Job Market Paper
Estimating Treatment Complementarity
How can we estimate the complementarity between two treatments when assignment is not fully random, such as in randomized experiments with imperfect compliance or in quasi-experimental settings? The first part of this paper shows that the commonly used two-stage least squares (2SLS)—with instruments for each treatment and their interaction—is often not suitable for estimating treatment interaction effects. Specifically, 2SLS requires strong assumptions about (1) treatment effect heterogeneity and (2) types of compliers. I show that these assumptions have testable implications on first stage patterns, and these often fail in published empirical studies on complementarity. The second part of the paper proposes an alternative estimation strategy for cases where these assumptions for 2SLS are unlikely to hold. Building on the marginal treatment effect literature, this approach models potential outcomes as a linear function of individuals’ unobserved resistance to treatment and offers a clearer connection to the intended estimand of treatment interaction. Lastly, the paper revisits Angelucci and Bennett (2024), an experimental study of complementarity under imperfect compliance, to illustrate how the proposed diagnostics and alternative estimator can enhance empirical analysis of interactions between two treatments.
Work in Progress
Effects of Work Requirements in Means-Tested Programs with Lexin Cai and Pauline Leung.
(Draft forthcoming pending Census Bureau disclosure review.) In this paper, we examine the effectiveness of work requirements as a screening device in the Supplemental Nutrition Assistance Program (SNAP), the main food assistance program in the United States. “Able-bodied adults without dependents” (ABAWDs) are subject to work requirements, but during the Great Recession these rules were broadly suspended and later reinstated at different times across counties and states throughout the 2010s. Using linked SNAP and LEHD administrative data from eight states, we exploit the age-50 eligibility cutoff and county-level waiver reinstatements in difference-in-differences and triple-differences designs to estimate the effects of reinstating work requirements. We find that reinstating work requirements reduces SNAP participation and benefits among ABAWDs. We do not find robust evidence that work requirements increase labor supply. Moreover, our results suggest that work requirements disproportionately screen out low-income individuals, suggesting worse program targeting.
Any views expressed are those of the authors and not those of the U.S. Census Bureau. The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data used to produce this product. This research was performed at a Federal Statistical Research Data Center under FSRDC Project Number 3049. (CBDRB-FY26-P3049-R12788).
New Data on War on Poverty Programs in the 1960s with Esra Kose, Henry Manley and Doug Miller.
We introduce a new data source on the War on Poverty programs from 1965-1969, using a collection of newly discovered and digitized Poverty Program Information (PPI) books. This grant-level data set has four primary contributions. First, it includes the name of each grant recipient, the type of program funded, and the amount of funding that was appropriated. Second, it indicates whether the grant coverage was nationwide, multiple state, individual county, or for multiple counties. Multiple county program listings provide information about the recipient counties by local agencies for the first time. Third, for several programs, it provides novel information on enrollment. Finally, it includes information on a new set of War on Poverty programs that have not been previously studied due to lack of data.
The Lifecycle Effects of War on Poverty Programs with Hilary Hoynes, Esra Kose, Henry Manley and Doug Miller.
Received U.S. Census Bureau approval for restricted-use data access.
Parental Gender Norms and College Major Choice with Chulhee Lee and Seojung Oh.
Why do women sort into “female” majors? This paper investigates whether parental gender norms affect a child’s choice of college major in Korea. As an index of parental son preference, we use the sex ratios at birth (SRB) in the parent’s province of birth that resulted from differential rates of sex-selective abortions across regions. We find that having fathers with more traditional gender norms tend to increase the probability of the daughters’ enrollment in a female-dominated major, such as education and home economics. However, this relationship is no longer found for recent cohorts who entered college after 2000. No significant effect is observed for sons, and only weak influence of maternal gender norms is found. We offer two possible explanations for the diminished influence of parental gender norms among the younger generations, namely, increasing labor-market disadvantage associated with female-dominated majors and convergence in parental preference on sons’ and daughters’ occupations. Our results show that conventional gender stereotype in Korea played a role in shaping segregated choice of major by gender through cultural transmission, and that its influence became weaker over time.
Publications
Economic costs of dementia in 11 countries in Europe: Estimates from nationally representative cohorts of a panel study with Erik Meijer, Maria Casanova, Ana Llena-Nozal, Jinkook Lee. The Lancet Regional Health – Europe (2022)