*Names in bold indicate Presenter
This paper investigates the patterns of between and during the school year student mobility in Clark County (Las Vegas) with a focus on the relationship between student mobility and school quality. Detailed longitudinal data from 2007-08 to 2012-13 allows for in-depth classification of the various timing and types of school changes across a broad range of grades. I provide a descriptive analysis of student mobility and compare the exit patterns of students as well as examine the destination schools of mobile students using a multinomial framework. I also estimate the impact of student mobility on student achievement by replicating the empirical model developed by Hanushek and colleagues (2004) that decomposes a student’s academic growth into components attributable to changes in school quality and the costs of moving. Specifically, I ask the following research questions: Does the likelihood of exiting a school differ by students’ and schools' characteristics? Do students’ prior achievement and the quality of their current school predict whether students move to higher quality schools? Is there evidence of a long-term school quality effect for mobile students?
Preliminary results indicate that multiple types of student mobility occur between and during the school year at considerable rates. About a third of all students move over the course of the school year, with roughly 10 percent moving during the school year and three percent changing schools both between and during the school year. Mobile and non-mobile students are significantly different and there is also heterogeneity among the different categories of movers. Overall, preliminary results also indicate that students in low-achieving schools switch to low-achieving schools while students in high achieving schools transfer to high-achieving schools, regardless of their prior achievement or the timing of school changes. Differential student mobility patterns in Clark County provide suggestive evidence of a stratified school system and may lead to increased student segmentation based on student achievement and school quality.