Three Essays on the Impact of High School Mathematics Credits on Education and Labor Market Outcomes

Impact of high school math credits on education and labor market outcomes;Education;Social Sciences;Higher Ed & Economics PhD

Sosa Gonzalez, AlfredoBound, John ;

University of Michigan

关键词: Impact of high school math credits on education and labor market outcomes;    Education;    Social Sciences;    Higher Ed & Economics PhD;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/138736/asosa_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

This dissertation focuses on the role of high school mathematics credits on shaping college access and graduation as well as future earnings. In the first chapter, I exploit state and time variation in shocks to teachers;; labor supply to identify the effect of high school mathematics credits on education and labor market outcomes. The results indicate that, on average, each additional year of math increases yearly labor income by about 3%.Other results show that math credits during high school also increase the probability of college attendance and bachelors;; degree completion.In the second chapter, I estimate marginal treatment effects of advanced high school mathematics credits on total labor income at age 28. The results indicate that the average gain from obtaining advanced math credits during high school for a randomly selected individual is about 4%. For people who already enrolled in advanced math credits the gain from another year of math is smaller of about 2.45% whereas that for individuals who never obtained mathematics credits the potential increase is the highest of about 7.39%. To this date, this is the first study of marginal treatment effects in the literature of the impact of high school math credits on labor market outcomes.Finally, in the third chapter, I describe the process to obtain a national data set of state-sponsored financial incentives utilized to recruit and retain teachers in STEM fields. Between 1983 and 2016, 41 states implemented 87 unique financial programs aimed at increasing the supply of teachers, especially in shortage subject and geographic areas. The data generated in this chapter helped me to identify and estimate different program evaluation parameters such as the weighted Local Average Treatment Effect in chapter 1, and, in chapter 2, the Average Treatment Effect (ATE), the Average Treatment Effect on the Treated (TT), the Average Treatment Effect on the Untreated (TUT) and, the Marginal Treatment Effect (MTE).