Grant Category

Human Capital and Wellbeing

How does economic inequality affect the development of human capital, and to what extent do aggregate trends in human capital explain inequality dynamics?

The acquisition and deployment of human capital in the market drives advances in productivity. The extent to which someone is rich or poor, experiences family instability, faces discrimination, or grows up in an opportunity-rich or opportunity-poor neighborhood affects future economic outcomes and can subvert the processes that lead to productivity gains, which drive long-term growth.

How does economic inequality affect the development of human capital, and to what extent do aggregate trends in human capital explain inequality dynamics? To what extent can social programs counteract these underlying dynamics? We are interested in proposals that investigate the mechanisms through which economic inequality might work to alter the development of human potential across the generational arc, as well as the policy mechanisms through which inequality’s potential impacts on human capital development and deployment may be mitigated.

  • Economic opportunity and intergenerational mobility
  • Economic instability
  • Family stability
  • Neighborhood characteristics

Explore the Grants We've Awarded

Reset

COVID-19 and Paid Leave: Assessing the Impact of the FFCRA

Grant Year: 2020

Grant Amount: $20,000

Grant Type: doctoral

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.

Access to Paid Leave during the Covid-19 Pandemic: Evidence from NYC

Grant Year: 2020

Grant Amount: $28,000

Grant Type: doctoral

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.

Did Paid Sick Leave and Family Medical Leave Ameliorate the Health and Economic Effects of the COVID-19 Pandemic?

Grant Year: 2020

Grant Amount: $34,500

Grant Type: doctoral

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.

The impacts of welfare cuts on well-being during the Great Recession: Evidence from linked U.S. administrative and survey data
  • Derek Wu University of Chicago
  • The impacts of welfare cuts on well-being during the Great Recession: Evidence from linked U.S. administrative and survey data

Grant Year: 2020

Grant Amount: $15,000

Grant Type: doctoral

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 long-term evolution of inequality: Poverty, pollution, and human capital

Grant Year: 2020

Grant Amount: $61,000

Grant Type: academic

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.

Recessions during young adulthood and U.S. racial income inequality

Grant Year: 2020

Grant Amount: $20,000

Grant Type: academic

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.

Experts

Research Advisory Board

Larry Katz

Harvard University

Learn More
Grantee

T. William Lester

San José State University

Learn More
Grantee

David Autor

Massachusetts Institute of Technology

Learn More
Grantee

Ammar Farooq

Uber

Learn More
Guest Author

John Majewski

University of California, Santa Barbara

Learn More

Explore other grant categories

Our funding interests are organized around the following four drivers of economic growth: the macroeconomy, human capital and the labor market, innovation, and institutions.

View all grant categories