How can colleges find successful applicants? Criteria such as GPA, interviews, essays, and tests provide information about candidates, but which work and why? We shed light on these questions using unique data on the universe of objective and subjective rankings of all college applicants in...

How can colleges find successful applicants? Criteria such as GPA, interviews, essays, and tests provide information about candidates, but which work and why? We shed light on these questions using unique data on the universe of objective and subjective rankings of all college applicants in...

How can colleges find successful applicants? Criteria such as GPA, interviews, essays, and tests provide information about candidates, but which work and why? We shed light on these questions using unique data on the universe of objective and subjective rankings of all college applicants in...

This paper proposes a theory of education curriculum and analyzes its distributional impact on student learning outcomes. Different curricula represent horizontal differentiation in the education technology, thus a curriculum change has distributional effects across students. We test the model...

Many commonly used treatment effects estimators rely on the unconfoundedness assumption ("selection on observables") which is fundamentally non-testable. When evaluating the effects of labor market policies, researchers need to observe variables that affect both treatment participation and labor...

Many commonly used treatment effects estimators rely on the unconfoundedness assumption ("selection on observables") which is fundamentally non-testable. When evaluating the effects of labor market policies, researchers need to observe variables that affect both treatment participation and labor...

The econometrics literature proposed several new causal machine learning methods (CML) in the past few years. These methods harness the strength of machine learning methods to flexibly model the relationship between the treatment, outcome and confounders, while providing valid inferential...

In the canonical regression discontinuity (RD) design for applicants who face an award or admissions cutoff, causal effects are nonparametrically identified for those near the cutoff. The effect of treatment on inframarginal applicants is also of interest, but identification of such effects...

In the canonical regression discontinuity (RD) design for applicants who face an award or admissions cutoff, causal effects are nonparametrically identified for those near the cutoff. The effect of treatment on inframarginal applicants is also of interest, but identification of such effects...

A review of the measures of the stock of human capital used in empirical growth research reveals that human capital is mostly poorly proxied. The simple use of the most common proxy, average years of schooling of the working-age population, misspecifies the relationship between education and the...