Data, Insights and Blog Posts
Most of my current research draws on education data from Ethiopia's secondary education system, which is organized into two sequential levels. The first level, referred to as the General High School Program, comprises grades 9 and 10 and follows a general curriculum. Upon completion of the program, students are required to sit for a standardized General High School Exit Examination, also known as the Pre-College Admission Examination. Those who score above a nationally determined cutoff are admitted to the second level of secondary education—the Pre-College Program.
Read MoreEconomists increasingly rely on administrative data for research. However, because such data are typically collected for non-research purposes—or at least not with specific economics research in mind—they often lack crucial information, such as the cutoff scores used to determine eligibility for programs (e.g., benefit eligibility). Academic records, for example, frequently omit admission cutoff scores for academic programs. In these cases, researchers may infer the missing cutoff values from the data itself, particularly when detailed information is available on the outcomes of individuals whose participation depended on those cutoffs. When datasets are sufficiently rich and well structured, such methods can accurately recover the original cutoff criteria.
Read MoreThis paper studies how college admission selectivity affects the college field choice of students in a centralized, field-specific admission system. I leverage a college admission policy reform in Ethiopia that sharply increased the share of college seats in public universities allocated to STEM fields. The reform substantially decreased the admission selectivity of STEM fields. Using cohort analysis and a regression discontinuity design, I show that students are significantly more likely to choose STEM fields after the reform.
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