Thursday, Aug 7: 10:30 AM - 12:20 PM
0523
Invited Paper Session
Music City Center
Room: CC-106A
"If you can't measure it, you can't manage it." The principle expressed in this quote, often attributed to Peter Drucker, motivates recent interest in promoting data equity. Policy analysts and program administrators often strive to reach populations at the margins of society. However, these populations tend to be historically undercounted or difficult to identify in official data sources.
Heightened interest in measuring the marginalized comes at a turbulent time for the federal statistical system. Statistics have traditionally been built on surveys, but there is growing reluctance to participate in federal surveys owing to multiple factors such as distrust of government and survey fatigue. The growth of statistics built on administrative data has helped increase the sophistication of public data consumers and sparked demand for more timely and more granular data. In response to these developments, the federal statistical system appears to be headed towards a future where surveys and administrative data are blended.
An open question remains: how do we blend data sources to learn about difficult-to-study segments of the U.S. population? Work that documents gaps or exploits innovative data or methods to fill these gaps is critical for establishing the bedrock on which the next-generation statistical infrastructure will be built. This session features four papers highlighting the measurement of marginalized, difficult-to-study populations: older criminal-justice-involved adults, transgender individuals, children facing elevated mental health risks, and people experiencing homelessness.
The first paper, "Criminal Justice Involvement and Well-Being in Old Age," uses data from the Criminal Justice Administrative Records Systems linked with survey and administrative data sources from the U.S. Census Bureau to provide the first evidence on the looming retirement crisis stemming from the aging generations of Americans who have been increasingly impacted by criminal justice policies like mass incarceration. (Authors: Jennifer Doleac, Jonathan Eggleston, William Gale, Michael Mueller-Smith, and Briana Sullivan)
The second, "Transgender Earnings Gaps in the United States: Evidence from Administrative Data," provides the first evidence on transgender earnings in the U.S. using administrative data on over 55,000 individuals who changed their gender marker with the Social Security Administration and had gender-congruent first name changes on tax records. (Authors: Christopher S. Carpenter, Lucas Goodman, and Maxine J. Lee)
The third, "Helping policymakers better predict the prevalence of children's mental health conditions: An analysis using restricted and publicly available health and education data," uses use publicly available, county- and school district-level datasets along with linked, health and education administrative from the State of Tennessee to predict the prevalence of mental health conditions among Tennessee children. (Authors: Liliane Nienstedt, Carolyn Heinrich, Carrie Fry, Melinda Buntin)
The fourth, "Homelessness and the Persistence of Deprivation: Income, Employment, and Safety Net Participation," links the 2010 Census to numerous sources of tax and safety net data to provide the most detailed and accurate portrait to date of the level and persistence of material disadvantage faced by people experiencing homelessness in the U.S., including the first national estimates of income, employment, and safety net participation based on administrative data. (Authors: Bruce D. Meyer, Angela Wyse, Alexa Grunwaldt, Gillian Meyer, Derek Wu)
Overall, this session aims to create a forum for discussion of shared challenges and opportunities in measuring these marginalized populations and for learning about difficult-to-study populations beyond those explicitly covered by this session.
Measurement
Criminal justice
Homelessness
Mental health
Transgender individuals
Applied
Yes
Main Sponsor
Government Statistics Section
Co Sponsors
Social Statistics Section
Presentations
This paper uses data from the Criminal Justice Administrative Records Systems linked with survey and administrative data sources from the U.S. Census Bureau to provide the first evidence on the looming retirement crisis stemming from the aging generations of Americans who have been increasingly impacted by criminal justice policies like mass incarceration. First, we characterize the living circumstances of those with criminal histories approaching retirement. In spite of almost a decade of criminal desistance on average, this population exhibits serious economic vulnerability, higher disability rates, and greater detachment from kinship networks, factors that put these individuals at risk in retirement. Current data indicate a growing reliance on safety net programs such as the Supplemental Security Income program, for which eligibility does not depend on work history. Second, we measure the share of current retirees with criminal records, and provide projections of how these rates among retiring cohorts will increase through 2050. We find that approximately 13% of those age 62 in 2018 have a criminal record, and this will grow to 23% over the next two decades, peaking among cohorts retiring around 2040. Finally, we leverage two recent class action lawsuits that constrained the Social Security Administration's ability to deny SSI and OASDI benefits to those with criminal records. This analysis shows that extending safety benefits to the aging justice-involved populations has a number of important benefits: reducing poverty; decreasing disability and mortality rates; lowering usage of costly living arrangements like nursing homes, homeless shelters, and residential treatment facilities; and strengthening co-residency among families.
Keywords
Criminal justice
We provide the first evidence on transgender earnings in the US using administrative data on over 55,000 individuals who changed their gender marker with the Social Security Administration and had gender-congruent first name changes on tax records. We validate and describe this sample which exhibits positive selection likely associated with the ability to legally affirm gender. To address selection we estimate transgender earnings gaps using timing variation within-person and variation across siblings and coworkers. All three approaches return evidence of robust transgender earnings penalties of 6-13 log points driven by extensive and intensive margin differences.
Keywords
Transgender
Speaker
Maxine Lee, San Francisco State University
One in five children has a mental health condition, yet less than half of these children receive needed treatments and services. Many state and local policymakers need tools to better identify and prioritize children most at risk of mental health conditions and their negative consequences. We use publicly available, county- and school district-level datasets along with linked, health and education administrative from the State of Tennessee to predict the prevalence of mental health conditions among Tennessee children. These data include diagnoses of mental health conditions at the child level, allowing us to assess the prevalence of these conditions (by child age) across the state. Recognizing, however, that many policymakers making decisions about the distribution of finite resources do not have access to these rich, linked data systems, we address the question: in the absence of individual-level administrative data on child mental health, can policymakers predict where children's mental health needs are greater? We separately predict the prevalence of mental health conditions among children first using only non-publicly available data and then using only publicly available county-level measures. Next, we combine measures from both sets of data to perform the same analysis and compare the predictive models' performance across these specifications. We assess whether there are key variables that consistently predict the prevalence of children's mental health needs/conditions across the estimations and whether there are publicly available data that could provide a sufficient guide for the allocation of resources to better meet children's mental health needs.
Keywords
Children
Mental health
Homelessness is arguably the most extreme hardship associated with poverty in the United States, yet people experiencing homelessness are excluded from official poverty statistics and much of the extreme poverty literature. This paper provides the most detailed and accurate portrait to date of the level and persistence of material disadvantage faced by this population, including the first national estimates of income, employment, and safety net participation based on administrative data. Starting from the first large and nationally representative sample of adults recorded as sheltered and unsheltered homeless taken from the 2010 Census, we link restricted-use longitudinal tax records and administrative data on the Supplemental Nutrition Assistance Program (SNAP), Medicare, Medicaid, Disability Insurance (DI), Supplemental Security Income (SSI), veterans' benefits, housing assistance, and mortality. Nearly half of these adults had formal employment in the year they were observed as homeless, and nearly all either worked or were reached by at least one safety net program. Nevertheless, their incomes remained low for the decade surrounding an observed period of homelessness, suggesting that homelessness tends to arise in the context of long-term, severe deprivation rather than large and sudden losses of income. People appear to experience homelessness because they are very poor despite being connected to the labor market and safety net, with low permanent incomes leaving them vulnerable to the loss of housing when met with even modest disruptions to life circumstances.
Keywords
Homelessness