ASSA 2026 Round-up: Day 2
Yesterday was the second day of the 2026 annual meeting of the Allied Social Science Associations, which is organized by the American Economic Association. The 3-day conference, held in Philadelphia this year, features hundreds of sessions covering a wide variety of economics and other social science research. This year, Equitable Growth’s grantee network, Steering Committee, and Research Advisory Board and their research are well-represented throughout the program, featured in many different sessions of the conference.
Below are lightly edited abstracts from some of the papers and presentations that caught the attention of Equitable Growth staff during the second day of this year’s conference, with links to the sessions in which the papers were presented.
Come back tomorrow morning for highlights from day three, and check out yesterday’s post for highlights from the first day.
Hiring Discrimination Against Transgender Job Applicants in the U.S. Labor Market
Emily Beam, University of Vermont; Ivy Stanton, University of Mannheim
Abstract: Discrimination against transgender individuals harms their well-being and contributes to lower incomes and higher poverty rates. Access to employment opportunities is a critical determinant of lifetime earnings and other outcomes, yet surveys document frequent discrimination against transgender individuals. While recent studies show hiring discrimination against transgender applicants, analyses examining intersections with gender and race remain limited, as does research on geographic variation, particularly given differences in state and local anti-trans policies. We conducted a correspondence study to measure discrimination against transgender applicants and examine how it varies with applicant gender and race. We submitted roughly 5,600 resumes for entry-level jobs in food and retail sectors across 49 markets in 2023–2024. We signaled gender identity and race through names, pronouns, and statements about differently gendered legal names to indicate transgender identity. We measured differences in callback rate between cisgender and transgender applicants and examined results by gender identity (cisgender and transgender women and men, as well as nonbinary applicants) and race (Black vs. White applicants). Additionally, we tested for heterogeneity between more and less trans-friendly states, using data on recently introduced or passed state-level anti-trans legislation. This research provides large-scale experimental evidence on how gender identity, race, geography, and policy environments intersect in labor market discrimination. The results identify which demographic groups and geographic areas face the most severe employment discrimination, informing targeted policy interventions to protect transgender job-seekers.
Race, Ethnicity, and Nonpayment of Unemployment Insurance: The Role of the Employer
Marta Lachowska, Institute for Employment Research; Stephen A. Woodbury, Michigan State University
Abstract: This study examines whether Unemployment Insurance claimants who are Black, Hispanic, or Asian are more likely than White claimants to have their claims disputed by an employer or ultimately denied by the UI agency—issues that are central to ongoing concerns about equity in access to UI benefits. Using UI administrative wage and claim records from Washington state from 2005 to 2013, we estimate the extent to which differences in claim disputes and denials across racial and ethnic groups can be explained by observable differences in worker characteristics, claim characteristics (such as conditions of job separation), and employer behavior. Our primary interest is in the role employers play in these outcomes. We estimate linear probability models of dispute or denial, including indicators for race and ethnicity, characteristics of the claimant and the claim, and a leave-one-out measure of the employer’s average dispute or denial rate. We first apply the decomposition method developed by Gelbach (2016) to quantify the importance of differences in claimant characteristics versus employer behavior. We condition on employer-specific dispute and denial rates to assess whether workers of different racial and ethnic backgrounds systematically sort across employers. Second, we conduct a “switcher” analysis of workers with multiple UI claims filed with different employers, which isolates the influence of employer behavior on disputes and denials. In particular, we examine whether the impact of an employer’s probability of disputing a claim varies with the worker’s race or ethnicity. We also examine whether differences by race and ethnicity in employer-dispute rates ultimately lead to differences in UI denial rates or whether the UI agency is able to mitigate the effects of employer behavior. We conclude by discussing the implications of employer-driven disparities for the functioning of the UI system.
This research was funded in part by Equitable Growth.
The “Great Reshuffling” and Entrepreneurship
Matthew Denes, Carnegie Mellon University; Spyridon Lagaras, University of Illinois; Margarita Tsoutsoura, Washington University in St. Louis
Abstract: The COVID-19 pandemic accelerated a paradigm shift in labor markets toward nontraditional employment arrangements, with flexibility increasingly developing into a critical differentiating factor. We study the impact of the “Great Reshuffling” on transitions into entrepreneurship using administrative data from U.S. tax returns. We find a large increase in entry to entrepreneurship, particularly for women and women with dependents. We examine the role of child care disruptions, remote-work availability, and displacement, finding support in favor of the pandemic-driven increase in child care responsibilities as a primary factor. We show that transitions are persistent and lead to higher income for women. The pandemic shifted the composition of firms in the economy toward digital retail stores. Firms started by women survive more and have higher profitability. Overall, the results indicate that the pandemic shifted individuals’ preferences toward work.
