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The Sequential College Application Process

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  • Jonathan Smith

    (Andrew Young School of Policy Studies Georgia State University Atlanta, GA 30302-3992 Author email: jsmith500@gsu.edu)

Abstract

To demonstrate the sequential nature of the college application process, in this paper I analyze the evolution of applications among high-achieving low-income students through data on the exact timing of SAT score sends. I describe at what point students send scores to colleges and which score sends ultimately become applications, resulting in three main points. First, score sends are not synonymous with applications—rather, only 62 percent of score sends in this sample turn into applications. Second, the conversion from score send to application is nonrandom as it relates to college characteristics: Score sends are more likely to convert into applications when they are to colleges with lower tuition, higher graduation rates, and relatively near a student's home. Third, the timing of score sends is related to the probability of its becoming an application, whereby score sends sent relatively early are least likely to become applications. These facts imply that there is room for improvement when modeling the application process and, in addition, the timing of an intervention or policy may be critical to its success.

Suggested Citation

  • Jonathan Smith, 2018. "The Sequential College Application Process," Education Finance and Policy, MIT Press, vol. 13(4), pages 545-575, Fall.
  • Handle: RePEc:tpr:edfpol:v:13:y:2018:i:4:p:545-575
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    References listed on IDEAS

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    1. David Card & Alan B. Krueger, 2005. "Would the Elimination of Affirmative Action Affect Highly Qualified Minority Applicants? Evidence from California and Texas," ILR Review, Cornell University, ILR School, vol. 58(3), pages 416-434, April.
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    8. Timothy N. Bond & George Bulman & Xiaoxiao Li & Jonathan Smith, 2018. "Updating Human Capital Decisions: Evidence from SAT Score Shocks and College Applications," Journal of Labor Economics, University of Chicago Press, vol. 36(3), pages 807-839.
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    12. Lindsay C. Page & Judith Scott-Clayton, 2015. "Improving College Access in the United States: Barriers and Policy Responses," NBER Working Papers 21781, National Bureau of Economic Research, Inc.
    13. Eleanor Wiske Dillon & Jeffrey Andrew Smith, 2017. "Determinants of the Match between Student Ability and College Quality," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 45-66.
    14. Dennis Epple & Richard Romano & Holger Sieg, 2006. "Admission, Tuition, and Financial Aid Policies in the Market for Higher Education," Econometrica, Econometric Society, vol. 74(4), pages 885-928, July.
    15. Smith, Jonathan & Pender, Matea & Howell, Jessica, 2013. "The full extent of student-college academic undermatch," Economics of Education Review, Elsevier, vol. 32(C), pages 247-261.
    16. Long, M.C.Mark C., 2004. "College applications and the effect of affirmative action," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 319-342.
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    20. Michael Luca & Jonathan Smith, 2013. "Salience in Quality Disclosure: Evidence from the U.S. News College Rankings," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 22(1), pages 58-77, March.
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    Cited by:

    1. Joshua Goodman & Oded Gurantz & Jonathan Smith, 2020. "Take Two! SAT Retaking and College Enrollment Gaps," American Economic Journal: Economic Policy, American Economic Association, vol. 12(2), pages 115-158, May.
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    3. Oded Gurantz & Jessica Howell & Michael Hurwitz & Cassandra Larson & Matea Pender & Brooke White, 2021. "A National‐Level Informational Experiment to Promote Enrollment in Selective Colleges," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(2), pages 453-479, March.
    4. Gurantz, Oded & Pender, Matea & Mabel, Zachary & Larson, Cassandra & Bettinger, Eric, 2020. "Virtual advising for high-achieving high school students," Economics of Education Review, Elsevier, vol. 75(C).

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