Research

Working Papers

Impact of Medicaid Dental Benefits on Maternal and Child Health
with Qian X, Bruckner T, Manski R, Lipton B

Despite elevated risks for oral health problems, more than half of pregnant women do not visit the dentist at least once during pregnancy. The Medicaid program covers more than 40% of US births and represents an important source of dental coverage with benefits that vary at the state level. We examine the effects of state-level pregnancy dental benefits using a difference-in-differences strategy and data from the 2012-2019 Pregnancy Risk Assessment and Monitoring System (PRAMS). We find that providing dental coverage to pregnant Medicaid recipients increases dental cleaning rates by 7.16 percentage points, or 29% relative to baseline. We also examine linked birth certificate data given evidence that poor oral health during pregnancy is associated with adverse pregnancy and birth outcomes. We find suggestive evidence of reductions in small for gestational age, preterm birth, and very low birthweight, though only the estimates for small for gestational age and very low birthweight are statistically significant at conventional levels. These findings underscore the importance of expanding access to preventive dental care during pregnancy as a strategy for improving long-term population health.

Impact of Medicaid Dental Coverage Expansion on Dental Care Utilization and Smoking Behavior Among Reproductive-Age Women

with Qian X, Bruckner T, Manski R, Lipton B

Dental care utilization among reproductive-age women not only affects their oral and overall health but also influences other health behaviors, with potential intergenerational implications. This study examines the effects of Medicaid dental coverage expansion for non-pregnant adults on dental care utilization and behavioral outcomes among reproductive-age women (21-44 years old) using data from the Behavioral Risk Factor Surveillance System (2000-2022). Exploiting state-level variations in dental benefit policies, we employ a difference-in-differences strategy to estimate the impact of expanded coverage. Our findings indicate that Medicaid dental benefit expansions increase the likelihood of dental care utilization by 4.8 percentage points, an 8.6% increase from the baseline rate. However, we also find evidence of potential moral hazard, as expanded coverage is associated with higher probabilities of smoking initiation and frequent smoking.

Policy Implications of Hearing Aid Coverage in Medicaid Managed Care Plans

with Tonti L, Arnold M, Lipton B

The Effect of Paid Sick Leave Mandates on Social Security Disability Claims

with Qian X, Dave D, Kim J, Lipton B, Sabia J

Impact of Telehealth Policy Expansion on Suicide Rates and Substance Use Treatment

with Masoumirad M

Striking the Balance: Human Discretion and Algorithmic Insights in Parole Supervision Decision-Making
with Nicholas Powell
Updated: May 2023

In this paper, we examine the interplay between predictive algorithms and hu- man discretion in determining parole supervision levels. Adopting a method- ological approach centered on the random assignment of parole officers at spe- cific risk score thresholds—particularly at junctures where parolees transition between various supervision levels—we investigate the impact of officers’ deci- sions to deviate from algorithmic recommendations on recidivism rates. Our findings reveal that professional adjustments to higher supervision levels consis- tently lead to reduced recidivism rates, while adjustments to lower supervision levels don’t display a significant effect. This underscores the pivotal role of strategic resource allocation in parole supervision, indicating that harsh over- rides can be resource-optimal in effectively lowering recidivism. Conversely, lenient overrides maintain stable recidivism rates without necessitating inten- sified supervision. Additionally, the study contributes to the ongoing discourse on the role of human intervention in algorithmic recommendations within the criminal justice system.

Discrimination and Constraints: Evidence from The Voice
Updated: November 2022

Gender discrimination in the hiring process is one significant factor contributing to labor market disparities. However, there is little evidence on the extent to which gender bias by hiring managers is responsible for these disparities. In this paper, I exploit a unique dataset of blind auditions of The Voice television show as an experiment to identify own-gender bias in the selection process. The  first televised stage audition, in which four noteworthy recording artists are coaches, listens to the contestants “blindly” (chairs facing away from the stage) to avoid seeing the contestant. Using a difference-in-differences estimation strategy, a coach (hiring person) is demonstrably exogenous with respect to the artist’s gender, I  find that artists are 4.5 percentage points (11 percent) more likely to be selected when they are the recipients of an opposite-gender coach. I also utilize the machine-learning approach in Athey et al. (2018) to include heterogeneity from team gender composition, order of performance, and failure rates of the coaches. The  findings of offer a new perspective to enrich past research on gender discrimination, shedding light on the instances of gender bias variation by the gender of the decision maker and team gender composition.