This research was funded in part by Equitable Growth.
Monopolizing Minds: How M&As Stifle Innovation Through Labor Market Power
Alex Xi He, University of Maryland; Jing Xue, Georgia State University
Abstract: This paper argues that mergers and acquisitions reduce inventors’ innovation incentives and outputs by increasing firms’ labor market power and limiting the rents inventors can capture. We test this mechanism using individual-level longitudinal data from the U.S. Census Bureau. We find that, at both target and acquiring firms, inventors exposed to greater increases in labor market concentration—particularly in already-concentrated markets—produce fewer patents, earn lower wages, and exhibit reduced job mobility following mergers. In aggregate, the negative impact of increased labor market power on inventor productivity outweighs the potential benefits from innovation synergies. Overall, our findings highlight the critical role of labor market dynamics and inventor incentives in evaluating the innovation consequences of mergers and aquisitions.
Artificial Intelligence and the Labor Market
Menaka Hampole, Yale University; Dimitris Papanikolaou, Northwestern University; Lawrence D.W. Schmidt, Massachusetts Institute of Technology; Bryan Seegmiller, Northwestern University
Abstract: We leverage recent advances in natural language processing to construct measures of workers’ task exposure to AI and machine learning technologies over the 2010 to 2023 period, varying across firms and time. Using a theoretical framework that allows labor-saving technology to affect worker productivity both directly and indirectly, we show that the impact on wage earnings and employment can be summarized by two statistics. First, labor demand decreases in the average exposure of workers’ tasks to AI technologies. Second, holding the average exposure constant, labor demand increases in the dispersion of task exposures to AI as workers shift effort to tasks not displaced by AI. Exploiting exogenous variation in our measures based on preexisting hiring practices across firms, we find empirical support for these predictions, together with a lower demand for skills affected by AI. Overall, we find muted effects of AI on employment due to offsetting effects: Occupations highly exposed to AI experience relatively lower demand compared to less exposed occupations, but the resulting increase in firm productivity increases overall employment across all occupations.
Gender, Race, and Online Platform Work in the U.S.: An Intersectional Analysis
Rachel Marie Brooks Atkins, St. John’s University; Quentin Brummet, NORC University of Chicago; Katie Johnson, NORC University of Chicago
Abstract: This study uses data from the Entrepreneurship in the Population Survey to measure the prevalence, earnings, and motivations for online platform work by race, gender, and their intersection. Though online platform work represents an important segment of the labor market, prior studies often fail to adequately capture its demographic nuances. Our analysis reveals gender and racial disparities in prevalence of online platform work. Earnings data show significant disparities, with women and racial minorities disproportionately concentrated in lower-income categories. White men dominate higher-earning brackets. Motivations for platform work also vary. Women frequently cite flexibility and a desire to supplement pay. Black workers pursue platform work for their primary source of income and to fulfill their entrepreneurial ambitions, while Hispanic workers emphasize career transitions and autonomy. This analysis also investigates the intersectional nature of labor market participation in the gig economy and suggest that the structural inequalities of traditional employment are mirrored, and in some cases amplified, in online platform work. Policymakers and researchers must address these disparities to ensure equity in the evolving digital labor market.
Michelle Holder, City University of New York
Abstract: The economic recovery in the United States after the onslaught of the COVID-19 pandemic included considerable job growth in the transportation and warehousing industrial sector: This sector gained 838,000 jobs on an annualized basis from 2019 to 2023, accounting for nearly 1 in 4 jobs added after the economy regained the total number of jobs lost during the pandemic. While the U.S. economy experienced strong job growth through 2024, the industrial mix of jobs changed after 2019; the number of jobs in transportation and warehousing grew by 11 percent from 2019 to 2023, while employment in sectors such as leisure and hospitality and retail sales remained below their pre-pandemic levels during the same time period. Given employment growth in transportation and warehousing, as well as the representation of Black workers in this sector, this research seeks to address the following three questions: Did the pandemic spur the creation of jobs in the transportation and warehousing sector jobs that benefitted Black workers, particularly those who do not possess a college degree? Did Black women benefit from this sector’s job growth, and, if not, why not? Were the jobs being created in transportation and warehousing “good” jobs, defined in this research as offering compensation that was not predominantly low-wage, as well as providing health insurance benefits, fair working conditions and full-time employment?
Effects of Fair Workweek Laws on Labor Market Outcomes
Joseph Pickens, United States Naval Academy; Aaron Sojourner, W. E. Upjohn Institute for Employment Research
Abstract: This paper models Fair Workweek regulations that require employers to provide employees with schedule predictability (via advance notice of their work schedule and premium payments for short-notice changes) and access to hours (meaning they must offer open hours to existing employees before hiring new workers). We develop a theoretical model of employers’ responses to these provisions and their implications for employment. Guided by the model, we estimate the effects of a recently adopted Fair Workweek regulation in New York City’s fast-food sector using a synthetic difference-in-differences design. We find a null effect.
