- Abadie, A. (2002). Bootstrap tests for distributional treatment effects in instrumental variables models. Journal of the American Statistical Association, 97(457).
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Abadie, A. (2003). Semiparametric instrumental variable estimation of treatment response models. Journal of Econometrics, 113(2).
Abdulkadiro˘glu, A., Angrist, J., Dynarski, S., Kane, T. J., and Pathak, P. (2011). Accountability and flexibility in public schools: Evidence from Boston’s charters and pilots. The Quarterly Journal of Economics, 126(2):699–748.
Anderson, M. L. (2008). Multiple inference and gender differences in the effects of early intervention: A reevaluation of the abecedarian, perry preschool, and early training projects. Journal of the American statistical Association, 103(484):1481–1495.
Andrabi, T., Das, J., Ijaz Khwaja, A., and Zajonc, T. (2011). Do value-added estimates add value? accounting for learning dynamics. American Economic Journal: Applied Economics, 3(3):29–54.
- Angrist, J. D., Cohodes, S. R., Dynarski, S. M., Fullerton, J., Kane, T. J., Pathak, P. A., and Walters, C. R. (2011a). Student achievement in Massachusetts’ charter schools. Center for Education Policy Research at Harvard University.
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Angrist, J. D., Dynarski, S. M., Kane, T. J., Pathak, P. A., and Walters, C. R. (2010). Inputs and impacts in charter schools: KIPP Lynn. American Economic Review, 100(2):239–243.
- Angrist, J. D., Dynarski, S. M., Kane, T. J., Pathak, P. A., and Walters, C. R. (2012). Who beneï¬ts from KIPP? Journal of Policy Analysis and Management, 31(4):837–860.
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Angrist, J. D., Lang, D., and Oreopoulos, P. (2009). Incentives and services for college achievement: Evidence from a randomized trial. American Economic Journal: Applied Economics, 1(1):136– 163.
- Angrist, J. D., Pathak, P. A., and Walters, C. R. (2011b). Explaining charter school effectiveness. Working Paper 17332, National Bureau of Economic Research, Cambridge, MA.
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- AP and SAT Data We use AP and SAT data ï¬les provided to the Massachusetts Department of Elementary and Secondary Education by College Board. The AP and SAT ï¬les include scores on all AP exams and SAT tests for graduation cohorts 2007 and 2012; for student who took the SAT more than once, the ï¬le includes only the score for the most recent exam. The AP and SAT ï¬les also include SASID identiï¬ers, which are used to merge these outcomes with the SIMS database.
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Banerjee, A. V., Cole, S., Duflo, E., and Linden, L. (2007). Remedying education: Evidence from two randomized experiments in india. The Quarterly Journal of Economics, 122(3):1235–1264.
Booker, K., Sass, T. R., Gill, B., and Zimmer, R. (2008). Going beyond test scores: Evaluating charter school impact on educational attainment in Chicago and Florida. RAND, Santa Monica, CA.
- Bowen, W. and Bok, D. (2000). The Shape of the River: Long-Term Consequences of Considering Race in College and University Admissions. Princeton University Press, Princeton, NJ.
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- Bowen, W. G., Chingos, M. M., and McPherson, M. S. (2009). Crossing the ï¬nish line: Completing college at America’s public universities. Princeton University Press, Princeton, NJ.
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Chetty, R., Friedman, J. N., and Rockoff, J. E. (2011b). The long-term impacts of teachers: Teacher value-added and student outcomes in adulthood. NBER Working Paper 17699, National Bureau of Economic Research.
Chetty, R., Friedman, J. N., Hilger, N., Saez, E., Schanzenbach, D. W., and Yagan, D. (2011a). How does your kindergarten classroom affect your earnings? Evidence from Project STAR. Quarterly Journal of Economics, 126(4):1593–1660.
Cohodes, S. and Goodman, J. (2013). Merit aid, college quality, and college completion: Massachusetts’ Adams scholarship as an in-kind subsidy. HKS Faculty Research Working Paper Series RWP13-005.
