In the past, migration was an important way Americans reacted to economic shocks. When one area was hit by a decline in labor demand, residents of the area could respond by moving to an area where demand for their labor was higher. But internal migration has been falling and may be a reason why incomes for most Americans have stagnated. In an era of low labor mobility, what determines who responds to the shock via migration? This research seeks to extend recent work that has studied the impact of the well-documented shock from increased Chinese imports on the mobility of affected workers across firms, industries, and local labor markets. The authors have access to rich census data that allows them to trace individuals over time and space, and to observe many variables that may affect the likelihood of an individual’s mobility response to the trade shock—for example, demographics, historical migration flows between locations, and presence of higher education opportunities. This project will look at the net mobility of each region, and also dig into the gross inflows and outflows to better understand the underlying mechanisms.

This project is an extension of the National Asset Scorecard for Communities of Color, or NASCC, a city-level analysis of wealth inequality. Previously, the research team surveyed five cities with large non-white populations with the aim of measuring household wealth at the level of detailed racial and ethnic categories. Specifically, this grant will support the second wave of the NASCC in Boston, which will be representative of subgroups of Asian households as well as the originally sampled groups from the previous wave. Findings will make an important contribution to the wealth inequality literature, going beyond the broad categories of “black” and “Hispanic” to provide more granular data on the economic situation of racial and ethnic groups in the Boston metropolitan area.

Recent research has clearly shown that the inequality of labor earnings, by itself, is not enough to explain the inequality of wealth. Utilizing a series of remarkable administrative records on the population of Norway from 1995 to 2015, where individuals are subject to both income and wealth taxation, this research seeks to fill a gap in our knowledge by addressing both our theoretical understanding of how wealth is accumulated and our empirical understanding of the distribution of wealth across individuals and households.

This research asks how gender inequality influences the number of chances that individuals receive to succeed in the workplace and whether this affects skill development and/ or contributes to wage and promotion gaps. Specifically, the research seeks to add to our understanding of how gender differences may affect whether an employee’s successes and failures are attributed to luck or ability, and if that has implications for career trajectory. The project uses a unique data set of primary care physicians’ referrals to surgeons.

Pervasive earnings losses are a well-documented feature of job displacement, yet the understanding of the sources of these earnings losses is limited. The decline could be due to a lower wage at a new job, a lower likelihood of finding a new job, working fewer hours, or the loss of firm-specific rents. This project proposes to take advantage of employer-employee matched administrative data from Washington state’s unemployment insurance program to better understand the sources of earnings losses and to analyze the role of employer characteristics in job losses. Obtaining a better diagnosis of the root causes behind the long-term earnings decline can lead to better-designed policy responses.

Through an intervention with a major U.S. retailer (The Gap), the project tests whether shifting hourly workers to more stable schedules results in cost savings and increased productivity for businesses. In the second year of work, Williams and her team continued to make progress, including broadening the intervention in three important ways: an increase in hours, which research shows can improve sales by adding staffing at peak hours; agreeing to consider sources of instability stemming from the supply chain; and adding a worker survey and focus groups to gather information on scheduling impacts, pre and post intervention, on workers’ and their families’ well-being.