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Private school vouchers and student achievement: A fixed effects quantile regression evaluation

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  • Lamarche, Carlos
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    Abstract

    Fundamental to the recent debate over school choice is the issue of whether voucher programs actually improve students' academic achievement. Using newly developed quantile regression approaches, this paper investigates the distribution of achievement gains in the first school voucher program implemented in the US. We find that while high-performing students selected for the Milwaukee Parental Choice program had a positive, convexly increasing gain in mathematics, low-performing students had a nearly linear loss. However, the program seems to prevent low-performing students from having an even bigger loss experienced by students in the public schools.

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    File URL: http://www.sciencedirect.com/science/article/B6VFD-4SDX2PR-1/2/6d219c0e3e48932888948e80b3da1156
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    Bibliographic Info

    Article provided by Elsevier in its journal Labour Economics.

    Volume (Year): 15 (2008)
    Issue (Month): 4 (August)
    Pages: 575-590

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    Handle: RePEc:eee:labeco:v:15:y:2008:i:4:p:575-590

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    Web page: http://www.elsevier.com/locate/labeco

    Related research

    Keywords: I21 I28 School choice Vouchers Milwaukee Fixed effects Quantile regression;

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    References

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    1. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2003. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," Working Papers 109, RAND Corporation Publications Department.
    2. Julie Berry Cullen & Brian Jacob & Steven Levitt, 2000. "The Impact of School Choice on Student Outcomes: An Analysis of the Chicago Public Schools," NBER Working Papers 7888, National Bureau of Economic Research, Inc.
    3. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275, October.
    4. Cecilia Elena Rouse, 1998. "Private School Vouchers And Student Achievement: An Evaluation Of The Milwaukee Parental Choice Program," The Quarterly Journal of Economics, MIT Press, vol. 113(2), pages 553-602, May.
    5. Justine S. Hastings & Thomas J. Kane & Douglas O. Staiger, 2006. "Preferences and Heterogeneous Treatment Effects in a Public School Choice Lottery," NBER Working Papers 12145, National Bureau of Economic Research, Inc.
    6. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    7. Jere R. Behrman & Yingmei Cheng & Petra E. Todd, 2004. "Evaluating Preschool Programs When Length of Exposure to the Program Varies: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 108-132, February.
    8. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    9. Thomas J. Kane & Douglas O. Staiger, 2002. "The Promise and Pitfalls of Using Imprecise School Accountability Measures," Journal of Economic Perspectives, American Economic Association, vol. 16(4), pages 91-114, Fall.
    10. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, 01.
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    Cited by:
    1. Olivier Damette & Philippe Delacote, 2011. "On the economic factors of deforestation: what can we learn from quantile analysis?," Working Papers 1110, Chaire Economie du Climat.
    2. Harding, Matthew & Lamarche, Carlos, 2009. "A quantile regression approach for estimating panel data models using instrumental variables," Economics Letters, Elsevier, vol. 104(3), pages 133-135, September.

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