To make high-quality research more accessible and easier to explore.

Fields:
3 results ✕ Clear filters

The Benefits of College Athletic Success: An Application of the Propensity Score Design

The Review of Economics and Statistics 2017 99(1), 119-134
Spending on big-time college athletics is often justified on the grounds that athletic success attracts students and raises donations. We exploit data on bookmaker spreads to estimate the probability of winning each game for college football teams. We then condition on these probabilities using a propensity score design to estimate the effects of winning on donations, applications, and enrollment. The resulting estimates represent causal effects under the assumption that, conditional on bookmaker spreads, winning is uncorrelated with potential outcomes. We find that winning reduces acceptance rates and increases donations, applications, academic reputation, in-state enrollment, and incoming SAT scores.

Uber and Traffic Fatalities

The Review of Economics and Statistics 2026 108(2), 525-532
Previous studies of the effect of ridesharing on traffic fatalities have yielded inconsistent conclusions. We revisit this question using proprietary data from Uber measuring monthly rideshare activity at the Census tract level. We find a consistent negative effect of ridesharing on traffic fatalities, with impacts concentrated during nights and weekends. Our results imply that ridesharing has decreased U.S. traffic fatalities by 5.2% in areas where it operates. The annual life-saving benefits are $6.8 billion. Back-of-the-envelope calculations suggest that these benefits are of similar magnitude to producer surplus captured by Uber shareholders or consumer surplus captured by Uber riders.

The Effect of Health Insurance on Emergency Department Visits: Evidence from an Age-Based Eligibility Threshold

The Review of Economics and Statistics 2014 96(1), 189-195
Health insurance affects the rate at which individuals visit hospitals and emergency departments (EDs). We identify the causal effect of losing health insurance using a regression discontinuity design. We compare individuals just before and after their twenty third birthday, which insurers have used as a cutoff after which students are no longer eligible for their parents' health insurance: 1.5% of young adults lose their health insurance upon turning 23, and this transition leads to a 1.6% decrease in ED visits and a 0.8% decrease in hospital stays. We discuss why these estimates are larger than those observed among teenage populations.