IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp8985.html
   My bibliography  Save this paper

Charters Without Lotteries: Testing Takeovers in New Orleans and Boston

Author

Listed:
  • Abdulkadiroglu, Atila

    () (Duke University)

  • Angrist, Joshua

    ()

  • Hull, Peter D.

    () (Massachusetts Institute of Technology)

  • Pathak, Parag A.

    () (MIT)

Abstract

Lottery estimates suggest oversubscribed urban charter schools boost student achievement markedly. But these estimates needn't capture treatment effects for students who haven't applied to charter schools or for students attending charters for which demand is weak. This paper reports estimates of the effects of charter school attendance on middle-schoolers in charter takeovers in New Orleans and Boston. Takeovers are traditional public schools that close and then re-open as charter schools. Students enrolled in schools designated for closure are eligible for "grandfathering" into the new schools; that is, they are guaranteed seats. We use this fact to construct instrumental variables estimates of the effects of passive charter attendance: the grandfathering instrument compares students at schools designated for takeover with students who appear similar at baseline and who were attending similar schools not yet closed, while adjusting for possible violations of the exclusion restriction in such comparisons. Estimates for a large sample of takeover schools in the New Orleans Recovery School District show substantial gains from takeover enrollment. In Boston, where we can compare grandfathering and lottery estimates for a middle school, grandfathered students see achievement gains at least as large as the gains for students assigned seats in lotteries. A non-charter Boston turnaround intervention that had much in common with the charter treatment generates gains as large as those seen for takeovers, but other more modest turnaround interventions produce much smaller effects.

Suggested Citation

  • Abdulkadiroglu, Atila & Angrist, Joshua & Hull, Peter D. & Pathak, Parag A., 2015. "Charters Without Lotteries: Testing Takeovers in New Orleans and Boston," IZA Discussion Papers 8985, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp8985
    as

    Download full text from publisher

    File URL: http://ftp.iza.org/dp8985.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Brian A. Jacob, 2004. "Public Housing, Housing Vouchers, and Student Achievement: Evidence from Public Housing Demolitions in Chicago," American Economic Review, American Economic Association, vol. 94(1), pages 233-258, March.
    2. 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.
    3. repec:mpr:mprres:7680 is not listed on IDEAS
    4. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
    5. Bruce Sacerdote, 2012. "When the Saints Go Marching Out: Long-Term Outcomes for Student Evacuees from Hurricanes Katrina and Rita," American Economic Journal: Applied Economics, American Economic Association, vol. 4(1), pages 109-135, January.
    6. Will Dobbie & Roland G. Fryer Jr., 2013. "Getting beneath the Veil of Effective Schools: Evidence from New York City," American Economic Journal: Applied Economics, American Economic Association, vol. 5(4), pages 28-60, October.
    7. Tatyana Deryugina & Laura Kawano & Steven Levitt, 2018. "The Economic Impact of Hurricane Katrina on Its Victims: Evidence from Individual Tax Returns," American Economic Journal: Applied Economics, American Economic Association, vol. 10(2), pages 202-233, April.
    8. 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, September.
    9. Atila Abdulkadiroğlu & Joshua Angrist & Parag Pathak, 2014. "The Elite Illusion: Achievement Effects at Boston and New York Exam Schools," Econometrica, Econometric Society, vol. 82(1), pages 137-196, January.
    10. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    11. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    12. Vigdor Jacob L, 2007. "The Katrina Effect: Was There a Bright Side to the Evacuation of Greater New Orleans?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 7(1), pages 1-40, December.
    13. Thomas Dee, 2012. "School Turnarounds: Evidence from the 2009 Stimulus," NBER Working Papers 17990, National Bureau of Economic Research, Inc.
    14. Will Dobbie & Roland G. Fryer, 2011. "Are High-Quality Schools Enough to Increase Achievement among the Poor? Evidence from the Harlem Children's Zone," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 158-187, July.
    15. repec:mpr:mprres:7681 is not listed on IDEAS
    16. Eyles, Andrew & Machin, Stephen, 2015. "The introduction of academy schools to England’seducation," LSE Research Online Documents on Economics 63815, London School of Economics and Political Science, LSE Library.
    17. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    18. Atila Abdulkadiroğlu & Joshua D. Angrist & Peter D. Hull & Parag A. Pathak, 2016. "Charters without Lotteries: Testing Takeovers in New Orleans and Boston," American Economic Review, American Economic Association, vol. 106(7), pages 1878-1920, July.
    19. Christopher R. Walters, 2014. "The Demand for Effective Charter Schools," NBER Working Papers 20640, National Bureau of Economic Research, Inc.
    20. Oecd, 2014. "Access Network Speed Tests," OECD Digital Economy Papers 237, OECD Publishing.
    21. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
    22. 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.
    23. Christina Clark Tuttle & Brian Gill & Philip Gleason & Virginia Knechtel & Ira Nichols-Barrer & Alexandra Resch, "undated". "KIPP Middle Schools: Impacts on Achievement and Other Outcomes (Executive Summary)," Mathematica Policy Research Reports ce0a1376d63744699ca19f917, Mathematica Policy Research.
    24. Scott A. Imberman & Adriana D. Kugler & Bruce I. Sacerdote, 2012. "Katrina's Children: Evidence on the Structure of Peer Effects from Hurricane Evacuees," American Economic Review, American Economic Association, vol. 102(5), pages 2048-2082, August.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    instrumental variables; education reform; education production; compliers;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp8985. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Holger Hinte). General contact details of provider: http://www.iza.org .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.