In the first chapter, we investigate the relationship between student test scores and discipline outcomes in Texas public schools and whether or not schools participated in the Universal Free Breakfast Program (UFB). Eating a routine breakfast leads to increased physical and mental performance, as well as test scores. Surprisingly, there has been little focus on how eating a routine breakfast affects disruptive behaviors. We compile a panel data set from two administrative sources in Texas, spanning school years 2011/2012-2016/2107. Using fixed effects models, a staggered difference in differences model, and a fuzzy regression discontinuity design, we find that schools that offer UFB experience higher test scores and have reduced conflict outcomes such as fights, substance abuse, and truancy. These results suggest that the benefit schools receive from taking part in UFB are significant, help their students achieve better outcomes in schooling, behavior, general well-being, and increase funding from lower truancy rates.

In the second chapter, we investigate how the technique of hydraulic fracturing or "fracking", has made it possible to produce vast new quantities of oil and natural gas. States like Colorado, Texas, and Oklahoma have seen a dramatic increase in the number of wells for both oil and natural gas. In this study, the main source of exogenous variation to be explored is the location of oil and natural gas well sites over time, relative to home locations. We estimate the effect of hydraulically fractured natural gas and oil well sites on both urban and rural residential home prices between 2000 to 2018. The data stems from the U.S. Department of Homeland Security that lists locations of all oil and natural gas wells, and from Zillow's ZTRAX data base which contains home transaction and administrative data. ArcGis is used to create varying buffer zones sizes around well sites, exploring how average home prices changed before and after a well opens. First, a zip code level fixed effects model is used. Second, household level fixed effects models and repeat sales models are implemented. Lastly, a spatial differences in differences (SDID) approach is used. Our results show that homes within .5 mile of a well have a 2.9% increase in selling price and homes that are .5-1 mile from a well site see a 1.2% increase compared to homes that are more than 2 miles away.

In the third chapter, we are interested in flat rate tuition and how it has effected student registration behaviors and academic performance. The cost to attend college has risen drastically over the past decade. This sharp increase has caused universities to reevaluate tuition pricing schemes how they charge tuition in efforts to keep enrollments and revenue's high. There is growing interest in flat rate tuition (FRT) where tuition is based on 15 credit hours per term for students enrolled in 12-19 hours. Thus, the marginal cost for over 15 credit hours is effectively zero. This new tuition pricing system has two big impacts on the student body. First, it can alter the academic performance of students. Second it can alter their registered and attempted semester course loads. Using a linear probability model and fixed effects regression models, find that under FRT, students register for more classes, attempt more credit hours, and have higher semester, yearly, and graduation GPA's compared to students that paid per credit hour. Using a rich data set from the University of Oklahoma, we compare cohorts of students facing different tuition schemes: no FRT (or per credit hour tuition), 1, 2, or 3 years of FRT, and all years of FRT, from the Fall of 2008 to Spring of 2018.