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Tracing The Effects Of Guaranteed Admission Through The College Process: Evidence From A Policy Discontinuity In The Texas 10% Plan

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  • JASON M. FLETCHER
  • ADALBERT MAYER

Abstract

The Texas 10% law states that students who graduated among the top 10% of their high school class are guaranteed admission to public universities in Texas. We estimate the causal effects of this admissions guarantee on a sequence of connected decisions: students' application behavior, admission decisions by the university, students' enrollment choices conditional on admission; as well as the resulting college achievement. We identify these effects by comparing students just above and just below the top 10% rank cutoff. While this design is in the spirit of a regression discontinuity, we note important differences in approach and interpretation. We find that students react to incentives created by the admissions guarantee - for example, by reducing applications to competing private universities. The results also suggest that the effects of the admissions guarantee depend on the university and the type of students it attracts, and that the law is binding and alters the decisions of the admissions committees. We find little evidence that the law increases diversity or leads to meaningful mismatch for the marginal student admitted.
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Suggested Citation

  • Jason M. Fletcher & Adalbert Mayer, 2014. "Tracing The Effects Of Guaranteed Admission Through The College Process: Evidence From A Policy Discontinuity In The Texas 10% Plan," Contemporary Economic Policy, Western Economic Association International, vol. 32(1), pages 169-186, January.
    • Handle: RePEc:bla:coecpo:v:32:y:2014:i:1:p:169-186
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    1. Cortes, Kalena E., 2010. "Do bans on affirmative action hurt minority students? Evidence from the Texas Top 10% Plan," Economics of Education Review, Elsevier, vol. 29(6), pages 1110-1124, December.
    2. Andrews, Rodney J. & Ranchhod, Vimal & Sathy, Viji, 2010. "Estimating the responsiveness of college applications to the likelihood of acceptance and financial assistance: Evidence from Texas," Economics of Education Review, Elsevier, vol. 29(1), pages 104-115, February.
    3. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    4. Cortes, Kalena E., 2010. "Do Bans on Affirmative Action Hurt Minority Students? Evidence from the Texas Top 10% Plan," IZA Discussion Papers 5021, Institute of Labor Economics (IZA).
    5. Kalena E. Cortes, 2010. "Do Bans on Affirmative Action Hurt Minority Students? Evidence from the Texas Top 10% Plan," Upjohn Working Papers 10-168, W.E. Upjohn Institute for Employment Research.
    6. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
    7. Sunny Xinchun Niu & Marta Tienda, 2010. "The impact of the Texas top ten percent law on college enrollment: A regression discontinuity approach," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 29(1), pages 84-110.
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    Cited by:

    1. Rajeev Darolia & Cory Koedel, 2018. "High Schools And Students' Initial Colleges And Majors," Contemporary Economic Policy, Western Economic Association International, vol. 36(4), pages 692-710, October.

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    More about this item

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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