Cunha, F., Heckman, J. J., and Schennach, S. M. (2010). Estimating the technology of cognitive and noncognitive skill formation. Econometrica, 78(3):883–931.
- Currie, J. and Thomas, D. (2000). School quality and the longer-term effects of head start. The Journal of Human Resources, 35(4):755.
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Deming, D. (2009). Early childhood intervention and life-cycle skill development: Evidence from Head Start. American Economic Journal: Applied Economics, 1(3):111–134.
Deming, D. J., Hastings, J. S., Kane, T. J., and Staiger, D. O. (2013). School choice, school quality and postsecondary attainment. The American Economic Review.
Dobbie, W. and Fryer, R. G. (2011a). Are high-quality schools enough to increase achievement among the poor? Evidence from the Harlem Children’s Zone. American Economic Journal: Applied Economics, 3(3):158–187.
Dobbie, W. and Fryer, R. G. (2011b). Getting beneath the veil of effective schools: Evidence from New York City. Technical Report NBER Working Paper No. 17632, National Bureau of Economic Research, Cambridge, MA.
- Dobbie, W. and Fryer, R. G. (2012). Are high quality schools enough to reduce social disparities? Evidence from the Harlem Children’s Zone. Unpublished manuscript, Harvard University.
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- Dynarski, M. and Gleason, P. (2002). How can we help? what we have learned from recent federal dropout prevention evaluations. Journal of Education for Students Placed At Risk, 7(1):43–69.
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Dynarski, M. and Wood, R. (1997). Helping high-risk youths: Results for the alternative schools demonstration program. Mathematica Policy Research, Inc. Princeton, NJ.
Dynarski, M., Gleason, P., Rangarajan, A., and Wood, R. (1998). Impacts of dropout prevention programs. Technical report, Mathematica Policy Research, Inc., Princeton, NJ.
Dynarski, S. M., Hyman, J. M., and Schanzenbach, D. W. (2011). Experimental evidence on the effect of childhood investments on postsecondary degree attainment and degree completion. Working Paper 17553, National Bureau of Economic Research, Cambridge, MA.
- Garces, E., Thomas, D., and Currie, J. (2002). Longer-term effects of head start. The American Economic Review, 92(4):999–1012.
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- GED Data Information on GED test-taking is provided by the Massachusetts Department of Elementary and Secondary Education’s GED Office. This data includes testing dates and outcomes (pass or fail) for students taking tests from 2002 to 2010. The GED information is merged to the SIMS administrative database by ï¬rst, middle, and last name, and birth date. This procedure matched 70 percent of GED tests to records in the SIMS database.
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- Hanushek, E., Kain, J., Markman, J. M., and Rivkin, S. (2003). Does peer ability affect student achievement? Heuer, R. and Stullich, S. (2011). Comparability of state and local expenditures among schools within districts: A report from the study of school-level expenditures. Technical report, U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Policy and Program Studies Service.
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Hoxby, C. (2000). Peer effects in the classroom: Learning from gender and race variation. NBER Working Paper, 7867.
Hoxby, C. M. and Avery, C. (2012). The missing “one-offsâ€: The hidden supply of high-achieving, low-income students. NBER Working Paper 18586, National Bureau of Economic Research.
- Imbens, G. W. and Angrist, J. D. (1994). Identiï¬cation and estimation of local average treatment effects. Econometrica, 62(2):467–475.
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- Jacob, B. A. (2007). Test-based accountability and student achievement: An investigation of differential performance on NAEP and state assessment. Working Paper 12817, National Bureau of Economic Research, Cambridge, MA.
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Jacob, B. A. and Levitt, S. D. (2003). Rotten apples: An investigation of the prevalence and predictors of teacher cheating. The Quarterly Journal of Economics, 118(3):843–877.
Jacob, B. A., Lefgren, L., and Sims, D. P. (2010). The persistence of teacher-induced learning. Journal of Human Resources, 45(4):915–943.
