Income-Based Affirmative Action in College Admissions

Abstract

We study whether college admissions should implement quotas for lower-income applicants. We develop an overlapping-generations model and calibrate it to data from Brazil, where such a policy is widely implemented. In our model, parents choose how much to invest in their child’s education, thereby increasing both human capital and likelihood of college admission. We find that, in the long run, the optimal income-based affirmative action increases welfare and aggregate output. It improves the pool of admitted students but distorts pre-college educational investments. The welfare-maximizing policy benefits lower- to middle-income applicants with income-based quotas, while higher-income applicants face fiercer competition in college admissions. The optimal policy reduces intergenerational persistence of earnings by 5.7% and makes nearly 80% of households better off.

Finding umbrella trees: cultivating inclusion and more than survival in a post-affirmative action academy

“…Upon deplaning in Accra, Ghana, at the start of an overdue vacation in late June 2023, I was greeted with the news that the US Supreme Court had, as expected, voted to ban the use of race-conscious affirmative action in college admissions ( Camera 2023 ; Maye 2023 ; Wood 2023 ). Of note, the decision carved out exceptions for military academies and legacy admissions, the former being highlighted by the dissenting justices as inconsistent and logically flawed ( Students for Fair Admissions Inc. vs. President and Fellows of Harvard College 2023 ; Students for Fair Admissions Inc. vs. University of North Carolina et al 2023 ).…”

Social Security Reforms, Retirement and Sectoral Decisions

“…An equivalent approach to modeling public exams in Brazil can be found inBrotherhood and Delalibera (2020) and inBrotherhood et al (2023).…”