An official website of the United States government
Wage insurance provides income support to displaced workers who find reemployment at a lower wage. We study the effects of the wage insurance provisions of the US Trade Adjustment Assistance (TAA) program using administrative data from the state of Virginia. The program includes an age-based eligibility cutoff, allowing us to compare earnings and employment trajectories for workers whose ages at the time of displacement make them eligible or ineligible for the program. Our findings suggest that wage insurance eligibility increases short-run employment probabilities and that wage insurance and TAA training may yield similar long-run effects on employment and earnings.
more »
« less
Long-Term Impacts of Childhood Medicaid Expansions on Outcomes in Adulthood
Abstract We use administrative data from the Internal Revenue Service to examine long-term impacts of childhood Medicaid eligibility expansions on outcomes in adulthood at each age from 19 to 28. Greater Medicaid eligibility increases college enrolment and decreases fertility, especially through age 21. Starting at age 23, females have higher contemporaneous wage income, although male increases are imprecise. Together, both genders have lower mortality. These adults collect less from the earned income tax credit and pay more in taxes. Cumulatively from ages 19 to 28, at a 3% discount rate, the federal government recoups 58 cents of each dollar of its “investment” in childhood Medicaid.
more »
« less
- Award ID(s):
- 1350132
- PAR ID:
- 10142426
- Date Published:
- Journal Name:
- The Review of Economic Studies
- ISSN:
- 0034-6527
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract We estimate the effect of losing Supplemental Security Income (SSI) benefits at age 18 on criminal justice and employment outcomes over the next two decades. To estimate this effect, we use a regression discontinuity design in the likelihood of being reviewed for SSI eligibility at age 18 created by the 1996 welfare reform law. We evaluate this natural experiment with Social Security Administration data linked to records from the Criminal Justice Administrative Records System. We find that SSI removal increases the number of criminal charges by a statistically significant 20% over the next two decades. The increase in charges is concentrated in offenses for which income generation is a primary motivation (60% increase), especially theft, burglary, fraud/forgery, and prostitution. The effect of SSI removal on criminal justice involvement persists more than two decades later, even as the effect of removal on contemporaneous SSI receipt diminishes. In response to SSI removal, youth are twice as likely to be charged with an illicit income-generating offense than they are to maintain steady employment at $${\$$}$$15,000/year in the labor market. As a result of these charges, the annual likelihood of incarceration increases by a statistically significant 60% in the two decades following SSI removal. The costs to taxpayers of enforcement and incarceration from SSI removal are so high that they nearly eliminate the savings to taxpayers from reduced SSI benefits.more » « less
-
We estimate the cost and impact of a proposed anti-displacement program in the Westside of Atlanta (GA) with data science and machine learning techniques. This program intends to fully subsidize property tax increases for eligible residents of neighborhoods where there are two major urban renewal projects underway, a stadium and a multi-use trail. We first estimate household-level income eligibility for the program with data science and machine learning approaches applied to publicly available household-level data. We then forecast future property appreciation due to urban renewal projects using random forests with historic tax assessment data. Combining these projections with household-level eligibility, we estimate the costs of the program for different eligibility scenarios. We find that our household-level data and machine learning techniques result in fewer eligible homeowners but significantly larger program costs, due to higher property appreciation rates than the original analysis, which was based on census and city-level data. Our methods have limitations, namely incomplete data sets, the accuracy of representative income samples, the availability of characteristic training set data for the property tax appreciation model, and challenges in validating the model results. The eligibility estimates and property appreciation forecasts we generated were also incorporated into an interactive tool for residents to determine program eligibility and view their expected increases in home values. Community residents have been involved with this work and provided greater transparency, accountability, and impact of the proposed program. Data collected from residents can also correct and update the information, which would increase the accuracy of the program estimates and validate the modeling, leading to a novel application of community-driven data science.more » « less
-
null (Ed.)Abstract The 2012 Deferred Action for Childhood Arrivals (DACA) program granted work authorization and protection from deportation to more than 800,000 young undocumented immigrants who arrived to the United States as minors. We estimate the association between this expansion of legal rights and birth outcomes among 72,613 singleton births to high school–educated Mexican immigrant women in the United States from June 2010 to May 2014, using birth records data from the National Center for Health Statistics. Exploiting the arbitrariness of the upper age cutoff for DACA eligibility and using a difference-in-differences design, we find that DACA was associated with improvements in the rates of low birth weight and very low birth weight, birth weight in grams, and gestational age among Mexican immigrant mothers.more » « less
-
null (Ed.)Growing economic disparities and the increased sorting of families into economically segregated communities have heightened the need to clearly delineate pathways through which family income promotes children’s development. Combining hypotheses from investment and stress theories, we developed and tested a multi-context and cross-domain conceptual model assessing how community and family contexts mediate links between family income and children’s cognitive and behavioral skills at kindergarten entry. We drew data on family income, parenting processes, and child functioning from the Early Childhood Longitudinal Study– Birth Cohort (ECLS-B; N ≈ 10,650), following children from infancy through age 5. We used Geographic Information Systems technology to create and validate community measures using administrative data from the Economic Census, Decennial Census, National Center of Education Statistics, Federal Bureau of Investigations, and Environmental Protection Agency, which were then linked to each child in the ECLS-B. Using structural equation modeling, our analyses revealed three primary lessons. First, lower-income children have limited access to community educational and cultural resources and heightened exposure to community stressors including concentrated disadvantage and violent crime. Second, these community features are associated with parenting processes, such that parent-child interactions tend to be less stimulating and supportive and more punitive in communities with fewer resources and heightened stressors. And third, community and family contexts together mediate connections between family income and children’s cognitive and behavioral functioning. Results, albeit showing small effect sizes, provide a more complex, multi-contextual view than prior research, delineating the role of both resources and stressors at community and family levels in explaining income disparities in young children’s developmental success.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/restud/rdz039
