Abstract
Recent empirical work has demonstrated the importance both of educational peer effects and of various factors that affect college choices. We connect these literatures by highlighting a previously unstudied determinant of college choice, namely the college choice made by one's older sibling. Data on 1.6 million sibling pairs of SAT-takers reveals that younger and older siblings’ choices are very closely related. One-fifth of younger siblings enroll in the same college as their older siblings. Compared to their high school classmates of similar academic skill and with observably similar families, younger siblings are about 15–20 percentage points more likely to enroll in 4-year colleges or highly competitive colleges if their older siblings do so first. These findings vary little by family characteristics. Younger siblings are more likely to follow the college choices of their older siblings the more they resemble each other in terms of academic skill, age and gender. We discuss channels through which older siblings’ college choices might causally influence their younger siblings, noting that the facts documented here should prompt further research on the sharing of information and shaping of educational preferences within families.
Highlights
Researchers have been modeling students’ college enrollment decisions for decades (e.g. Fuller, Manski and Wise, 1982)
There is substantial evidence that students don’t have complete information or, at the very least, have different amounts of information (Dillon and Smith, 2013; Hoxby and Turner, 2013). This implies that the variation in college choice is left largely unexplained, or statistically speaking, the R-squared is quite low
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
Summary
Researchers have been modeling students’ college enrollment decisions for decades (e.g. Fuller, Manski and Wise, 1982). Fuller, Manski and Wise, 1982). It has proven a difficult modeling problem for at least three reasons. There are thousands of colleges, each with countless attributes, most of which are unobservable to the econometrician. There is substantial evidence that students don’t have complete information or, at the very least, have different amounts of information (Dillon and Smith, 2013; Hoxby and Turner, 2013). Combined, this implies that the variation in college choice is left largely unexplained, or statistically speaking, the R-squared is quite low.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
