Regression Discontinuity Analysis of Affirmative Action
Project Overview
Conducted doctoral research on the effects of affirmative action policies in Korea, developing and applying a regression discontinuity design with multiple assignment variables. This methodological innovation allowed for more precise estimation of policy impacts in complex institutional settings.
Methodology
Extended the traditional regression discontinuity design to accommodate multiple assignment variables, addressing a significant methodological gap in the literature. Collected and analyzed comprehensive data on educational outcomes before and after the implementation of affirmative action policies. Implemented robust statistical tests to validate the assumptions of the regression discontinuity approach.
Results
The analysis provided nuanced insights into the effects of affirmative action policies, identifying both intended and unintended consequences. The methodological contribution of handling multiple assignment variables enhanced the precision and reliability of the estimates.
Conclusion
This research made significant contributions to both the methodological literature on causal inference and the substantive understanding of affirmative action policies. The dissertation was recognized for its innovative approach to a complex policy evaluation challenge.
