Publication Cover
Journal of School Choice
International Research and Reform
Volume 11, 2017 - Issue 1
453
Views
4
CrossRef citations to date
0
Altmetric
Articles

Heterogeneous Effects of Charter Schools: Unpacking Family Selection and Achievement Growth in Los Angeles

, &

References

  • Abdulkadiroğlu, A., Angrist, J. D., Dynarski, S. M., Kane, T. J., & Pathak, P. A. (2011). Accountability and flexibility in public schools: Evidence from Boston’s charters and pilots. The Quarterly Journal of Economics, 126(2), 699–748. doi:10.1093/qje/qjr017
  • Angrist, J. D., Pathak, P. A., & Walters, C. R. (2011). Explaining charter school effectiveness. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w17332
  • Ballou, D., Teasley, B., & Zeidner, T. (2008). Charter schools in Idaho. Charter school outcomes. New York, NY: Lawrence Erlbaum Associates.
  • Berends, M., Goldring, E., Stein, M., & Cravens, X. (2010). Instructional conditions in charter schools and students’ mathematics achievement gains. American Journal of Education, 116(3), 303–335. doi:10.1086/651411
  • Bilfulco, R., & Buerger, C. (2012). The influence of finance and accountability policies on charter school locations. Syracuse, NY: Syracuse University.
  • Bodine, E., Fuller, B., González, M., Huerta, L., Naughton, S., Park, S., & Teh, L. W. (2008). Disparities in charter school resources—The influence of state policy and community. Journal of Education Policy, 23(1), 1–33. doi:10.1080/02680930701625262
  • Buckley, J., & Schneider, M. (2005). Are charter school students harder to educate? Evidence from Washington, DC. Educational Evaluation and Policy Analysis, 27(4), 365–380. doi:10.3102/01623737027004365
  • Carruthers, C. K. (2012). The qualifications and classroom performance of teachers moving to charter schools. Education Finance and Policy, 7(3), 233–268. doi:10.1162/EDFP_a_00067
  • Cowen, J. M., & Winters, M. A. (2013). Do charters retain teachers differently? Evidence from elementary schools in Florida. Education Finance and Policy, 8(1), 14–42. doi:10.1162/EDFP_a_00081
  • Dauter, L., & Fuller, B. (2016). Student movement in social context: The influence of time, peers, and place. American Educational Research Journal, 53, 33–70.
  • Diamond, A., & Sekhon, J. S. (2013). Genetic matching for estimating causal effects: A general multivariate matching method for achieving balance in observational studies. Review of Economics and Statistics, 95(3), 932–945. doi:10.1162/REST_a_00318
  • Dobbie, W., & Fryer, R. G., Jr. (2011). Getting beneath the veil of effective schools: Evidence from New York City. Cambridge, MA: National Bureau of Economic Research.
  • Epple, D., Romano, R., & Zimmer, R. (2015). Charter schools: A survey of research on their characteristics and effectiveness. Cambridge, MA: National Bureau of Economic Research (no. 21256). Retrieved from http://www.nber.org/papers/w17632.pdf
  • Fleming, D., Cowen, J., Witte, J., & Wolf, P. (2015). Similar students, different choices: Who uses a school voucher in an otherwise similar population of students?. Education and Urban Society, 47, 785–812. doi:10.1177/0013124513511268
  • Fligstein, N., & Dauter, L. (2007). The sociology of markets. Annual Reviews Sociology, 33, 105–128. doi:10.1146/annurev.soc.33.040406.131736
  • Fuller, B. (2010). Palace revolt in Los Angeles? How charter school and Latino leaders push unions to innovate. Education Next, 10. Retrieved from http://educationnext.org/palace-revolt-in-los-angeles/
  • Fuller, B. (2015). Organizing locally: How the new decentralists improve education, health care, and trade. Chicago, IL: University of Chicago Press.
  • Fuller, B., Waite, A., Chao, C., & Benedicto, I. (2014). Rich communities in small high schools? Teacher collaboration and cohesion inside 25 Los Angeles campuses. Berkeley, CA: Graduate School of Education.
  • Furgeson, J., Gill, B., Haimson, J., Killewald, A., McCullough, M., Nichols-Barrer, I., & Demeritt, A. (2012). Charter-school management organizations: Diverse strategies and diverse student impacts. Mathematica Policy Research, Inc. Retrieved from http://files.eric.ed.gov/fulltext/ED528536.pdf
  • Gleason, P., Clark, M., Tuttle, C., & Dwoyer, E. (2010). The evaluation of charter school impacts: Final report. Washington, DC: Mathematica Policy Research.
  • Hanushek, E. A., Kain, J. F., Rivkin, S. G., & Branch, G. F. (2007). Charter school quality and parental decision making with school choice. Journal of Public Economics, 91(5–6), 823–848. doi:10.1016/j.jpubeco.2006.09.014
  • Henderson, J., & Chatfield, S. (2011). Who matches? Propensity scores and bias in the causal effects of education on participation. The Journal of Politics, 73(3), 646–658. doi:10.1017/S0022381611000351
  • Henig, J. R., Hula, R. C., Orr, M., & Pedescleaux, D. S. (2001). The color of school reform: Race, politics, and the challenge of urban education. Princeton, NJ: Princeton University Press.
  • Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15(3), 199–236. doi:10.1093/pan/mpl013
  • Holland, P. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81(396), 945–960. doi:10.1080/01621459.1986.10478354
  • Howell, W. (2004). Dynamic selection effects in means-tested urban school voucher programs. Journal of Policy Analysis & Management, 23, 225–250. doi:10.1002/(ISSN)1520-6688
