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The relationship between siblings’ college choices: Evidence from one million SAT-taking families

 
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Author
Goodman, Joshua SamuelHARVARD
Hurwitz, Michael
Smith, Jonathan
Fox, Julia
Published Version
https://doi.org/10.1016/j.econedurev.2015.05.006
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Citation
Goodman, Joshua, Michael Hurwitz, Jonathan Smith, and Julia Fox. 2015. “The Relationship Between Siblings’ College Choices: Evidence from One Million SAT-Taking Families.” Economics of Education Review 48 (October): 75–85. doi:10.1016/j.econedurev.2015.05.006.
Abstract
Research consistently shows that college choice in an important predictor of college completion and labor market outcomes. These longer term implications of college choice, combined with suboptimal choices made by many low-income but high-achieving students, has sparked several large-scale initiatives to improve college choice. Strategically targeting those students most susceptible to making questionable decisions in the college-choice process remains challenging, as variation in college choice is largely unexplained by easily measurable socio-demographic characteristics. This paper explores the potential to improve upon existing models and, more generally, to better understand college choice by documenting the similarities in college enrollment patterns between younger and older siblings. To do so, we identify siblings in the millions of SAT test-takers between the 2004 and 2011 high school graduation cohorts. We find that younger siblings enroll in the same college as their older sibling 21.2 percent of the time. Also, conditional on their own SAT scores, we find that younger siblings whose older siblings enrolled in four-year colleges and the most selective colleges are 17.4 and 21.3 percentage points, respectively, more likely to themselves enroll in four-year and the most selective colleges. Overall, adding characteristics and enrollment decisions of older siblings to standard college choice models improves model fit and consequently, are valuable pieces of information for explanatory and predictive power.
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https://research.hks.harvard.edu/publications/getFile.aspx?Id=1062
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This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:22805380

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Except where otherwise noted, this work is subject to a Creative Commons Attribution 4.0 International License, which allows anyone to share and adapt our material as long as proper attribution is given. For details and exceptions, see the Harvard Library Copyright Policy ©2022 Presidents and Fellows of Harvard College.

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