Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions
Résumé
We propose novel approaches to estimating student preferences with data from matching mechanisms, especially the Gale-Shapley Deferred Acceptance. Even if the mechanism is strategy-proof, assuming that students truthfully rank schools in applications may be restrictive. We show that when students are ranked strictly by some ex-ante known priority index (e.g., test scores), stability is a plausible and weaker assumption, implying that every student is matched with her favorite school/college among those she qualifies for ex post. The methods are illustrated in simulations and applied to school choice in Paris. We discuss when each approach is more appropriate in real-life settings.
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