IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/22390.html
   My bibliography  Save this paper

What Can We Learn from Charter School Lotteries?

Author

Listed:
  • Julia Chabrier
  • Sarah Cohodes
  • Philip Oreopoulos

Abstract

We take a closer look at what we can learn about charter schools by pooling data from lottery-based impact estimates of the effect of charter school attendance at 113 schools. On average, each year enrolled at one of these schools increases math scores by 0.08 standard deviations and English/language arts scores by 0.04 standard deviations. There is wide variation in impact estimates. To glean what drives this variation, we link these effects to school practices, inputs, and characteristics of fallback schools. In line with the earlier literature, we find that schools that adopt an intensive “No Excuses” attitude towards students are correlated with large gains in academic performance, with traditional inputs like class size playing no role in explaining charter school effects. However, we highlight that “No Excuses” schools are also located among the most disadvantaged neighborhoods in the country. After accounting for performance levels at fallback schools, the relationship between the remaining variation in school performance and the entire “No Excuses” package of practices weakens. “No Excuses” schools are effective at raising performance in neighborhoods with very poor performing schools, but the available data have less to say on whether the “No Excuses” approach could help in nonurban settings or whether other practices would similarly raise achievement in areas with low-performing schools. We find that intensive tutoring is the only “No Excuses” characteristic that remains significant (even for nonurban schools) once the performance levels of fallback schools are taken into account.