Kane, T. J. and Staiger, D. O. (2008). Estimating teacher impacts on student achievement: An experimental evaluation. Technical Report Working Paper 14607, National Bureau of Economic Research, Cambridge, MA.
- Kemple, J. and Snipes, J. (2000). Career academies: Impacts on students’ engagement and performance in high school. MDRC. New York.
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Krueger, A. B. and Whitmore, D. M. (2001). The effect of attending a small class in the early grades on college-test taking and middle school test results: Evidence from project star. The Economic Journal, 111(468):1–28.
- Legewie, J. and DiPrete, T. A. (2012). School context and the gender gap in educational achievement. American Sociological Review, 77(3):463–485.
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- Massachusetts Department of Elementary and Secondary Education (2013). The Commenwealth of Massachusetts Department of Elementary and Secondary Education Massachusetts charter schools fact sheet.
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- MCAS Data We use MCAS data from the 2001-2002 school year through the 2011-2012 school year. Each observation in the MCAS database corresponds to a students test results in a particular grade and year. The MCAS outcomes of interest are math and English Language Arts (ELA) tests in grade 10. We also use baseline tests taken prior to charter application, which are from 4th grade or 8th grade depending on a students application grade. The raw test score variables are standardized to have mean zero and standard deviation one within a subject-grade-year in Massachusetts. We also make use of scaled scores, which are used to determine whether students meet MCAS thresholds, which are Needs Improvement, Proï¬cient, and Advanced. Unless otherwise noted, we only use the ï¬rst test taken in a particular subject and grade.
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Neal, D. and Schanzenbach, D. W. (2010). Left behind by design: Proï¬ciency counts and test-based accountability. Review of Economics and Statistics, 92(2):263–283.
- NSC Data Data on college outcomes comes from the National Student Clearinghouse (NSC) database, which captures enrollment for 94% of undergraduates in Massachusetts. We combine information from three separate searches of the NSC database: • A 2010 search for all students in the SIMS database between 2002 and 2009 with projected graduation years earlier than 2014, assuming normal academic progress from the last observed grade and year (not restricted to students who graduated high school); • A 2011 search of students who graduated from Massachusetts public high schools in the class of 2010; • A 2012 search of all students who graduated from Massachusetts public high schools in the classes of 2003 through 2010; • A 2013 search of students who graduated from Massachusetts public high schools in the classes of 2003 through 2012.
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- P-valuesarefromtestsofthehypothesisthatallcoefficientsarezero.Baselinegradeisdefinedas4thgradeforBostonCollegiateapplicants,5thgradeforBostonPreparatoryandAcademyofthePacificRim,and 8thgradeforMatch,CodmanAcademyandCityonaHill.BaselinegradeforBPS9thgradersis8thgrade.On-timecollegeenrollmentisindicatesenrollmentbythesemesterafterprojectedhighschoolgraduation, assumingnormalacademicprogressfrombaseline. *significantat10%;**significantat5%;***significantat1% 2007-12(AP/SAToutcomesample)2006-11(NSCoutcomesample) ProjectedSeniorYear ------
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Sacerdote, B. (2011). Peer Effects in Education: How Might They Work, How Big Are They and How Much Do We Know Thus Far?, volume 3 of Handbook of the Economics of Education, chapter 4, pages 249–277. Elsevier.
- Silverman, B. W. (1986). Density estimation for statistics and data analysis, volume 26. CRC press.
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- Skinner, K. (2009). Charter school succes or selective out-migration of low achievers? effects of enrollment management on student achievement. Technical report, Massachusetts Teachers Association.
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- Thernstrom, A. M. and Thernstrom, S. (2003). No excuses: Closing the racial gap in learning. Simon & Schuster, New York.
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Tuttle, C. C., Gill, B., Gleason, P., Knechtel, V., Nichols-Barrer, I., and Resch, A. (2013). KIPP middle schools: Impacts on achievement and other outcomes. Mathematica Policy Research, Princeton, NJ.