether the evolving nature of work has also impacted the relationship between health and work-related disability and disability applications.
Using data from the Health and Retirement Study, supplemented with data on job demands from the Occupational Requirement Survey and Occupational Information Network, this project will document trends in the association of health and functioning with the risk of experiencing a work-limiting health event and applying for disability benefits. It will also assess whether the changing composition of jobs and job demands impacted the strength of the relationship between health status and the two outcomes of interest.
1. “Why Are Some Areas “Hot Spots” of Disabling Condition Prevalence?”
by Anna Hill and Jody Schimmel Hyde, Mathematica Policy Research and Jonathan Schwabish, Urban Institute
This project will identify geographic “hot spots” where the prevalence of certain primary impairments among DI and SSI awardees is substantially above average. The results will inform SSA’s understanding of geographic variation and trends in program awards. The analysis will leverage a public-use file that is currently being developed as part of BC20-06 that will include information on the primary impairments of DI and SSI awardees at the level of the U.S. Census Bureau Public Use Microdata Areas.
Previous work has documented substantial geographic variation in DI and SSI receipt, and a separate strand of literature has considered trends in disabling conditions among beneficiaries. Less is known, however, about the extent of geographic variation in disabling conditions.
2. “What Is the Relationship between Deprivation and Child SSI Participation?”
by Michael Levere and David Wittenburg, Mathematica Policy Research and Jeffrey Hemmeter, U.S. Social Security Administration
This project will map the relationship between child SSI participation and measures of local community deprivation using administrative data from the Supplemental Security Record and the Health Resources and Services Administration’s Area Deprivation Index. This research will be useful to SSA in assessing the relationship between SSI participation and deprivation.
We will examine the relationship at the county level of SSI participation and economic deprivation. For example, areas that have low rates of SSI participation and high rates of deprivation are potential areas where SSA could fulfill its statutory responsibility of conducting outreach. Conversely, areas that have high rates of SSI participation and low rates of deprivation are candidates for better understanding why some areas rely on SSI more than others. We will also conduct case studies in census tracts, focusing on high deprivation and low SSI participation that are candidates for potential outreach efforts.
3. “How Accurate Are HRS Self-Reports of Disability Benefit Application and Receipt”
by Amal Harrati and Jody Schimmel Hyde, Mathematica Policy Research
This project will assess the accuracy of self-reports of applications to and receipt of DI and SSI using data from the Health and Retirement Study linked to SSA administrative records. The findings will help SSA better understand the advantages and limitations of using HRS self-reported and administrative data for disability policy research.
The HRS is the preeminent data source for research on the financial decision-making of older adults, but it has been underused for disability policy research (Schimmel Hyde and Stapleton 2017). The rich HRS data are matched to longitudinal SSA administrative records, which together offer a unique option for analyzing benefit claiming decisions and beneficiary outcomes. Thus, underuse of the HRS for disability research represents a missed opportunity.
4. “What Are Pathways to Overpayments”
by Denise Hoffman and Michael Anderson, Mathematica Policy Research and John Jones, Social Security Administration
This project will study the experiences of the 2008 cohort of first-time DI beneficiaries who were at risk for work-related overpayments from award through 2018 using data from SSA’s Disabled Beneficiaries and Dependents files, Disability Analysis File, and Master Earnings File. The results will inform SSA’s understanding of the trajectories that lead beneficiaries to overpayments, which could identify mitigation strategies.
To date, limited information is available on work-related overpayments, such as the total amount and duration of overpayments and the average characteristics of overpaid beneficiaries. Previous research documents that more than 70 percent of beneficiaries at risk of a work-related overpayment were overpaid in a three-year window (Hoffman et al. 2019). However, experiences and trajectories presumably vary across beneficiaries and understanding common pathways may help identify points of intervention that could prevent overpayments.
5. “What Happens Following DI Termination?”
by Michael Anderson and Denise Hoffman, Mathematica Policy Research and Kai Filion, Social Security Administration
This project will use data from SSA’s Disability Analysis File and Master Earnings File to document trends in labor market outcomes and return to DI or SSI following termination of DI benefits. The results will be useful to SSA in: 1) informing potential interventions to promote self-sufficiency and reduce return to disability benefit entitlement; and 2) anticipating potential outcomes of proposed legislative changes.
Prior research suggests that beneficiaries terminated for medical improvement have limited earnings following termination and may return to SSA disability programs. However, that research focused on benefit terminations through 2008 and did not include termination for employment. We will add to the existing literature by identifying DI beneficiaries whose benefits were terminated for medical improvement or employment in 2001-2018 and track the outcomes of those terminated by 2013 in the first 5 years following termination. The years after 2008 are of special interest because of the recovery following the Great Recession and because of changes in the composition of the DI caseload since that time.
6. “What Is the Preferred Consumption Pattern in Retirement?”
by Anqi Chen, Robert Siliciano, and Alicia H. Munnell, Boston College
The life-cycle model, under certain assumptions, predicts a stable consumption path in retirement. Consistent with this model, Social Security provides steady inflation-adjusted benefits, and financial planners and researchers often assume that retirees would like to maintain their pre-retirement standard of living. However, several studies suggest that retired households decrease their consumption over time, while others indicate consumption increases as retirees age and pay more for health care. Desired consumption patterns are of direct interest to SSA because they have implications for the adequacy and appropriate indexation of benefits in retirement.
This project will use the Health and Retirement Study to address three shortcomings of the existing literature: 1) the short time period and/or small sample size of household consumption data; 2) the combining of constrained and unconstrained households, which makes it impossible to separate necessity from preferences; and 3) the failure to account for survival bias, whereby only long-lived low-consuming households are alive at older ages. The question is what consumption pattern emerges after adjusting for these shortcomings.
7. “What Share of Non-covered Public Employees Will Earn Benefits that Fall Short of Social Security?” (Part 2)
by Jean-Pierre Aubry, Alicia H. Munnell, and Laura D. Quinby, Boston College
This proposal will combine information from Actuarial Valuations and the Annual Survey of Public Employment and Payroll with the data gathered from a separate study on employee tenure and earnings to estimate the percentage of non-covered workers whose benefits fall short of Social Security. Federal regulations under IRC 3121 were intended to ensure that non-covered state and local employees receive pension benefits comparable to Social Security. Yet, unintended loopholes in the regulations mean that, in some cases, public pensions fall short.
This project will use the detailed data from a separate study to calibrate a model of defined benefit (DB) adequacy that builds on the analysis in Quinby, Aubry, and Munnell (2020). It will expand the model to assess the adequacy of defined contribution (DC) and “hybrid” DB-DC plans for non-covered workers.
8. “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.
9. “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.
10. “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.
11. “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.
12. “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?