This course analyzes the key role of education policy and human capital accumulation in reducing inequality and affecting labor market opportunities. The course is designed to equip students with program evaluation tools (using multiple regression analysis) to evaluate policy effectiveness. The policy applications in the course will focus on education policies implemented worldwide to reduce inequality and discrimination in education. During the last two classes, we will conclude the course by discussing the future of education policy using machine learning.
The course is designed with two objectives in mind. The first is to provide you with the ability to analyze critically the empirical studies done by others at a level sufficient to make intelligent decisions about how to use that analysis in the design of public policy. The second is to provide you with the skills necessary to perform empirical policy analysis on your own, to participate on a team involved in such an empirical analysis and to present your work in a convincing and clear way.
Also offered by the Graduate School of Education as A-142 and the Economics Department as 1078.