IES Grant
Title: | Why are Some Charter Schools More Effective than Others? Econometric Methods and Empirical Evidence from Massachusetts, Michigan, and Texas | ||
Center: | NCER | Year: | 2012 |
Principal Investigator: | Angrist, Joshua | Awardee: | National Bureau of Economic Research (NBER) |
Program: | Improving Education Systems: Policies, Finance, Organization, Management, and Leadership [Program Details] | ||
Award Period: | 3 years (3/1/12-2/28/15) | Award Amount: | $1,654,320 |
Type: | Efficacy and Replication | Award Number: | R305A120269 |
Description: | Co-Principal Investigators: Susan Dynarski (NBER/University of Michigan), Parag Pathak (NBER/ Massachusetts Institute of Technology), and Brian Jacob (NBER/University of Michigan) Purpose: Enrollment in charter schools has tripled over the last decade, and more states are making it easier to open charter schools. These two factors make it likely that growth in charter school enrollment will continue in the coming years. The goal of the proposed research plan is to use a diverse sample of charter schools from three states to determine what makes some charter schools reliably succeed at increasing learning while others do not. A key feature of this study is that charter enrollment will be determined by a lottery system. Such an approach allows comparisons between charter school students and non-charter school students in a manner that meaningfully reduces selection bias. The results of this study are intended to contribute to the body of literature available to policy makers when developing or refining charter school initiatives. Project Activities: The research team will collect data on student demographics, student test scores, charter lotteries, and schools' educational approaches from Massachusetts, Michigan, and Texas. The team will use those data to conduct several analyses in an effort to control for selection bias while addressing questions involving differences in student outcomes between charter schools and non-charter schools, differences in educational approaches between charter schools and non-charter schools, and differences in educational approaches among charter schools themselves. Products: Products include evidence on the effect of charter schools on educational attainment, including the aspects of charter schools that best facilitate learning and the types of students most likely to benefit from charter schooling. Peer reviewed publications will also be produced. Structured Abstract Setting: This study will include data from students enrolled in charter schools and non-charter schools in Massachusetts, Michigan, and Texas. Sample: Data from multiple timepoints on thousands of students in elementary-, middle-, and high-school grade levels from Massachusetts, Michigan, and Texas will be obtained from existing state data sets and analyzed to address the research questions of the study. The data pool was limited to public school students who were part of a lottery to get into an over-subscribed charter school and for whom lottery data are available. The sample is diverse in ethnicity, urbanicity, and economic status, and it is considered representative of school-aged children in Massachusetts, Michigan, and Texas, as well as school-aged children in geographically and demographically comparable areas. Intervention: The intervention under investigation is charter schooling in general, with a specific focus on the various charter school structures and curricula in Massachusetts, Michigan, and Texas. Charter schools in those states are not understood to represent all forms of charter schooling that are currently or might later be implemented, but they do form a large and diverse set of charter schools to yield results that can be applied to other states. Research Design and Methods: The primary approach is the use of pre-existing randomized entrance lotteries to test the effects of charter schools on student outcomes and to use those results to inform an investigation of attributes of charter schools that seem to yield better student outcomes. Data come from state records and from the National Student Clearinghouse (undergraduate enrollment). Control Condition: Depending on the specific question being addressed by a given analysis, the control group will be non-charter schools, students who attend non-charter schools due to not being selected by the random lottery to attend a charter school, or students who choose not to attend a charter school, despite being given the option via the lottery. Key Measures: Data on student demographics, enrollment, graduation, and test scores are provided by the states from the Student Information Management System (SIMS; Massachusetts), the Department of Education, and the Center for Educational Performance and Information in Michigan, and from the Public Education Information Management System available from the Texas Education Research Center. The states' standardized test scores included in the study are the Massachusetts Comprehensive Assessment System for mathematics and English language arts; the Michigan Educational Assessment Program scores for math and English language arts; and Texas's test scores are provided from the Texas Assessment of Academic Schools, the Texas Assessment of Knowledge and Skills (TAKS), and the State of Texas Assessments of Academic Readiness), which will replace scores from the TAKS, beginning with the 2011–2012 school year. Data from the National Student Clearinghouse will be used to track post-secondary attainment of the students in the sample who graduate from high school. The researchers are also conducting telephone surveys of all of the eligible charter schools in the three states to obtain data about school practices and curricula. Data Analytic Strategy: Researchers will use a battery of analyses featuring an instrumental variables approach known as two-stage least squares. This will remedy selection bias issues in ordinary least squares estimates of models of student-level charter effect heterogeneity. Additional modeling strategies will model and test for the relationship between school-level causal effects and charter school characteristics, differences between urban and non-urban charter school effects, and to test the lottery process itself to ensure that it is functioning properly. Products and Publications Journal article, monograph, or newsletter Angrist, J. D., Cohodes, S. R., Dynarski, S. M., Pathak, P. A., and Walters, C. R. (2016). Stand and Deliver: Effects of Boston's Charter High Schools on College Preparation, Entry, and Choice. Journal of Labor Economics, 34 (2): 275–318. Angrist, J. D., Pathak, P. A., and Walters, C. R. (2013). Explaining Charter School Effectiveness. American Economic Journal: Applied Economics,, 5 (4): 1–27. |
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