Forecasting the Effect of Affirmative Action Policies in Undergraduate College Admissions (2018)

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Assessing affirmative action policies in undergraduate admissions procedures in the United States is important for ensuring educational equity. Specifically, racial affirmative action policies provide the opportunity for students to have the same access to higher education, regardless of racial/ethnic background. The goal of this thesis was to develop a method of predicting how the current (lack of) racial affirmative action policy at UC-Berkeley would effect the racial/ethnic representation of incoming classes over the next ten years. By using a Markov chain model and an ideal quantification of critical mass, our results indicate that students from different racial/ethnic backgrounds at UC-Berkeley are not accessing higher education at equal rates. Our results suggest that African-American students, Hispanic/Latino students, and White/Caucasian students are underrepresented, while Asian-American students are overrepresented.