IDEAS home Printed from https://ideas.repec.org/p/dew/wpaper/2017-01.html
   My bibliography  Save this paper

The Role Of Distance In College Undermatching

Author

Listed:
  • Lois Miller

    (DePauw University)

  • Humberto Barreto

    (Department of Economics and Management, DePauw University)

Abstract

This paper explores factors explaining why so many high-achieving, low-income students apply to and enroll at universities with relatively low academic standards, despite generous financial aid packages and evidence that these students would be successful at colleges that are more selective. Amazon’s Mechanical Turk was used to gather data, and the entire file is freely available at academic.depauw.edu/hbarreto_web/working. A probit analysis confirms an established result that low-income students are more likely to undermatch. The key result is that as the distance between a student’s home and the university they attend increases, the probability that the student will undermatch decreases. At a distance of 500 miles between a student’s home and college, the difference in the probability of undermatching between low-income students and high-income students is 25.5 percentage points. At 3,000 miles, the gap is only 8.7 percentage points.

Suggested Citation

  • Lois Miller & Humberto Barreto, 2017. "The Role Of Distance In College Undermatching," Working Papers 2017-01, DePauw University, School of Business and Leadership and Department of Economics and Management.
  • Handle: RePEc:dew:wpaper:2017-01
    as

    Download full text from publisher

    File URL: https://www.depauw.edu/site/learn/dew/wpaper/workingpapers/DePauw2017-01-Miller-Barreto-CollegeUndermatching.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lincove, Jane Arnold & Cortes, Kalena E., 2016. "Match or Mismatch? Automatic Admissions and College Preferences of Low- and High-Income Students," IZA Discussion Papers 10150, Institute of Labor Economics (IZA).
    2. Katherine Michelmore & Susan Dynarski, 2016. "The Gap within the Gap: Using Longitudinal Data to Understand Income Differences in Student Achievement," NBER Working Papers 22474, National Bureau of Economic Research, Inc.
    3. Gordon C. Winston & Catharine B. Hill, 2005. "Access to the Most Selective Private Colleges by High-Ability, Low-Income Students: Are They Out There?," Williams Project on the Economics of Higher Education DP-69, Department of Economics, Williams College.
    4. Caroline Hoxby & Christopher Avery, 2013. "The Missing "One-Offs": The Hidden Supply of High-Achieving, Low-Income Students," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 44(1 (Spring), pages 1-65.
    5. Jane Arnold Lincove & Kalena E. Cortes, 2016. "Match or Mismatch? Automatic Admissions and College Preferences of Low- and High-Income Students," NBER Working Papers 22559, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    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. Bo, Shiyu & Liu, Jing & Shiu, Ji-Liang & Song, Yan & Zhou, Sen, 2019. "Admission mechanisms and the mismatch between colleges and students: Evidence from a large administrative dataset from China," Economics of Education Review, Elsevier, vol. 68(C), pages 27-37.
    2. Eleanor Wiske Dillon & Jeffrey Andrew Smith, 2020. "The Consequences of Academic Match between Students and Colleges," Journal of Human Resources, University of Wisconsin Press, vol. 55(3), pages 767-808.
    3. Ilya Prakhov & Denis Sergienko, 2017. "Matching between Students and Universities: What are the Sources of Inequalities of Access to Higher Education?," HSE Working papers WP BRP 45/EDU/2017, National Research University Higher School of Economics.
    4. Song, Yang, 2019. "Sorting, school performance and quality: Evidence from China," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 238-261.
    5. Amanda Pallais, 2015. "Small Differences That Matter: Mistakes in Applying to College," Journal of Labor Economics, University of Chicago Press, vol. 33(2), pages 493-520.
    6. Castleman, Benjamin L. & Owen, Laura & Page, Lindsay C., 2016. "Reprint of “Stay late or start early? Experimental evidence on the benefits of college matriculation support from high schools versus colleges”," Economics of Education Review, Elsevier, vol. 51(C), pages 113-124.
    7. Lindo, Jason M. & Marcotte, Dave E. & Palmer, Jane E. & Swensen, Isaac D., 2019. "Any press is good press? The unanticipated effects of Title IX investigations on university outcomes," Economics of Education Review, Elsevier, vol. 73(C).
    8. Avery, Christopher & Castleman, Benjamin L. & Hurwitz, Michael & Long, Bridget Terry & Page, Lindsay C., 2021. "Digital messaging to improve college enrollment and success," Economics of Education Review, Elsevier, vol. 84(C).
    9. Adam Altmejd & Andrés Barrios-Fernández & Marin Drlje & Joshua Goodman & Michael Hurwitz & Dejan Kovac & Christine Mulhern & Christopher Neilson & Jonathan Smith, 2021. "O Brother, Where Start Thou? Sibling Spillovers on College and Major Choice in Four Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(3), pages 1831-1886.
    10. Christopher Neilson & Adam Altmejd & Andres Barrios-Fernandez & Marin Drlje & Dejan Kovac, 2019. "Siblings' Effects on College and Major Choices: Evidence from Chile, Croatia and Sweden," Working Papers 633, Princeton University, Department of Economics, Industrial Relations Section..
    11. Andrews, Rodney J. & Imberman, Scott A. & Lovenheim, Michael F., 2020. "Recruiting and supporting low-income, high-achieving students at flagship universities," Economics of Education Review, Elsevier, vol. 74(C).
    12. 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).
    13. Yang, Ruijuan & You, Xuqun & Zhang, Yu & Lian, Ling & Feng, Wei, 2019. "Teachers’ mental health becoming worse: The case of China," International Journal of Educational Development, Elsevier, vol. 70(C), pages 1-1.
    14. Joshua S. Goodman & Michael Hurwitz & Christine Mulhern & Jonathan Smith, 2019. "O Brother, Where Start Thou? Sibling-Spillovers in College Enrollment," CESifo Working Paper Series 7974, CESifo.
    15. Juliana Londoño-Vélez, 2022. "The Impact of Diversity on Perceptions of Income Distribution and Preferences for Redistribution," NBER Working Papers 30386, National Bureau of Economic Research, Inc.
    16. Raj Chetty & John N. Friedman & Emmanuel Saez & Nicholas Turner & Danny Yagan, 2017. "Mobility Report Cards: The Role of Colleges in Intergenerational Mobility," NBER Working Papers 23618, National Bureau of Economic Research, Inc.
    17. Londoño-Vélez, Juliana, 2022. "The impact of diversity on perceptions of income distribution and preferences for redistribution," Journal of Public Economics, Elsevier, vol. 214(C).
    18. Comi, Simona & Origo, Federica & Pagani, Laura & Tonello, Marco, 2021. "Last and furious: Relative position and school violence," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 736-756.
    19. Rodney J. Andrews & Kevin M. Stange, 2019. "Price Regulation, Price Discrimination, and Equality of Opportunity in Higher Education: Evidence from Texas," American Economic Journal: Economic Policy, American Economic Association, vol. 11(4), pages 31-65, November.
    20. Castleman, Benjamin L. & Owen, Laura & Page, Lindsay C., 2015. "Stay late or start early? Experimental evidence on the benefits of college matriculation support from high schools versus colleges," Economics of Education Review, Elsevier, vol. 47(C), pages 168-179.

    More about this item

    Keywords

    college application; Mechanical Turk; matching; sorting; education; inequality; social capital;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

    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:dew:wpaper:2017-01. 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: Manu Raghav or Humberto Barreto (email available below). General contact details of provider: https://edirc.repec.org/data/emdepus.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.