“…While we estimate the school choice model (1) by assuming stable matching but not truth-telling, we can allow students to be truthful in order to study matching outcomes. This holds as long as preference estimates are consistent (Artemov et al 2023). We use the simulated rank-ordered 11 One potential caveat with our school choice framework is that it precludes applicants from reacting to (expected) policy-induced changes in peer composition across schools.…”
Section: The Impact Of Information Provision At Scalementioning
“…While we estimate the school choice model (1) by assuming stable matching but not truth-telling, we can allow students to be truthful in order to study matching outcomes. This holds as long as preference estimates are consistent (Artemov et al 2023). We use the simulated rank-ordered 11 One potential caveat with our school choice framework is that it precludes applicants from reacting to (expected) policy-induced changes in peer composition across schools.…”
Section: The Impact Of Information Provision At Scalementioning
“…That is, no college prefers to reject any of its currently matched students to vacate a seat, and no student prefers to leave her current match to become unmatched or matched with a college that is willing to accept her and, if necessary, reject one of its currently matched students. Stability is often imposed in the study of various matching markets (see, for a survey, Chiappori and Salanié (2016)) and is satisfied in equilibrium in our setting in certain game‐theoretical models (Artemov, Che, and He (2023), Fack, Grenet, and He (2019)).…”
Section: Introductionmentioning
confidence: 99%
“…Our setting contains one single matching game that changes with the market size. Proposition 3 of Azevedo and Leshno (2016), Proposition 4 of Fack, Grenet, and He (2019), and Corollary 2 of Artemov, Che, and He (2023) imply that, under certain conditions, the equilibrium outcome in the continuum approximates well an equilibrium outcome in a large finite market. Such an approximation is also used in the network literature (e.g., Menzel (2022)).…”
mentioning
confidence: 96%
“… Stability can be achieved in certain equilibrium if students apply to all acceptable colleges and if a stable mechanism, for example, the deferred acceptance (Gale and Shapley (1962)), is used to find the matching. Theoretically, provided that students know what criteria colleges use to rank them, stability can still be satisfied in equilibrium, even if students choose not to apply to all acceptable colleges due to application costs (Fack, Grenet, and He (2019)) or if students make certain application mistakes (Artemov, Che, and He (2023)). Importantly, achieving stability does not require the market to be centralized, as shown in laboratory experiments (see, e.g., Pais, Pintér, and Veszteg, 2020), and steps in mechanisms such as the deferred acceptance can be implemented in a decentralized fashion (Grenet, He, and Kübler (2022)). …”
In a setting of many‐to‐one two‐sided matching with nontransferable utilities, for example, college admissions, we study conditions under which preferences of both sides are identified with data on one single market. Regardless of whether the market is centralized or decentralized, assuming that the observed matching is stable, we show nonparametric identification of preferences of both sides under certain exclusion restrictions. To take our results to the data, we use Monte Carlo simulations to evaluate different estimators, including the ones that are directly constructed from the identification. We find that a parametric Bayesian approach with a Gibbs sampler works well in realistically sized problems. Finally, we illustrate our methodology in decentralized admissions to public and private schools in Chile and conduct a counterfactual analysis of an affirmative action policy.
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