Poster Paper: An Exploration of Charter Impacts on Student Mobility Utilizing Charter Lottery Results as a Natural Experiment

Saturday, November 8, 2014
Ballroom B (Convention Center)

*Names in bold indicate Presenter

Kailey Spencer, University of Pennsylvania
Student mobility is an important phenomenon to explore in its own right but also because it is associated with other key educational outcomes.  Despite these meaningful associations, there is little research on student mobility. In particular, not enough is known about whether and how popular movements in education reform impact student mobility.  As a major educational reform that is shaping the public school system in the United States, it is essential to have an understanding of how charter schools impact important educational outcomes, including nonstructural student mobility—students exiting their school prior to the completion of their school’s terminal grade. This study explores whether charter schools affect rates of nonstructural student mobility, and whether their influence varies among students with different characteristics by answering two questions: 1) does winning admission to a charter school—intent-to-treat (ITT)—or attending a charter school—treatment on the treated (TOT)—impact the occurrence of nonstructural student mobility? And, 2) is the impact of winning admission to or attending a charter school on nonstructural student mobility moderated by student characteristics? The data for this study come from The Evaluation of Charter School Impacts conducted by Mathematica Policy Research for the U.S. Department of Education’s Institute of Education Sciences.  These data utilize admissions lottery results from 29 charter schools and 2,330 students. Students who applied to and won charter lotteries make up the treatment group and students who applied to and lost charter lotteries comprise the control group. This design serves as a natural experiment and allows for the estimation of charter school impacts on student outcomes.   I employ logistic regression analysis to calculate the ITT estimates, and a two-stage least squares procedure to estimate TOT effects.