2016-17 projects

This paper aims to evaluate recent changes in the U.S. education system, namely an influx in the number of charter schools, on the percent of racially segregated schools within our public school system. Conducting analysis at a school, district, and state level, it is first apparent that segregation in schools continues to be extant and disproportionately impacts certain regions. Our regression analysis, both at district and state levels using a non-delayed dataset and a time-delayed dataset, precludes us from confidently determining the increase in number of charter schools during our entire time frame of analysis, 2006 school year to the 2013 school year, causes a decrease in the percent of segregated schools. However, at a regional level controlling for year effects, it becomes apparent that certain states have experienced a decrease in the percent of segregated schools when comparing one school year to the first school year of study. While this study attempts to understand the effect of school choice on school segregation, it is evident further analysis will be needed to grasp this phenomenon.

Do non-white players in the National Football League suffer because of implicit racial discrimination by the League’s officials, the majority of whom are white? This paper looks at data from the National Football League over the most recent five seasons (2012-2016) to consider this question. Evidence of similar bias was previously found in the NBA by Price and Wolfers (2006) and in the MLB by Parsons, Sulaeman, Yates, and Hamermesh (2007). Considering 1,278 games over 5 seasons, this analysis finds statistically significant evidence for implicit bias by officials based on the racial composition of a team’s starting lineup. Testing indicates that teams with a fewer number of white players, and hence greater number of non-white players, in the starting lineup are called for fewer penalties both in terms of yardage and number of calls, providing evidence of implicit bias on the part of referees.

Under current redistricting practices, prisoners are counted where they are held rather than where they are from. Given the frequent and extensive movement of prisoners, who are not allowed to vote, how we count naturally affects whose representation counts. Using Census block data and electoral returns from state lower house elections, this study examines how partisan control of redistricting procedures can strategically distort voter representation at the ballot boxes by giving voters in some areas de facto “extra votes” from the phantom prison population counted in their district. The evidence suggests parties in control of redistricting will move prisons into swing districts to reduce the amount of campaigning need to tip the seat. While the substantive effects in the overall model are limited, a close examination of individual cases identifies numerous examples of partisan-motivated distortion through strategic prison allocation.

Opioid addiction is a crisis hitting every corner of the United States. Mortality rates from overdose are skyrocketing and addiction is spreading across the country. In this paper, I am testing if Substance Abuse and Mental Health Services Administration (SAMHSA) certified Opioid Treatment Programs (OTPs) are established based on the need for treatment, determined by overdose mortality rates, or for political motivations, determined by statewide party control. As the only option for Medication-Assisted Treatment, these Opioid Treatment Programs are crucial to the comprehensive fight against addiction. While this paper shows a correlation between need and number of programs, statewide poverty levels, political control and Good Samaritan policies also act as important indicators of treatment availability.

My QSS project examined whether people can infer someone's political affiliation based off their first name or other characteristics, such as what car a person drives or which beer someone prefers to drink.

This project studied the effect of multi-racial interaction in the student body and faculty at the school level at over four thousand institutions in the United States. By leveraging the expansiveness of the College Scorecard panel dataset and data-wrangling capabilities in R, the data indicated that diversity had a positive effect on completion and retention, but varied and sometimes negative effects on loan repayment and earnings.