UC Santa Cruz

This dissertation focuses on using causal inference techniques to assess the impact that public policies have on health outcomes, and the behavioral response of consumers and firms to consumer information. In two of the three chapters of this dissertation, I rely on quasi-experimental variation, namely regression discontinuity designs, to find causal estimates of the determinants of health and the behavioral responses to public health policies and ratings systems.

The first chapter examines the behavioral responses of patients and hospitals to public information disclosure about hospital quality. Specifically, I analyze the assignment of letter grades to hospitals by the non-profit consortium known as the Leapfrog Group. Letter grades are assigned based on sharp cutoffs of a continuous score, so I implement a regression discontinuity design which provides causal estimates of whether patients sort into hospitals with a better grade and if lower-rated hospitals improve quality relative to higher-rated hospitals in order to achieve a higher grade in the next period. Using inpatient discharge records from 7 states, I find evidence that lower-rated hospitals reduce their rate of healthcare-associated infections and patients sort into hospitals that receive the highest grade. These responses occur nearly entirely in competitive hospital markets where patients have more choice and hospitals have a higher incentive to improve, and in large hospitals, where hospitals have a higher capacity to improve.

The second chapter exploits two compulsory schooling reforms in England to find estimates of the causal effect of education on health. We use a regression discontinuity design to compare individuals that were just barely subject or not subject to the reforms, and examine the differences in their long term health outcomes. Using hospital records from the National Health Service of England, we do not find any causal effect of an additional year of high school education on mortality or morbidity.

The third chapter analyzes the effect of one of the largest public health interventions in the United States, the artificial fluoridation of community water systems, on dental health, general health, and education. In this chapter, I merge several surveys and administrative data sets to obtain a rich set of controls, a fixed effects model to examine the effect of fluoride on educational achievement, and non-parametric specifications to assess how fluoride affects dental health at different levels of health and fluoride levels. I find consistent evidence that fluoridated water has a significant impact on the prevention of dental cavities in baby teeth, but no robust effect on permanent teeth or on general health or educational attainment. I do find however that fluoridated water significantly increases mild or severe cases of fluorosis.