2014
DOI: 10.1093/restud/rdu003
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Student Portfolios and the College Admissions Problem

Abstract: We develop a decentralized Bayesian model of college admissions with two ranked colleges, heterogeneous students and two realistic match frictions: students find it costly to apply to college, and college evaluations of their applications are uncertain. Students thus face a portfolio choice problem in their application decision, while colleges choose admissions standards that act like market-clearing prices. Enrollment at each college is affected by the standards at the other college through student portfolio … Show more

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Cited by 119 publications
(84 citation statements)
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“…Modeling search frictions in this simultaneous way appears in some equilibrium search models of price dispersion such as Burdett and Judd (1983); directed search models with one or multiple applications and ex ante identical firms such as Burdett, Shi, and Wright (2001) and Albrecht, Gautier, and Vroman (2006); as well as search problems with multiple applications and heterogeneous options such as Chade, Lewis, and Smith (2014) for college admissions, and Kircher (2009) and Galenianos and Kircher (2009) …”
Section: Simultaneous Searchmentioning
confidence: 99%
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“…Modeling search frictions in this simultaneous way appears in some equilibrium search models of price dispersion such as Burdett and Judd (1983); directed search models with one or multiple applications and ex ante identical firms such as Burdett, Shi, and Wright (2001) and Albrecht, Gautier, and Vroman (2006); as well as search problems with multiple applications and heterogeneous options such as Chade, Lewis, and Smith (2014) for college admissions, and Kircher (2009) and Galenianos and Kircher (2009) …”
Section: Simultaneous Searchmentioning
confidence: 99%
“…Gale and Shapley (1962) ignore the wealth of search and information frictions that afflict the sorting of students into colleges. Chade, Lewis, and Smith (2014) explore how students and colleges react to these frictions and what happens to sorting.…”
Section: Sorting With Signaling Costsmentioning
confidence: 99%
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“…All that remains is to show  satisfies (46), but that follows directly from (47) and (48) because they normalize  = 1 and  = 0. In fact, the weight on  is the probability a seller gets at least 2 buyers, and the weight on  is probability he gets just 1.…”
Section: Thementioning
confidence: 99%
“…Condition (ii) of the definition states that if a university has not reached its capacity then no researcher would be strictly better off by moving to that university. 5 One can think of the equilibrium as a result of an assignment procedure such as the one presented in Gale and Shapley (1962).…”
Section: Definition 1 (Feasible Allocation) a Feasible Allocation Ismentioning
confidence: 99%