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Abstract

This dissertation examines the impacts of public policy in the healthcare and education sectors. The first chapter examines a number of government policies that encourage successful charter networks to open new schools. However, there is little evidence on how quality changes within a network as it expands, and from a theoretical perspective, the direction of that change is ambiguous. I use student-level panel data from New York City to examine within-network changes in quality, and I find that charter networks are not able to maintain test-score value-added quality in expansion schools. Later schools in a network have lower quality, especially for English test score value-added. This decline increases in magnitude with a school's ordinal number in that network. In addition, I find that network value-added declines with a school's age, while quality for non-network charters improves with age. Last, I look into some mechanisms that could explain these trends, focusing on changes to the treatment group on the demand side and span of control issues on the supply side. Although I find heterogeneous returns to charter schools based on student demographics and prior test scores, I find no evidence that demographics or prior test scores changed in a way that could explain the patterns in quality that I observe. If anything, the prior test scores of incoming cohorts moved in a way that suggest I am underestimating the declines in quality with age. At the same time, I do not find any evidence that network declines in quality can be attributed to managers having increasing difficulty managing networks as they expand. The second chapter investigates the Center for Medicare and Medicaid Services' attempts to reduce the high number of unplanned hospital readmissions. As part of the Affordable Care Act, CMS introduced the Hospital Readmissions Reduction Program (HRRP) which fined hospitals for excessive risk-adjusted readmissions. After readmissions fell, CMS declared the program a success. However, the HRRP was criticized by some because hospitals which served more minorities and low-income patients were more likely to be fined. This led some to argue that demographics should be included in the readmission rate risk adjustment. However, it is unclear if patient demographics had a causal effect on readmission rates or if low-income and minority patients were just attending lower quality hospitals. In this chapter, I investigate both whether the HRRP has been effective and if the risk-adjustment calculations should be altered. To achieve the first goal, I use hospitals that were exempt from the program as a control group and uncover little evidence that the HRRP had much of an effect. In the years following the introduction of the program, the treatment and control hospitals saw nearly identical declines in readmission rates. To achieve my second goal, I identify ninety-nine hospital closings in the last eight years as an exogenous change to patient demographics at the closest neighboring hospital. I use difference-in-differences to first confirm that the closest hospital sees an increase in patients relative to the other nearby hospitals, and then determine if readmission rates changed based on the change in average patient demographics. I am unable to reject the null that the change in patient demographic mix had any effect on a hospital's readmission rates.

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