Suggested Citation

  • Julia Chabrier & Sarah Cohodes & Philip Oreopoulos, 2016. "What Can We Learn from Charter School Lotteries?," NBER Working Papers 22390, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:22390
    Note: CH ED LS
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w22390.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Patrick L. Baude & Marcus Casey & Eric A. Hanushek & Gregory R. Phelan & Steven G. Rivkin, 2020. "The Evolution of Charter School Quality," Economica, London School of Economics and Political Science, vol. 87(345), pages 158-189, January.
    2. 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.
    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, September.
    4. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    5. Christopher R. Walters, 2018. "The Demand for Effective Charter Schools," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2179-2223.
    6. Helen F. Ladd & Charles T. Clotfelter & John B. Holbein, 2017. "The Growing Segmentation of the Charter School Sector in North Carolina," Education Finance and Policy, MIT Press, vol. 12(4), pages 536-563, Fall.
    7. Matthew A. Kraft, 2014. "How to Make Additional Time Matter: Integrating Individualized Tutorials into an Extended Day," Education Finance and Policy, MIT Press, vol. 10(1), pages 81-116, November.
    8. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sarah R. Cohodes & Elizabeth M. Setren & Christopher R. Walters, 2021. "Can Successful Schools Replicate? Scaling Up Boston's Charter School Sector," American Economic Journal: Economic Policy, American Economic Association, vol. 13(1), pages 138-167, February.
    2. Frederico Finan & Demian Pouzo, 2021. "Reinforcing RCTs with Multiple Priors while Learning about External Validity," Papers 2112.09170, arXiv.org, revised Mar 2023.
    3. Henrekson, Magnus & Wennström, Johan, 2018. "“Post-Truth” Schooling and Marketized Education: Explaining the Decline in Sweden’s School Quality," Working Paper Series 1228, Research Institute of Industrial Economics, revised 28 Jan 2019.
    4. Mauricio Romero & Justin Sandefur, 2022. "Beyond Short-Term Learning Gains: the Impact of Outsourcing Schools in Liberia After Three Years," The Economic Journal, Royal Economic Society, vol. 132(644), pages 1600-1619.
    5. Matthew Davis & Blake Heller, 2019. "No Excuses Charter Schools and College Enrollment: New Evidence from a High School Network in Chicago," Education Finance and Policy, MIT Press, vol. 14(3), pages 414-440, Summer.
    6. Aaron K. Chatterji, 2017. "Innovation and American K-12 Education," NBER Chapters, in: Innovation Policy and the Economy, Volume 18, pages 27-51, National Bureau of Economic Research, Inc.
    7. Martin Bøg & Jens Dietrichson & Anna A. Isaksson, 2021. "A multi-sensory tutoring program for students at risk of reading difficulties: Evidence from a randomized field experiment," The Journal of Educational Research, Taylor & Francis Journals, vol. 114(3), pages 233-251, April.
    8. Ebrahim Azimi & Jane Friesen & Simon Woodcock, 2023. "Private Schools and Student Achievement," Education Finance and Policy, MIT Press, vol. 18(4), pages 623-653, Fall.
    9. Dennis Epple & Francisco Martinez-Mora & Richard Romano, 2021. "Charter School Practices and Student Selection: An Equilibrium Analysis," NBER Working Papers 29529, National Bureau of Economic Research, Inc.
    10. Andrew Bibler & Stephen B. Billings, 2020. "Win or Lose: Residential Sorting After a School Choice Lottery," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 457-472, July.
    11. Karin Edmark & Lovisa Persson, 2020. "The Impact of Attending an Independent Upper Secondary School: Evidence from Sweden Using School Ranking Data," CESifo Working Paper Series 8680, CESifo.
    12. W. Bentley MacLeod & Miguel Urquiola, 2018. "Is Education Consumption or Investment? Implications for the Effect of School Competition," NBER Working Papers 25117, National Bureau of Economic Research, Inc.
    13. Diana McCallum & Christina Tuttle & Jeffrey Max & Brian Gill & Philip Gleason, "undated". "How Does School Choice Affect Racial Integration?," Mathematica Policy Research Reports 60be07fb436f46b6b40a9178f, Mathematica Policy Research.
    14. Philip Oreopoulos, 2021. "What Limits College Success? A Review and Further Analysis of Holzer and Baum's Making College Work," Journal of Economic Literature, American Economic Association, vol. 59(2), pages 546-573, June.
    15. Angrist, Joshua D. & Pathak, Parag A. & Zarate, Roman A., 2023. "Choice and consequence: Assessing mismatch at Chicago exam schools," Journal of Public Economics, Elsevier, vol. 223(C).
    16. Elert, Niklas & Henrekson, Magnus, 2023. "The Profit Motive in the Classroom - Friend or Foe?," IZA Discussion Papers 16301, Institute of Labor Economics (IZA).
    17. Wu, Jia & Wei, Xiangdong & Zhang, Hongliang & Zhou, Xiang, 2019. "Elite schools, magnet classes, and academic performances: Regression-discontinuity evidence from China," China Economic Review, Elsevier, vol. 55(C), pages 143-167.
    18. Helen F. Ladd & John D. Singleton, 2020. "The Fiscal Externalities of Charter Schools: Evidence from North Carolina," Education Finance and Policy, MIT Press, vol. 15(1), pages 191-208, Winter.
    19. Fazzio, Ila & Eble, Alex & Lumsdaine, Robin L. & Boone, Peter & Bouy, Baboucarr & Hsieh, Pei-Tseng Jenny & Jayanty, Chitra & Johnson, Simon & Silva, Ana Filipa, 2021. "Large learning gains in pockets of extreme poverty: Experimental evidence from Guinea Bissau," Journal of Public Economics, Elsevier, vol. 199(C).
    20. Philip Gleason & Sarah Crissey & Greg Chojnacki & Marykate Zukiewicz & Tim Silva & Sarah Costelloe & Fran O'Reilly, "undated". "Evaluation of Support for Using Student Data to Inform Teachers’ Instruction," Mathematica Policy Research Reports c8487f07fcc34792b99d2b144, Mathematica Policy Research.
    21. Aaron Chatterji, 2017. "Innovation and American K-12 Education," NBER Working Papers 23531, National Bureau of Economic Research, Inc.
    22. Shi, Ying, 2020. "Who benefits from selective education? Evidence from elite boarding school admissions," Economics of Education Review, Elsevier, vol. 74(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John D. Singleton, 2019. "Incentives and the Supply of Effective Charter Schools," American Economic Review, American Economic Association, vol. 109(7), pages 2568-2612, July.
    2. Joshua D. Angrist, 2022. "Empirical Strategies in Economics: Illuminating the Path From Cause to Effect," Econometrica, Econometric Society, vol. 90(6), pages 2509-2539, November.
    3. 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.
    4. Atila Abdulkadiroğlu & Weiwei Hu & Parag A. Pathak, 2013. "Small High Schools and Student Achievement: Lottery-Based Evidence from New York City," NBER Working Papers 19576, National Bureau of Economic Research, Inc.
    5. Brigham R. Frandsen & Lars J. Lefgren, 2021. "Partial identification of the distribution of treatment effects with an application to the Knowledge is Power Program (KIPP)," Quantitative Economics, Econometric Society, vol. 12(1), pages 143-171, January.
    6. 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.
    7. Singleton, John D., 2017. "Putting dollars before scholars? Evidence from for-profit charter schools in Florida," Economics of Education Review, Elsevier, vol. 58(C), pages 43-54.
    8. Susan Dynarski & Daniel Hubbard & Brian Jacob & Silvia Robles, 2018. "Estimating the Effects of a Large For-Profit Charter School Operator," NBER Working Papers 24428, National Bureau of Economic Research, Inc.
    9. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    10. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    11. 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.
    12. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    14. Carlson, Deven & Lavertu, Stéphane, 2016. "Charter school closure and student achievement: Evidence from Ohio," Journal of Urban Economics, Elsevier, vol. 95(C), pages 31-48.
    15. Heidi Allen & Katherine Baicker, 2021. "The Effect of Medicaid on Care and Outcomes for Chronic Conditions: Evidence from the Oregon Health Insurance Experiment," NBER Working Papers 29373, National Bureau of Economic Research, Inc.
    16. Margaret Brehm & Scott A. Imberman & Michael Naretta, 2017. "Capitalization of Charter Schools into Residential Property Values," Education Finance and Policy, MIT Press, vol. 12(1), pages 1-27, Winter.
    17. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    18. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    19. Seojeong Lee, 2018. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 400-410, July.
    20. Michael R.M. Abrigo & Timothy J. Halliday & Teresa Molina, 2022. "Expanding health insurance for the elderly of the Philippines," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 500-520, April.

    More about this item

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy

    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:nbr:nberwo:22390. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.