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.
Archives: Grant
Did Paid Sick Leave and Family Medical Leave Ameliorate the Health and Economic Effects of the COVID-19 Pandemic?
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.
Racial and ethnic inequality in consumption smoothing
Forty-two percent of Americans report that they do not have savings that could be used to cover unexpected expenses, a staggeringly high number. And there are stark racial differences, with 38 percent of White households and 55 percent of Black households saying they don’t have money to cover an emergency expense—one manifestation of the Black-White wealth divide. Yet there is surprisingly little research on how typical month-to-month fluctuations in income affect consumption and even less evidence on how this consumption smoothing varies with wealth. Given how central consumption dynamics are for macroeconomics, it’s important to understand the sensitivity of consumption to income and how that might vary by race and wealth.
This project uses exciting new data to explore how income shocks may be passed through to consumption. By linking deidentified administrative bank data with self-reported race information from voter registration records, the authors will be able to identify the response of consumption by race with a large enough dataset (the analysis sample consists of 1.8 million matched bank-voter records) to identify racial differences credibly. Understanding how well households can smooth consumption, and how and why some groups—such as Black and Hispanic households who have lower-than-average wealth—may face greater challenges in doing so, is central for developing policy to address economic inequality and ensure vulnerable households achieve economic security.
The impacts of welfare cuts on well-being during the Great Recession: Evidence from linked U.S. administrative and survey data
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.
The redistributional consequences of multiple minimum wages
This project will analyze how the labor market absorbs an increase in the minimum wage. Utilizing the case study of Costa Rica’s highly binding and relatively more comprehensive minimum wage policy that includes multiple wage floors based on workers’ skill levels, the author will use employer-employee microdata and administrative data to explain how minimum wages shape the earnings distribution and the labor market equilibrium.
The long-term evolution of inequality: Poverty, pollution, and human capital
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.
Where does new work come from?
This project will construct a database of new work from 1900 to 2020 by compiling a list of job titles from the U.S. Census Bureau’s Alphabetical Index of Occupations. Previous research on “new work” measures the introduction of new job titles beginning in 1964 and documents that new work is performed by high-skilled workers and in cities. Preliminary work in this project indicates that at least some of these previously documented patterns may not have been true in the middle of the 20th century. The authors’ aim is: to chart the evolution of new work over 12 decades; to assess the potentially varying importance of new work in job creation and skill demands during different epochs in this period; and to test a set of economic hypotheses about where and when new work arises.
The project has the potential to provide insight into why the locus of job creation, measured in terms of occupations, industries, skill demands, and wage levels has varied across decades, and the role of new technologies in the creation of new work. In addition to compiling job titles from U.S. Census data, the researchers will link the text of patents to new job titles to explore the impact of new technologies on jobs, and will link to the Consumer Expenditure Survey to measure demand shifts for the relatively recent period (from 1980 onward) to test the hypothesis that demand shifts may lead to new work.
Recessions during young adulthood and U.S. racial income inequality
This research promises to advance our understanding of employment scarring by empirically teasing out the racial differences in long-term consequences of deep U.S. economic downturns for those who are relatively young when a recession hits. Focusing on the 1980 recession, which was both deep and long, the author will use a triple-difference approach to examine the recession’s long-run effects by comparing the incomes in adulthood of teens (ages 14 to 17) and young adults (ages 18 to 22) (first difference), living in counties with a more-severe versus less-severe recessions (second difference), who are Black or Hispanic versus White (third difference).
Using the differences in the severity of the recession across local areas as an identifying variation, the author will utilize individual-level data from the National Longitudinal Survey of Youth in 1979, along with county-level location data with special access from the U.S. Bureau of Labor Statistics. The 1980 recession is far enough in the past to allow a study of the outcomes of the sample when individuals are in their mid-30s to mid-40s years of age. This research is poised to provide insight into the long-run effects of recessions on Black and Hispanic youth who resided in regions where the recession was deepest, adding nuance to our understanding of the “scarring” effects of recessions on young workers by adding a racial component. Givin the current economic situation, it is clear why this research is relevant to current policy debates.
Domestic outsourcing in the United States
Recent research finds that most, if not all, of the growth in earnings inequality in the United States may be explained by the growth in inequality across firms or establishments. This finding is consistent with research showing that workers in outsourced establishments—such as call centers, janitorial service companies, or security services—receive lower pay and benefits than those workers doing the same jobs but who are employed by lead or primary firms. But our knowledge of the extent and impact of outsourcing on a broader set of workers is limited, in large part because of data constraints.
This study will provide evidence based on rigorous, quantitative analysis of the extent to which outsourcing has contributed to inequality in the United States. The study will rely on Longitudinal Employer-Household Dynamics data linked with American Community Suvey data and will use the methodology established in a previous paper based on German data. A key shortcoming of the LEHD data is that it does not have information on occupation. By linking to ACS data, the authors will be able to observe occupation for a subset of those in the LEHD dataset and to assess the effects of outsourcing on outcomes besides earnings—most critically, health insurance.
The impact of a tuition credit program on Pell-eligible student outcomes
Research shows how important college is to upward economic mobility. Yet there are many barriers to getting into and completing college, most notably cost. Community colleges are frequently touted as a cost-effective path, whereby students begin at a community college and then transfer to a 4-year university. This research focuses on transfer students and Wisconsin’s Promise Tuition grants, a place-based scholarship which offers debt-free tuition assistance.
Over the past decade, more and more states and postsecondary institutions are offering such grants, yet there is virtually no research that focuses on their impact on transfer students, particularly transfer students’ degree completion. This project explores the intersection between transfer students, their perceptions related to college finances, and the design of Promise Tuition scholarships and grants by using a mixed methods study.
The first part utilizes student-level administrative data from the University of Wisconsin to examine course-taking patterns, credits attempted and completed, Grade Point Average, persistence rates, financial aid eligibility and receipt, and degrees conferred. The second part is a survey of a random sample of transfer students in order to elicit information regarding college experiences and finances. This rich case study promises to inform not only policy debates around college affordability and completion, but also our understanding of how the institutional structures of postsecondary education in the United States are supporting or inhibiting intergenerational mobility.