Capital gains are one of the largest components of income at the top of the wealth distribution and play a key role in measuring wealth inequality. Yet capital gains are rarely included in estimates of the wealth distribution in economics, mainly because measurement requires detailed information on the distribution of wealth at the individual security level.
This project will construct a new dataset to directly measure the holdings of public equities and fixed-income assets for all individuals in the United States using internal IRS data from the 1099-DIV and 1099-INT forms, which have not previously been used by researchers. This improved data will allow for more accurate estimates of wealth inequality, including new estimates of top-end wealth inequality. It will also shed light on savings rates across the income distribution and bring to bear new evidence of whether the rich save more.
Many social insurance programs replace some percentage of prior earnings while a claimant is away from work during a shock, such as unemployment, disability, or the birth of a child. Implementation relies on “base periods” from which prior earnings are measured in order to establish the wage replacement rate. This project will explore the base period and its implications for a large subset of primarily low-income program recipients. Focusing on California’s Unemployment Insurance program and combining three administrative datasets, this researcher seeks to explain how earnings volatility, among other factors, can impact the value of Unemployment Insurance and claimant experience with the program. Other research shows that low-income workers experience significant volatility in earnings, partially due to a lack of control over how many hours of work they are given. Understanding how income volatility in the base period impacts subsequent volatility/income decline while receiving benefits is an important policy question.
Prior research suggests that concentration and firm mark-ups have increased in the United States over the past several decades, potentially resulting in a higher share of income going to capital instead of labor. These previous multi-industry studies have not addressed why concentration and mark-ups may have increased, and how policies, such as greater antitrust enforcement or merger review, could alter these trends.
This project aims to contribute to these unanswered questions by focusing on an industry-specific analysis. Utilizing cement industry data from the United States between 1973 and 2019, the authors will explore how technological change sparked by the introduction of the precalciner kiln altered market structure and the changes in the share of income going to owners’ profits relative to workers’ wages over time.
A clearer picture of U.S. intergenerational mobility is emerging for the latter part of the 20th century, but the same is not true for earlier in the century. This project is a massive data undertaking that will produce a database of mobility rates going back to 1900. Previous work, most notably the American Opportunity Study, links U.S. Census Decennials from 1940–2000.
This project makes some important extensions. It will expand the feasible linkages back to 1900 so that the panel spans the entire 20th century. Perhaps the most important contribution is the use of the Social Security Numerical Identification Files, or SS-5s, which contain information obtained from the application for a Social Security card for more than 40 million individuals who died prior to 2007 and include substantially more information on individuals than U.S. Census records, increasing the number of linkages and the quality of those linkages. In particular, the wealth of information in a single record is vastly superior to a Census-to-Census linking process and will better facilitate linkages within families, including for married women who have changed their names, improving the representation of women and racial and ethnic minorities. This will allow the researchers to study differences across space (states), as well as differences by race and gender.
This project will provide estimates of the impact of prospective merger reviews on antitrust enforcement actions, product prices, input prices, output, investment, and research and development. Using administrative data collected through taxation, employment, and antitrust provision, the project exploits the introduction of a premerger notification policy in Chile to see how it changed the types of mergers being agreed to.
The result will help policymakers understand how much notification systems have a deterrent impact. Prospective merger reviews constitute a large share of antitrust enforcement expenditures, and yet little work has systematically studied its effectiveness. By providing a comprehensive study across industries using detailed data on real economic variables, this project could provide invaluable insights into the effects of mergers in both input and output markets, the impact of notification requirements, and the resource allocation within enforcement agencies.
This project will examine how Unemployment Insurance policies interact with job search behavior in dual-earner households in the United States. More specifically, the researcher will explore the impacts of an expansion of Unemployment Insurance to include workers who leave their jobs due to their spouse getting a job that requires relocation. Using the National Longitudinal Survey of Youth from 1979 and 1997, and the Survey of Income and Program Participation from 2008, this study will seek to explain how and if access to Unemployment Insurance influences whether households will migrate long distances and attempts to measure if access to Unemployment Insurance is associated with higher wages after the household moves. The findings have the potential to inform our understanding of the gender wealth gap and women’s labor force participation, as well as geographic mobility, which has been declining in recent decades.
This project will use surveys to assess the role customers play as a source of power for U.S. workers who strike or protest working conditions, as well as the effects of different aspects of job quality on the likelihood of workers to leave a current job. The coronavirus pandemic is providing a laboratory for examining how the salience of these issues affect workers’ views of their jobs and their willingness to work under conditions of varying risk.
The first survey will use experiments embedded in a Facebook-based convenience sample to target food workers broadly, with a focus on W-2 employees at meat processing facilities, grocery stores, restaurants, and platform-based food delivery workers, including but not limited to Instacart. The second will survey a nationally representative sample of the full U.S. population in order to assess changing food consumption habits, as well as perceptions of food workers and collective action during the pandemic. This timely research promises to bring worker views into the public discussion of quality jobs, including welfare and safety, and will shed light on how workers and customers are intertwined in workplace issues of the day.
This study will provide a much-needed window into the sorts of labor processes that are coming to dominate an increasingly important industry: package delivery. It will examine how workers experience new technological and outsourcing practices. It will focus on new technologies in three categories—communication and monitoring, algorithmic planning and management, and the surveillance of delivery by customers—that are used to manage workers and how workers respond to these technologies in the context of outsourcing.
This large qualitative project involves 2 years of ethnography and 100 interviews. It will provide ethnographic insights into Amazon.com, Inc. delivery workers, in particular women, workers of color, and immigrants—all of whom will be a particular focus of the interviews. This research will be a valuable contribution, given the lack of attention by researchers on this burgeoning and quickly changing segment of the industry.
This study focuses on place-based policies and how geographic concentration of innovation affects regional economic growth in the United States. The researchers will explore how local fiscal stimulus in the form of defense spending impacts both innovation and economic growth. Using contract-level data on defense spending and county-level measures of innovation, the researchers will attempt to identify through which channels defense spending affects aggregate innovation. They use Gross Domestic Product, personal income, and total employment to evaluate how defense spending affects economic growth.
This project explores whether, as an empirical matter, people have constrained choice sets in energy consumption due to where they live, and if that, in turn, may mean that traditional models of the efficiency of carbon taxation are incorrect. The researcher will decompose the spatial heterogeneity in carbon emissions into a component driven by individual preferences and a component driven by place. Using U.S. Census data, the American Community Survey, and the Longitudinal Employer-Household Dynamics, among other data sources, the author explores how factors such as climate, income inequality, segregation, and public disinvestment impact place-based heterogeneity. Since so much emission heterogeneity is tied to income, there are clear implications for how this could impact and be impacted by inequality. Findings have the potential to inform our understanding of how carbon taxes may need to be accompanied by rezoning or other policies.
