Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jan, 2022, Volume 90, Issue 1

Breaking Ties: Regression Discontinuity Design Meets Market Design
p. 117-151

Atı̇la Abdulkadı̇roğlu, Joshua D. Angrist, Yusuke Narita, Parag Pathak

Many schools in large urban districts have more applicants than seats. Centralized school assignment algorithms ration seats at over‐subscribed schools using randomly assigned lottery numbers, non‐lottery tie‐breakers like test scores, or both. The New York City public high school match illustrates the latter, using test scores and other criteria to rank applicants at the city's screened schools, combined with lottery tie‐breaking at the rest. We show how to identify causal effects of school attendance in such settings. Our approach generalizes regression discontinuity methods to allow for multiple treatments and multiple running variables, some of which are randomly assigned. The key to this generalization is a local propensity score that quantifies the school assignment probabilities induced by lottery and non‐lottery tie‐breakers. The utility of the local propensity score is demonstrated in an assessment of the predictive value of New York City's school report cards. Schools that earn the highest report card grade indeed improve SAT math scores and increase graduation rates, though by much less than OLS estimates suggest. Selection bias in OLS estimates of grade effects is egregious for screened schools.

Log In To View Full Content

Supplemental Material

Supplement to "Breaking Ties: Regression Discontinuity Design Meets Market Design"

This zip file contains the replication files for the manuscript.

Supplement to "Breaking Ties: Regression Discontinuity Design Meets Market Design"

This online appendix contains material not found within the manuscript.