Smart Matching Platforms and Heterogeneous Beliefs in Centralized School Choice

S-Tier
Journal: Quarterly Journal of Economics
Year: 2022
Volume: 137
Issue: 3
Pages: 1791-1848

Authors (4)

Felipe Arteaga (not in RePEc) Adam J Kapor (not in RePEc) Christopher A Neilson (Yale University) Seth D Zimmerman (Yale University)

Score contribution per author:

2.011 = (α=2.01 / 4 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Many school districts with centralized school choice adopt strategy-proof assignment mechanisms to relieve applicants from needing to strategize based on beliefs about their own admissions chances. This article shows that beliefs about admissions chances shape choice outcomes even when the assignment mechanism is strategy-proof by influencing how applicants search for schools and that “smart matching platforms” that provide live feedback on admissions chances help applicants search more effectively. Motivated by a model in which applicants engage in costly search for schools and overoptimism can lead to undersearch, we use data from a large-scale survey of choice participants in Chile to show that learning about schools is hard, beliefs about admissions chances guide the decision to stop searching, and applicants systematically underestimate nonplacement risk. We use RCT and RD research designs to evaluate scaled live feedback policies in the Chilean and New Haven choice systems. Twenty-two percent of applicants submitting applications where risks of nonplacement are high respond to warnings by adding schools to their lists, reducing nonplacement risk by 58% and increasing test score value added at the schools where they enroll by 0.10 standard deviations. Reducing the burden of school choice requires not just strategy-proofness inside the centralized system but also choice supports for the strategic decisions that inevitably remain outside of it.

Technical Details

RePEc Handle
repec:oup:qjecon:v:137:y:2022:i:3:p:1791-1848.
Journal Field
General
Author Count
4
Added to Database
2026-01-26