Preference-based sorting of students into schools under different school-choice policies¶

Theory · All theories
Evidence · 2 claims (2 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 2 claims rest on one study

Description¶

The brief organizes its policy analysis around how parental preferences translate into the sorting of students across schools under alternative school-choice policies. It states: "This brief describes (1) what parents look for when they choose a school and (2) how these preferences affect the sorting of students into schools under different school-choice policies." The framework links measured parent preferences (distance, demographics, academics, and variation across parents) to the equilibrium assignment of students produced by choice-policy designs.

Design Implications¶

Context¶

Requirements¶

• Data on parents' ranked school preferences, such as lottery application lists

Constraints¶

• Sorting outcomes depend on the specific school-choice policy in place, as the brief examines sorting under different policies

Target Learners¶

• Students and families participating in school-choice lotteries

Target Learning Objectives¶

• Designing school-choice policies in light of how parental preferences sort students into schools

Claims¶

• Dc Parents Distance Demographics Academics Drive Choice [+M]
• Dc Parents Considerable Variation Preferences [+M]

Related Theories¶

• School choice architecture as a behavioral design framework

Examples¶

• DC citywide lottery ranked-preference dataset from over 20,000 applicants to more than 100 schools

Key Sources¶

• Steven Glazerman, Dallas Dotter. (2016). Market Signals: How Do DC Parents Rank Schools, and What Does It Mean for Policy? Washington, DC: Mathematica Policy Research. https://www.mathematica.org/publications/market-signals-how-do-dc-parents-rank-schools-and-what-does-it-mean-for-policy