Prior research suggests that the pathways through which childhood poverty shapes poverty in adulthood include physical and mental well-being, educational attainment, employment, and family structure. Income support policies, such as the Earned Income Tax Credit, Supplemental Nutrition Assistance Program, and cash assistance from Temporary Assistance for Needy Families, are all known to reduce levels of child poverty and have the potential to reduce racial disparities in child poverty. Using the Panel Study of Income Dynamics from 1967–2018, the researchers plan to investigate how the introduction of and/or policy changes to the EITC, SNAP, and TANF programs are effective at reducing racial differences in the intergenerational transmission of poverty. The authors will disaggregate their findings by race and use individual-level data from the Panel Study of Income Dynamics to identify children in poverty who were exposed to these programs and will follow them through early adulthood, assessing their poverty status.

Using monthly Current Population Survey data, this study will examine leave-taking behavior during the first few months of the coronavirus pandemic in the United States. Specifically, the authors will investigate whether and how leave-taking was influenced by the passage of the Families First Coronavirus Response Act. The researchers will analyze the impact of FFCRA on several employment and leave-taking outcomes such as employment status, usual hours worked, and reasons for work absence (including child-care problems or one’s own illness). They will use these variables to measure leave-taking behavior, including total leave-taking and reasons for leave taking. These data allow them to explore how workers trade off the alternatives to leave-taking, including working while sick or separation from the labor force. Using a difference-in-difference empirical estimation strategy, the authors will compare leave taking in states that do or do not have state-based paid family and medical leave programs.

This study will explore access, use, and outcomes associated with paid leave during the pandemic in New York City utilizing The New York City Longitudinal Study of Health and Wellbeing, also known as the Poverty Tracker. This survey follows representative samples of New York City residents, interviewing them every three months for up to four years and collecting a wealth of data on poverty, hardship (e.g. food insecurity), health and wellbeing, and specialized topics such as assets and debts. The research team will administer a post-COVID-19 survey with members of their second panel, for whom they have four years of pre-COVID-19 data, including information on employment and employer-provided paid sick leave. Interviewing this panel again will allow the researchers to gather important post-COVID-19 data on (1) use of employer-provided paid sick leave, (2) use of New York State paid family and medical leave and temporary disability insurance, and (3) use of the new federal emergency paid sick leave and paid family leave; as well as 4) post-COVID-19 data on poverty, hardship, and health and wellbeing.

This study will examine whether state-mandated paid sick leave and state-mandated paid family and medical leave has helped control the early spread of COVID-19 and ameliorated the economic distress caused by the pandemic. In particular, the research team will explore whether people in states with guaranteed paid sick leave fared better in the pandemic and were better able to adopt social distancing measures compared to those in states without such a guarantee. State administrative data show that, early in the pandemic, there was a surge of initial claims in some states with their own paid leave systems—well before the Families First Coronavirus Response Act was signed into law. The research team will explore whether this surge in leave-taking is reflected in measures of social distancing or staying at home as captured by cell-phone location data, and whether that is reflected in the COVID-19 incidence data. Finally, the authors are also interested in whether there are differences across states with and without paid leave systems in reported measures of illness, leave-taking, and economic and psychological distress associated with the pandemic.

This research project will examine the short- and long-run impacts of being suddenly removed from critical government programs, including the Supplemental Nutrition Assistance Program, Medicaid, and the Temporary Assistance for Needy Families program. The author will utilize the case of Indiana, which, in 2007, attempted to automate its welfare systems, resulting in a number of individuals being removed from essential welfare programs. The author will use linked administrative and survey data to first analyze the effects of the policy change on enrollment and demographics in the programs and then identify the short- and long-term impact of being removed from welfare on earnings, occupation, financial solvency, and health outcomes.

Environmental inequity is intertwined with income inequality in a variety of ways. Demand for housing, for example, is higher in cleaner areas than in polluted ones, and, at the same time, evidence is accumulating that the communities in which children grow up have long-lasting impacts on their economic and other social outcomes. Other research finds that pollution exposure in utero and in early childhood can have lifelong effects on economic outcomes, suggesting pollution may be one important characteristic of the communities in which children grow up. This project engages with these issues by investigating the relationships among race/ethnicity, income, pollution, and human capital in Pittsburgh from 1910 to 2010. The two main areas of research are sorting by race that leads to inequality in pollution exposure, and the effects of childhood exposure to pollution on adult income. Although limited to Pittsburgh, it is a strategic site. Once considered "Hell with a lid off" because of the intense pollution arising from the furnaces of the steel industry, exposure to pollution used to be extremely high in the early 20th century but has since declined dramatically, allowing for the comparison over time. To do this, the authors will take advantage of never-before-used historical data and link it to demographic characteristics of individuals with known residential locations to pollution exposure, jobs, and future outcomes. An anonymized version of these data will be made publicly available, creating a valuable resource for future research.