Structured Abstract
Setting
Sample
Research design and methods
Key measures
Data analytic strategy
People and institutions involved
IES program contact(s)
Products and publications
ERIC Citations: Find available citations in ERIC for this award here.
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Journal articles
Hastings, J.S., Kane, T.J., and Staiger, D.O. (2006). Gender and Performance: Evidence From School Assignment by Randomized Lottery. American Economic Review, 96 (2): 232-236.
Hastings, J.S., Kane, T.J., Staiger, D.O., and Weinstein, J.M. (2007). The Effects of Randomized School Admissions on Voter Participation. Journal of Public Economics, 91 (5): 915-937.
Weinstein, J.M. (2016). The Impact of School Racial Compositions on Neighborhood Racial Compositions: Evidence from School Redistricting. Economic Inquiry, 54 (3): 1365-1382.
** This project was submitted to and funded under Education Policy, Finance, and Systems in FY 2005.
Supplemental information
During spring 2002 parents submitted their top three choices of schools for the 2002-2003 school year, resulting in applications for approximately 95 percent of the district's 110,000 students. Each student was guaranteed admission to a default "home school" within their neighborhood if they were not admitted to any of their parents' top three choices. Additionally, students were guaranteed admission to continue in magnet programs in which they were enrolled in spring 2002.
Approximately 60 percent of the choice applications requested that students be assigned to their home school or a continuation magnet school as a first choice, while approximately 40 percent identified a first choice school to which students had no guarantee of admission. This resulted in an oversubscription of approximately one third of the schools in the district. Using a lottery-based system to determine enrollment in oversubscribed schools, students who were not guaranteed admission to their first-choice school were assigned to priority groups by school and grade. Groups were prioritized in the following order: students living in the home school zone, students who had attended the school in the prior year, free-lunch eligible students (in schools where less than half the students were free-lunch eligible), and students applying to schools within their choice zone. Within each priority group, admission was determined by lottery number; for each school slots were assigned in order of priority group and random number and proceeded until the school's capacity was reached. If a school was not filled by those students whose parents listed it as a first choice, this lottery process would repeat with students whose parents listed it as a second choice. Approximately 19 percent of students winning the lottery to attend the first-choice school selected by their parents subsequently attended a different school. Ultimately, for the fall 2002 semester, the school choice process resulted in a re-sorting of students across schools in the district. Approximately one-third of continuing elementary school students and two-fifths of continuing middle school students attended a different school than they had attended the previous year.
In phase 1, researchers will assemble student data and merge it with the characteristics of each parental school choice, the lottery results, the geographic boundary files, and responses to parental satisfaction surveys. Researchers will also develop a statistical package and an estimation theory for determining whether the impacts of school choice on student achievement are consistent with parental preferences. In phase 2, they will estimate the models of parental school preferences needed to determine the trade-offs parents made when choosing the schools they wished their students would attend with the Charlotte-Mecklenburg school system. They will also estimate the impacts of students being offered their parents' first choice school on various student outcomes. Phase 3 will involve merging previous findings to identify the subgroups of youth for whom researchers would expect the largest academic achievement impacts. The final tasks in phase 4 will include studying the causes of racial re-segregation and the competitive environment facing individual schools, and will also involve making recommendations to the school district.
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