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Distributional Analysis in Educational evaluation : A Case Study from the New York City Voucher Program Marianne P. Bitler, UC Irvine & NBER,* Thurston Domina, UC Irvine, Emily K. Penner, UC Irvine, & Hilary W. Hoynes, UC Berkeley and NBER April 2014 Abstract: We use quantile treatment effects estimation to examine the consequences of the random-assignment New York City School Choice Scholarship Program (NYCSCSP) across the distribution of student achievement. Our analyses suggest that the program had negligible and statistically insignificant effects across the skill distribution. In addition to contributing to the literature on school choice, the paper illustrates several ways in which Distributional effects estimation can enrich Educational research: First, we demonstrate that moving beyond a focus on mean effects estimation makes it possible to generate and test new hypotheses about the heterogeneity of Educational treatment effects that speak to the justification for many interventions.
Distributional Analysis in Educational Evaluation: A Case Study from the New York City Voucher Program Marianne P. Bitler, UC Irvine & NBER,*
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