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Getting Beneath the Veil of Effective Schools: Evidence from New York City

Author

Listed:
  • Will Dobbie
  • Roland G. Fryer, Jr

Abstract

Charter schools were developed, in part, to serve as an R&D engine for traditional public schools, resulting in a wide variety of school strategies and outcomes. In this paper, we collect unparalleled data on the inner-workings of 35 charter schools and correlate these data with credible estimates of each school's effectiveness. We find that traditionally collected input measures -- class size, per pupil expenditure, the fraction of teachers with no certification, and the fraction of teachers with an advanced degree -- are not correlated with school effectiveness. In stark contrast, we show that an index of five policies suggested by over forty years of qualitative research -- frequent teacher feedback, the use of data to guide instruction, high-dosage tutoring, increased instructional time, and high expectations -- explains approximately 50 percent of the variation in school effectiveness. Our results are robust to controls for three alternative theories of schooling: a model emphasizing the provision of wrap-around services, a model focused on teacher selection and retention, and the "No Excuses'' model of education. We conclude by showing that our index provides similar results in a separate sample of charter schools.

Suggested Citation

  • Will Dobbie & Roland G. Fryer, Jr, 2011. "Getting Beneath the Veil of Effective Schools: Evidence from New York City," NBER Working Papers 17632, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17632 Note: ED LS
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    References listed on IDEAS

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    1. Sorting through heterogeneity of impact to enhance policy learning
      by Jed Friedman in Development Impact on 2012-11-21 19:18:30

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    Cited by:

    1. Joshua D. Angrist & Parag A. Pathak & Christopher R. Walters, 2013. "Explaining Charter School Effectiveness," American Economic Journal: Applied Economics, American Economic Association, vol. 5(4), pages 1-27, October.
    2. Isabella Sulis & Mariano Porcu, 2015. "Assessing Divergences in Mathematics and Reading Achievement in Italian Primary Schools: A Proposal of Adjusted Indicators of School Effectiveness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 607-634, June.
    3. John P. Papay & Richard J. Murnane & John B. Willett, 2014. "Income-based Inequality in Educational Outcomes: Learning from State Longitudinal Data Systems," NBER Working Papers 20802, National Bureau of Economic Research, Inc.
    4. Victor Lavy, 2012. "Expanding School Resources and Increasing Time on Task: Effects of a Policy Experiment in Israel on Student Academic Achievement and Behavior," NBER Working Papers 18369, National Bureau of Economic Research, Inc.
    5. Joshua D. Angrist & Sarah R. Cohodes & Susan M. Dynarski & Parag A. Pathak & Christopher R. Walters, 2016. "Stand and Deliver: Effects of Boston's Charter High Schools on College Preparation, Entry, and Choice," Journal of Labor Economics, University of Chicago Press, vol. 34(2), pages 275-318.
    6. Kevin Booker & Brian Gill & Tim Sass & Ron Zimmer, "undated". "Charter High Schools' Effects on Long-Term Attainment and Earnings (Working Paper)," Mathematica Policy Research Reports cfe561a4b1924b7eafb64f918, Mathematica Policy Research.
    7. Joshua M. Cowen & Marcus A. Winters, 2013. "Do Charters Retain Teachers Differently? Evidence from Elementary Schools in Florida," Education Finance and Policy, MIT Press, vol. 8(1), pages 14-42, January.
    8. Dennis Epple & Richard Romano & Ron Zimmer, 2015. "Charter Schools: A Survey of Research on Their Characteristics and Effectiveness," NBER Working Papers 21256, National Bureau of Economic Research, Inc.
    9. Will Dobbie & Roland G. Fryer, Jr, 2013. "The Medium-Term Impacts of High-Achieving Charter Schools on Non-Test Score Outcomes," NBER Working Papers 19581, National Bureau of Economic Research, Inc.
    10. repec:mpr:mprres:7927 is not listed on IDEAS
    11. Philip Oreopoulos & Robert S. Brown & Adam M. Lavecchia, 2017. "Pathways to Education: An Integrated Approach to Helping At-Risk High School Students," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 947-984.
    12. 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 133-152, Spring.

    More about this item

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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