Essays in Labor and Public Economics

Abstract

In this dissertation, I use tools from labor and public economics to study the effectiveness of policies aimed at improving access to public goods and services and how the benefits of these policies are distributed across key decision-makers and recipients. In the first essay, joint with Shreya Tandon, we estimate the causal effects of new primary care physician arrivals to underserved areas on net physician supply, healthcare utilization, and health outcomes of local residents using quasi-random variation in the timing of physician placements through the National Health Service Corps (NHSC) program. Our primary data include the roster of NHSC physician recipients and a sample of Medicare claims from 1999--2019. We find that physician arrivals increase overall primary care supply. Half of the non-inpatient healthcare provided by new entrants would have been satisfied by the incumbent primary care physicians, while the other half constitutes an increase in overall utilization. The additional utilization is concentrated in more advanced preventive care services, such as advanced testing and imaging. We also find an overall increase in elective inpatient procedures, particularly related to cardiovascular diagnoses. The greater healthcare utilization is associated with significant reductions in emergency hospitalizations and mortality. Health improvements persist for at least four years following physician arrival and are particularly pronounced for beneficiaries with chronic conditions and those living in more disadvantaged and rural locations. In the second essay, joint with Leonardo D'Amico, we examine how a persistent change in mortgage rates affects city growth, home prices and construction, and household formation. We study the revolutions in mortgage financing that took place in the U.S. between 1933 and 1940, which created a national mortgage market and allowed mortgage capital to move from the financial centers to the rest of the country. By digitizing city-level census data and a new sample of loan-level data, we show that differences in mortgage rates across cities went from nearly 300 basis points to just over 100 in only six years. This national mortgage market allowed initially capital-scarce places to grow more than initially capital-abundant ones. In the decades following the housing policies, cities where mortgage rates declined more as a result of the integration of mortgage markets saw higher growth in rates of homeownership, population, and housing construction. House prices moved only modestly, suggesting that, in 1940--50, housing supply responded robustly to higher demand for homes. These macro-level policies also influenced intra-household decision-making: we find that women who experienced lower mortgage interest rates during their childbearing years had more children. In the third essay, joint with Will Dobbie and Crystal Yang, we study a common feature of policies that deploy predictive algorithms in high-stakes settings: despite the availability of algorithmic recommendations, human decision-makers are typically kept in the loop and can exercise discretion to override them. We ask whether these discretionary overrides add valuable private information or merely reintroduce human biases and mistakes, in the context of bail decisions. We develop new quasi-experimental tools to measure the impact of human discretion over an algorithm on the accuracy of decisions, even when the outcome of interest is only selectively observed. We find that 90 percent of the judges in our setting underperform the algorithm when they make a discretionary override, with most making override decisions that are no better than random. Yet the remaining 10 percent of judges outperform the algorithm in terms of both accuracy and fairness when they make a discretionary override. We provide suggestive evidence on the behavior underlying these differences in judge performance, showing that the high-performing judges are more likely to use relevant private information and are less likely to overreact to highly salient events compared to the low-performing judges.