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Search and Matching in Education Markets

Paper Session

Friday, Jan. 3, 2020 10:15 AM - 12:15 PM (PDT)

Marriott Marquis, Rancho Santa Fe 2
Hosted By: American Economic Association
  • Chair: Eric Budish, University of Chicago

Simultaneous Search: Beyond Independent Successes

Ran Shorrer
,
Pennsylvania State University

Abstract

A key decision commonly faced by students is how to optimally choose their portfolio of college applications. Students are often advised to apply to a combination of "reach," "match," and "safety" schools. Empirically, when reductions in the cost of application permit students to apply to more schools, they expand the range of selectivity of schools to which they apply both upwards and downwards. However, this ubiquitous practice of diversification is difficult to reconcile with existing theoretical analyses of search decisions. To solve this, I develop a generalized framework for simultaneous search problems in which students' optimal behavior generates these patterns. My framework generates many predictions that are consistent with empirical findings on school choice. The important departure that I make from existing models is that colleges' admissions decisions are not independent.

Search Costs, Biased Beliefs and School Choice under Endogenous Consideration Sets

Christopher Neilson
,
Princeton University
Claudia Allende
,
Columbia University
Patrick Agte
,
Princeton University
Adam Kapor
,
Princeton University

Abstract

We develop a model of sequential search where families add schools to their consideration set endogenously depending on the expected benefits of search and the cost of search. We examine how school consideration
sets are endogenously developed as a function of how preferences and search costs interact with biased beliefs about the distribution of school characteristics. To inform this question, we survey a panel of families that will eventually have a child starting school and measure the evolution of the set of schools that they know of. We follow these families through the search process that leads them to make choices over schools. To distinguish between potentially biased beliefs about the expected benefits of search and the search costs, we use the model to inform the design of a randomized control trial in the Dominican Republic where we vary the nature of the information that is given to households in such a way as to identify the key parameters in the model. In the first treatment arm, we attempt to change households’ beliefs by providing information on the joint distribution of prices and quality of schools in their neighborhood. In the second treatment arm, we further reduce their search costs by also providing information on the attributes of each individual school and reveal their location and identity. The experimental results are used to estimate a structural model of endogenous consideration set determination, search and ultimately, school choice. We find evidence that in the context of school choice, considerations sets are endogenously too small due to biased beliefs of the joint distribution of prices and quality of schools in their neighborhood.

Facilitating Student Information Acquisition in Matching Markets

Nicole Immorlica
,
Microsoft Research
Jacob Leshno
,
University of Chicago
Irene Lo
,
Stanford University
Brendan Lucier
,
Microsoft Research

Abstract

In matching markets, such as college admissions and medical residency, the efficiency of the marketplace depends on its ability to effectively guide applicants in searching through options and forming their preferences. We provide a model of many-to-one matching that formally incorporates students’ preference formation through costly information acquisition. The model captures the harm of requiring students to submit a full preference list in advance, and rationalizes students’ tendency to delay making decisions.

We ask whether markets can facilitate optimal information acquisition for each student. We find that the matching constraint can lead to information deadlocks, as students need information to decide which information to gather. Consequently, even sequential matching mechanisms are limited in their ability to coordinate search. Instead, we show that historical market information can be used with simple mechanisms to achieve approximately optimal outcomes. In markets without historical information, a bootstrapping method together with flexible capacities can alleviate unnecessary costs and break the deadlock. Our results help explain why many established matching markets perform well despite informational frictions.

Why Are Schools Segregated? Evidence from the Secondary-School Match in Amsterdam

Hessel Oosterbeek
,
University of Amsterdam
Sandor Sovago
,
University of Groningen
Bas van der Klaauw
,
VU University Amsterdam

Abstract

We use rich data from the secondary-school match in Amsterdam to decompose school segregation by ethnicity and household income into five additive sources: i) ability tracking, ii) noise, iii) residential segregation, iv) preference heterogeneity, and v) capacity constraints. Important features of the Amsterdam school district are that students can freely choose any school at their ability level, school density is high and private schools are absent. We find that school segregation is mainly driven by ability tracking and students from different groups having different preferences. Residential segregation, capacity constraints and noise play only a minor role. Of the four policies that we analyze, affirmative action in the form of minority quotas reduces segregation the most. This comes, however, at the cost of a reduction of student welfare.
JEL Classifications
  • D8 - Information, Knowledge, and Uncertainty
  • I2 - Education and Research Institutions