Funded Research

Our funding interests are organized around the following four drivers of economic growth: macroeconomic policy, market structure, the labor market, and human capital. We consider proposals that investigate the consequences of economic inequality, as well as group dimensions of inequality; the causes of inequality to the extent that understanding these causal pathways will help us identify and understand key channels through which inequality may affect growth and stability; and the ways in which public policies affect the relationship between inequality and growth.

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Public policy and opioid drug abuse: Investigating the effects of paid family and medical leave and Medicaid

Grant Year: 2019

Grant Amount: $135,700

Grant Type: doctoral

This research will analyze how state-level paid family medical leave and Medicaid expansions influence drug-related outcomes. The research team will draw from a variety of administrative data sources, including restricted individual-level mortality data from the Centers for Disease Control; data from the Healthcare Cost and Utilization Project’s National Inpatient Sample and Nationwide Emergency Department Sample; and the Treatment Episode Data Set-Admissions. Drawing from these rich data sources in combination with information on population demographic characteristics and state policies, the team will employ a variety of causal inference techniques to examine whether access to paid family medical leave can help reduce the abuse of opioids. While a large literature has examined the impacts of paid family medical leave on parental leave-taking, labor market outcomes, and child health, there is no research to date on whether it can influence drug abuse and treatment. Similarly, there is little research on the effect of Medicaid coverage on drug-related deaths or measures of drug-related morbidity.

Understanding the effects of California’s paid family and medical leave law on inequality in labor market outcomes for older adults

Grant Year: 2019

Grant Amount: $90,100

Grant Type: doctoral

The project seeks to identify the causal impact of paid leave on older workers using the case of California’s paid family leave program. The research team will take a quasi-experimental approach, using data from the American Communities Survey to compare outcomes of older workers to younger workers in California and in comparison states, both before and after the program’s implementation. They will examine impacts on labor force participation, employment status, level of work effort, earnings, and income to provide a fuller picture of how the labor market experience is impacted by the policy. Importantly, the team will examine how effects vary by subgroup of workers and how paid leave affects disparities in labor force participation. There is little research on how provision of eldercare may affect the employment of caregivers, and similarly little research on how access to paid family leave may change the employment landscape for those who might be called on to provide eldercare. As increasing numbers of policymakers consider adopting paid family and medical leave programs, this research will provide timely and relevant information on how paid leave affects the labor force participation of people who are likely to have caregiving responsibilities.

Scheduling strategies for warehouse work

Grant Year: 2019

Grant Amount: $80,000

Grant Type: academic

This project will partner directly with a warehousing firm in order to: document the risks of certain schedules for subjective well-being and self-reported health for workers and specific demographic groups; document the relationships between work schedules and turnover for workers and for specific demographic groups; quantify the costs of current scheduling practices for the organization by building a more systemic view of the interdependencies of scheduling, absenteeism, productivity, and turnover; and develop and evaluate a workplace intervention targeting workers’ control over their schedules using a cluster-randomized trial.

Understanding the incidence of minimum wage increases

Grant Year: 2019

Grant Amount: $60,000

Grant Type: academic

This project aims to understand how firms accommodate increases in the minimum wage by using granular compensation data that the research team will construct by merging the individual tax returns of all employees and contractors of a firm to the business tax return of the firm. These data allow for an exploration of how changes in the minimum wage affect the full distribution of employee and contractor compensation within affected firms, including changes in employment and income. They will look at which kinds of workers, if any, lose or gain employment following increases in the minimum wage and how the incomes of covered and uncovered workers, as well as firm owners, are affected. Notably, the 17-year data panel will enable them to study dozens of minimum wage increases legislated at the federal, state, and substate level.

Between exclusion and cumulative advantage: Effects of within-organization mobility on inequality

Grant Year: 2019

Grant Amount: $30,510, co-funded with the Russell Sage Foundation

Grant Type: academic

This research seeks to empirically disentangle and quantify job moves that occur within versus between employers. It utilizes two main sources of data: the Current Population Survey and restricted versions of the Survey of Income and Program Participation. The project investigates the extent to which aggregate trends in wage inequality are the result of increased within-organization job mobility and whether this shift has disproportionately benefited high-income/high-skill workers. It will also account for heterogeneity of outcomes among low-skilled/low-educated workers by exploring under what conditions less-educated workers benefit from internal labor markets and whether these conditions vary systematically by industry, occupation, or region.

New evidence on local minimum wage laws and earnings inequality

Grant Year: 2019

Grant Amount: $50,000

Grant Type: academic

The research team will develop the Washington Merged Longitudinal Administrative Data, which will link demographic information to employment records, and public program administrative data. It will construct households from these state-level data, including the creation of detailed documentation and testing that will allow other scholars to replicate these methodological innovations for analysis of a host of policy interventions on household income and program participation.

Funded research

Human Capital

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

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Funded research

Macroeconomic Policy

What are the implications of inequality on the long-term stability of our economy and its growth potential?

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Funded research

Market Structure

Are markets becoming less competitive and, if so, why, and what are the larger implications?

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Funded research

The Labor Market

How does the labor market affect equitable growth? How does inequality in turn affect the labor market?

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