[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/aea/jecper/v30y2016i3p57-84.html
   My bibliography  Save this article

What Can We Learn from Charter School Lotteries?

Author

Listed:
  • Julia Chabrier
  • Sarah Cohodes
  • Philip Oreopoulos
Abstract
We take a closer look at what can be learned 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 relative to attending a counterfactual public school. 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 positive effects on 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?," Journal of Economic Perspectives, American Economic Association, vol. 30(3), pages 57-84, Summer.
    • Handle: RePEc:aea:jecper:v:30:y:2016:i:3:p:57-84
    Note: DOI: 10.1257/jep.30.3.57
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/articles?id=10.1257/jep.30.3.57
    Download Restriction: no
    File URL: https://www.aeaweb.org/articles/attachments?retrieve=p28uFSl6bBMpj_NZGNNL8VgH_av3PnIZ
    Download Restriction: no
    File URL: https://www.aeaweb.org/articles/attachments?retrieve=hsh2-DdZ5jOwI_Sig16w53FdwVzGZzDl
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    4. Christopher R. Walters, 2018. "The Demand for Effective Charter Schools," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2179-2223.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    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. 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.
    2. Léonard Moulin, 2023. "Do private schools increase academic achievement? Evidence from France," Education Economics, Taylor & Francis Journals, vol. 31(2), pages 247-274, March.
    3. 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.
    4. 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.
    5. 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.
    6. Aaron Chatterji, 2017. "Innovation and American K-12 Education," NBER Working Papers 23531, National Bureau of Economic Research, Inc.
    7. Frederico Finan & Demian Pouzo, 2021. "Reinforcing RCTs with Multiple Priors while Learning about External Validity," Papers 2112.09170, arXiv.org, revised Sep 2024.
    8. Elert, Niklas & Henrekson, Magnus, 2023. "The Profit Motive in the Classroom - Friend or Foe?," IZA Discussion Papers 16301, Institute of Labor Economics (IZA).
    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. Edmark, Karin & Persson, Lovisa, 2021. "The impact of attending an independent upper secondary school: Evidence from Sweden using school ranking data," Economics of Education Review, Elsevier, vol. 84(C).
    11. 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.
    12. 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.
    13. 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.
    14. Henrekson, Magnus & Wennström, Johan, 2019. "‘Post-truth’ schooling and marketized education: explaining the decline in Sweden's school quality," Journal of Institutional Economics, Cambridge University Press, vol. 15(5), pages 897-914, October.
    15. 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.
    16. Shi, Ying, 2020. "Who benefits from selective education? Evidence from elite boarding school admissions," Economics of Education Review, Elsevier, vol. 74(C).
    17. 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.
    18. 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.
    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. 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.
    21. 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).
    22. 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.
    23. 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.
    24. Chen, Feng & Harris, Douglas N., 2023. "The market-level effects of charter schools on student outcomes: A national analysis of school districts," Journal of Public Economics, Elsevier, vol. 228(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. Tobin, Zachary, 2024. "How do public schools respond to competition? Evidence from a charter school expansion," Economics of Education Review, Elsevier, vol. 99(C).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    12. 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.
    13. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP77/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. 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.
    15. 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.
    16. 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.
    17. Hsu, De Fen & Morrill, Melinda & Pathak, Aditi, 2024. "Health and retirement: Heterogeneity in the responsiveness to pension incentives," Economics Letters, Elsevier, vol. 238(C).
    18. 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.
    19. 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.
    20. 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.

    More about this item

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

    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:aea:jecper:v:30:y:2016:i:3:p:57-84. 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: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.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.