Leveraging Uncertainties to Infer Preferences: Robust Analysis of School Choice

• DOI: 10.48550/arxiv.2309.14297
• Publication Date: 2023-01-01
• Authors: Yeon‐Koo Che; Dong Woo Hahm; Yinghua He
• Keywords: Desegregation; Revealed preference; School Choice; Stochastic game

Inferring applicant preferences is fundamental in many analyses of school-choice data. Application mistakes make this task challenging. We propose a novel approach to deal with the deferred-acceptance matching environment. The key insight that uncertainties faced by applicants, e.g., due tie-breaking lotteries, render some costly, allowing us reliably infer relevant preferences. Our extracts all information on robustly payoff-insignificant mistakes. apply it data from Staten Island, NYC. Counterfactual analysis suggests we underestimate effects proposed desegregation reforms when applicants' are not accounted for preference inference and estimation.