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.

This project will create a publicly available database of statutory and administrative laws governing the ability of ex-offenders to be granted an occupational license for all universally licensed occupations in the United States. The newly created time-series will be linked with Census microdata, including data from the American Community Survey, Current Population Survey, and Survey of Income and Program Participation. The research team will then use the changes in these ex-offender occupational licensing laws over time and across states to estimate the impact of these laws on the labor market outcomes of workers, with particular attention to the labor market outcomes of minorities. There are very few high-quality studies of the impacts of such licensing laws on employment and earnings among individuals with felonies. This research creates a new, detailed, and valuable dataset of state occupational licensing laws, which will allow both this research team and future researchers to study the impact of these laws on wage and employment outcomes.

This project investigates the impact of wage increases at large employers in the United States. It will study the wages of other similarly skilled workers in the labor market exposed to one of these large employers in order to better understand how actions by firms, the government, and worker advocacy organizations influence wages in their local labor markets more broadly. This topic helps to contribute to our understanding of how to improve economic outcomes at the bottom of the earnings distribution. The research uses a difference-in-difference design and will compare outcomes for similarly skilled workers that are exposed versus not-exposed to one of the major employers when that employer changes its wage policy. They will use Burning Glass data to isolate spillovers from mechanical effects since they will be able to look at posted wages for employers that are not the ones changing their wage policy.

This research asks whether employers compensate workers for the implicit option of unpredictable and unstable schedules. It will use the National Longitudinal Survey of Youth, 1997 cohort, to analyze the labor market effects of unpredictable and unstable schedules. The project will focus on identifying marginal effects while controlling for observed and unobserved heterogeneity using fixed-effects or first-difference specifications.

How does the availability of job options outside workers’ own occupations affect their labor market outcomes? This project uses Burning Glass data to define labor markets by the probabilistic occupational transitions that workers make. The research looks at the likelihood that a worker switches occupations based on location and other job determinants. In addition, the researchers will study differences based on the industrial composition of a location, local labor market shocks, and race and gender analyses, thus deepening our understanding of workers’ outside options in regard to the impact of labor market concentration.

This research aims to empirically analyze potential explanations for gender wage gaps, glass ceilings, and differential labor market returns for women by looking at how gender gaps may be perpetuated within a firm. Using a dataset from a multinational firm employing 300,000 people that includes applications for promotions, as well as observed promotions, the project seeks to understand internal firm promotion processes that affect the gender wage gap over the career cycle.