Yongjoon Park, University of Massachusetts-Amherst; Yichen Christy Zhou, Clemson University; Joshua Linn, University of Maryland
Abstract: It is becoming increasingly common to package environmental policies with industrial policies that promote domestic manufacturing, businesses, and jobs. Recent examples include the Inflation Reduction Act’s electric vehicle tax credits in the United States and the Green Deal Industrial Policy in the European Union. These policies intend to “kill two birds with one stone,” yet these two goals may not necessarily align. This study examines whether the dual objectives of EV subsidies in the IRA—reducing greenhouse gas emissions and boosting domestic vehicle production—exhibit synergies or create conflicts. Whether these goals are complementary or create trade-offs, and whether these subsidies are efficient, crucially depends on what eligible electric vehicles replace, particularly how consumers substitute between eligible electric cars and other vehicles (e.g., other energy/fuel-efficient electric vehicles, domestically produced gasoline vehicles). To provide useful policy implications, it is crucial to obtain accurate estimates of the substitution patterns between products for the consumer. Therefore, we estimate a structural model of new vehicle demand and supply in the United States while incorporating information on production location, which we then use to simulate policy counterfactuals.
Preschool as Child Care: Head Start Duration Expansions and Maternal Employment
Chloe Gibbs, University of Notre Dame; Esra Kose, University of California, Merced; Maria Rosales-Rueda, University of Delaware
Abstract: Early childhood care and education settings serve two purposes simultaneously: supporting children’s development and early learning and facilitating parents’ gainful activities. We examine how access to full-day Head Start programs affects maternal labor supply, leveraging a recent funding eligibility rule that expanded the duration of Head Start programs. In 2016, the U.S. Department of Health and Human Services announced the availability of supplemental funds to extend the duration of Head Start programming. Head Start grantees serving fewer than 40 percent of their center-based slots for a full school day and full school year were eligible to apply. Our analysis leverages this policy threshold and combines data on Head Start enrollment and center locations with parents’ employment data from the annual American Community Survey from 2008 to 2020. We first demonstrate that the 2016 funding availability significantly increased full-time Head Start enrollment. Next, using variation in access to full-day Head Start across place and time, we find that single mothers of preschool-aged children increase their labor force participation and work more hours per week. Our findings provide new evidence on the broader effects of early childhood investments on mothers’ economic opportunities.
One Giant Leap: Emancipation and Aggregate Economic Gains
Richard Hornbeck, University of Chicago; Trevon Logan, Ohio State University
Abstract: We characterize American slavery as inefficient, whereby emancipation generated substantial aggregate economic gains. Coercion distorted labor markets, raising the marginal cost of labor substantially above its marginal benefit. Production came at immense costs imposed on enslaved people that reduced aggregate economic surplus (the total value of output minus total costs incurred). Costs of enslavement are inherently difficult to quantify, which leads to a wide range of quantitative estimates from this conceptual shift, but we calculate that emancipation generated aggregate economic gains worth a 4 percent to 35 percent increase in U.S. aggregate productivity (or worth 7–60 years of technological innovation). Emancipation decreased output but decreased costs substantially more, illustrating the substantial potential for aggregate economic gains in the presence of severe sectoral misallocation.
State Tax Policy, Health Outcomes, and Racial Animus
Krista Ruffini, Georgetown University; Bradley L. Hardy, Georgetown University
Abstract: The United States is a federal system in which federal, state, and local governments share responsibilities for raising tax revenue and investing in public goods. This decentralized system means that states have considerable autonomy in determining how to structure their revenue base in progressivity and levels and what types of goods and services (and for whom) to spend this revenue on. At the same time, there is substantial variation in health outcomes across states, and, within states, Black individuals tend to have worse average health outcomes than non-Hispanic White individuals, even after accounting for factors such as socioeconomic status. Despite substantial cross-state variation in both the availability of public goods and the progressivity of state tax systems, there is relatively little work examining how these state level decisions shape child health and health inequities by race and ethnicity. This paper fills this gap in knowledge by providing some of the first evidence describing the relationship between state taxes, public goods, and child health. We explore measures of health separately by race and ethnicity in order to explore the extent to which tax and transfer policies shape health inequities. We find that more progressive tax systems at the state level are also associated with more robust state safety nets. Tax and transfer policies that serve lower-income households are also associated with better infant health along multiple dimensions and lower racial health inequities.
