Work in Progress
Heuristic Self-Evaluation and the Returns to STEM (in revision, new draft coming soon)
older version: Learning from Round Test Scores: University Field Choices and Career Outcomes
Human capital decisions shape long-term outcomes, yet students often make them under uncertainty about their own ability. Admissions to high-earning STEM programs rely on test scores that are noisy signals of ability. This paper studies how heuristics and self-evaluation influence the decision to pursue such programs. Using linked administrative data, I implement a regression discontinuity at a round-number threshold on an initial university entrance test. Although the threshold has no official role in admissions, crossing it sharply increases applications to STEM, consistent with left-digit bias: students interpret a higher first digit as a signal of ability. Affected students retake the exam, improve their scores, and enroll in STEM. Over the next two decades, they are more likely to work in the technology sector, earn higher wages, and reach the upper tail of the earnings distribution. The findings show how misperceived ability can deter students from selective fields, generating persistent disparities in economic opportunity unrelated to actual talent.