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Explaining Charter School Effectiveness

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Author Info

  • Angrist, Joshua

    ()
    (MIT)

  • Pathak, Parag A.

    ()
    (MIT)

  • Walters, Christopher R.

    ()
    (MIT)

Abstract

Estimates using admissions lotteries suggest that urban charter schools boost student achievement, while charter schools in other settings do not. Using the largest available sample of lotteried applicants to charter schools, we explore student-level and school-level explanations for this difference in Massachusetts. In an econometric framework that isolates sources of charter effect heterogeneity, we show that urban charter schools boost achievement well beyond that of urban public school students, while non-urban charters reduce achievement from a higher baseline. Student demographics explain some of these gains since urban charters are most effective for non-whites and low-baseline achievers. At the same time, non-urban charter schools are uniformly ineffective. Our estimates also reveal important school-level heterogeneity within the urban charter sample. A non-lottery analysis suggests that urban charters with binding, well-documented admissions lotteries generate larger score gains than under-subscribed urban charter schools with poor lottery records. Finally, we link charter impacts to school characteristics such as peer composition, length of school day, and school philosophy. The relative effectiveness of urban lottery-sample charters is accounted for by these schools' embrace of the No Excuses approach to urban education.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 6525.

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Length: 59 pages
Date of creation: Apr 2012
Date of revision:
Publication status: published in: American Economic Journal: Applied Economics, 2013, 5 (4), 1-27
Handle: RePEc:iza:izadps:dp6525

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Keywords: achievement; charter schools; human capital;

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References

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  1. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
  2. Scott Imberman, 2008. "Achievement and Behavior in Charter Schools: Drawing a More Complete Picture," Working Papers 2009-01, Department of Economics, University of Houston.
  3. Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak & Christopher R. Walters, 2012. "Who Benefits from KIPP?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 31(4), pages 837-860, 09.
  4. Jesse M. Rothstein, 2006. "Good Principals or Good Peers? Parental Valuation of School Characteristics, Tiebout Equilibrium, and the Incentive Effects of Competition among Jurisdictions," American Economic Review, American Economic Association, vol. 96(4), pages 1333-1350, September.
  5. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2000. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," NBER Working Papers 7831, National Bureau of Economic Research, Inc.
  6. Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak & Christopher R. Walters, 2010. "Inputs and Impacts in Charter Schools: KIPP Lynn," American Economic Review, American Economic Association, vol. 100(2), pages 239-43, May.
  7. Vilsa E. Curto & Roland G. Fryer, Jr., 2011. "Estimating the Returns to Urban Boarding Schools: Evidence from SEED," NBER Working Papers 16746, National Bureau of Economic Research, Inc.
  8. Atila Abdulkadiroğlu & Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak, 2011. "Accountability and Flexibility in Public Schools: Evidence from Boston's Charters And Pilots," The Quarterly Journal of Economics, Oxford University Press, vol. 126(2), pages 699-748.
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Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Sorting through heterogeneity of impact to enhance policy learning
    by Jed Friedman in Development Impact on 2012-11-21 13:18:30
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Cited by:
  1. Cortes, Kalena & Goodman, Joshua & Nomi, Takako, 2013. "Intensive Math Instruction and Educational Attainment: Long-Run Impacts of Double-Dose Algebra," Working Paper Series rwp13-009, Harvard University, John F. Kennedy School of Government.
  2. Felipe Barrera-Osorio & Darío Maldonado & Catherine Rodríguez, 2012. "Calidad de la Educación Básica y Media en Colombia: Diagnóstico y Propuestas," DOCUMENTOS CEDE 010321, UNIVERSIDAD DE LOS ANDES-CEDE.
  3. Kevin Booker & Brian Gill & Tim Sass & Ron Zimmer, 2014. "Charter High Schools' Effects on Long-Term Attainment and Earnings," Mathematica Policy Research Reports 8005, Mathematica Policy Research.
  4. Clark, Damon & Del Bono, Emilia, 2014. "The long-run effects of attending an elite school: evidence from the UK," ISER Working Paper Series 2014-05, Institute for Social and Economic Research.
  5. Julie Berry Cullen & Steven D. Levitt & Erin Robertson & Sally Sadoff, 2013. "What Can Be Done to Improve Struggling High Schools?," Journal of Economic Perspectives, American Economic Association, vol. 27(2), pages 133-52, Spring.
  6. Brian Gill & Joshua Furgeson & Hanley S. Chiang & Bing-Ru Teh & Joshua Haimson & Natalya Verbitsky-Savitz, 2013. "Replicating Experimental Impact Estimates with Nonexperimental Methods in the Context of Control Crossover," Mathematica Policy Research Reports 7927, Mathematica Policy Research.

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