  • Hoxby, C. M., & Murarka, S. (2009). Charter schools in New York City: Who enrolls and how they affect their students’ achievement. Cambridge, MA: National Bureau of Economic Research.
  • Huerta, L. A. (2009). Institutional v. technical environments: Reconciling the goals of decentralization in an evolving charter school organization. Peabody Journal of Education, 84(2), 244–261. doi:10.1080/01619560902810179
  • Jackson, C. K. (2012). School competition and teacher labor markets: Evidence from charter school entry in North Carolina. Journal of Public Economics, 96(5–6), 431–448. doi:10.1016/j.jpubeco.2011.12.006
  • Keele, L. (2010). An overview of rbounds: An R package for Rosenbaum bounds sensitivity analysis with matched data (White Paper, pp. 1–15). Columbus, OH. Retrieved from http://www.personal.psu.edu/ljk20/rbounds%20vignette.pdf
  • Kerchner, C. T., Menefee-Libey, D. J., Mulfinger, L. S., & Clayton, S. E. (2008). Learning from LA: Institutional Change in American Public Education. Cambridge, MA: Harvard Education Press.
  • Lauen, D. (2009). To choose or not to choose: High school choice and graduation in Chicago. Educational Evaluation and Policy Analysis, 31(3), 179–199. doi:10.3102/0162373709339058
  • Lauen, D., Fuller, B., & Dauter, L. (2015). Positioning charter schools in Los Angeles: Diversity of form and homogeneity of effects. American Journal of Education, 121, 213–239. doi:10.1086/679391
  • Ledwith, V. (2010). The influence of open enrollment on scholastic achievement among public school students in Los Angeles. American Journal of Education, 116(2), 243–262. doi:10.1086/649493
  • Lesaffre, E., & Albert, A. (1989). Multiple-group logistic regression diagnostics. Applied Statistics, 38, 425–440. doi:10.2307/2347731
  • Lubienski, S. T., & Lubienski, C. (2006). School sector and academic achievement: A multilevel analysis of NAEP mathematics data. American Educational Research Journal, 43(4), 651–698. doi:10.3102/00028312043004651
  • Martínez, R. A., & Quartz, K. H. (2012). Zoned for change: A historical case study of the Belmont Zone of Choice. Teachers College Record, 114(10), 1–40.
  • Nisar, H. (2012). Heterogeneous competitive effects of charter schools in Milwaukee. Cambridge, MA: Abt Associates.
  • Peterson, P., Campbell, D., & West, M. (2002). Who chooses? Who uses? Participation in a national school voucher program. In P. Hill (Ed.), Choice with equity (pp. 51–84). Stanford, CA: Hoover Institution Press.
  • R Development Core Team. (2013). R: A language and environment for statistical computing. Vienna, Austria. Retrieved from https://cran.r-project.org
  • Raymond, M. (2013). National charter school study. Stanford, CA: Center for Research on Education Outcomes.
  • Raymond, M. (2014). Charter school performance in Los Angeles. Stanford, CA: Center for Research on Education Outcomes.
  • Reardon, S. (2009). Review of how New York City’s charter schools affect achievement. Boulder, CO: National Education Policy Center.
  • Rebell, M. A. (2009). Courts and kids: Pursuing educational equity through the state courts. Chicago, IL: University of Chicago Press.
  • Renzulli, L. A. (2006). District segregation, race legislation, and Black enrollment in charter schools. Social Science Quarterly, 87(3), 618–637. doi:10.1111/ssqu.2006.87.issue-3
  • Renzulli, L. A., Barr, A. B., & Paino, M. (2014). Innovative education? A test of specialist mimicry or generalist assimilation in trends in charter school specialization over time. Sociology of Education, 88, 83–102.
  • Rosenbaum, P. R. (2002). Observational studies. New York, NY: Springer.
  • Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. doi:10.1093/biomet/70.1.41
  • Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688–701. doi:10.1037/h0037350
  • Rubin, D. B. (2005). Causal inference using potential outcomes. Journal of the American Statistical Association, 100(469), 322–331. doi:10.1198/016214504000001880
  • Sekhon, J. (2011). Multivariate and propensity score matching software with automated balance optimization: The matching package for R. Journal of Statistical Software, 42(7), 1–52. doi:10.18637/jss.v042.i07
  • Sekhon, J. S., & Mebane, W. R. (1998). Genetic optimization using derivatives. Political Analysis, 7(1), 187–210. doi:10.1093/pan/7.1.187
  • Tuttle, C. C., Gill, B., Gleason, P., Knechtel, V., Nichols-Barrer, I., & Resch, A. (2013). KIPP middle schools: Impacts on achievement and other outcomes (Final Report). Princeton, NJ: Mathematica Policy Research, Inc.
  • Xiang, Y., & Tarasawa, B. (2015). Propensity score stratification using multilevel models to examine charter school achievement effects. Journal of School Choice, 9, 179–196. doi:10.1080/15582159.2015.1028862
  • Zimmer, R., & Buddin, R. (2006a). Charter school performance in two large urban districts. Journal of Urban Economics, 60(2), 307–326. doi:10.1016/j.jue.2006.03.003
  • Zimmer, R., & Buddin, R. (2006b). Making sense of charter schools: Evidence from California ( Occasional Paper). Santa Monica, CA: Rand Corporation.
  • Zimmer, R., Gill, B., Booker, K., Lavertu, S., & Witte, J. (2012). Examining charter student achievement effects across seven states. Economics of Education Review, 31(2), 213–224. doi:10.1016/j.econedurev.2011.05.005

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.