Degree choice evidence from stated preferences

This paper studies the factors driving the choice of university degree or college major. Previous research shows that students choose the degree/major that reports them the maximum utility level. This evidence relies on data from revealed preferences, implicitly assuming that the degree/major a stud...

Full description

Saved in:
Bibliographic Details
Published in:Empirical economics 2017-06, Vol.52 (4), p.1205-1234
Main Authors: Artabe, Alaitz, Gardeazabal, Javier
Format: Article
Language:English
Subjects:
Academic degrees
College students
Decision making models
Discrete choice
Econometrics
Economic models
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Finance
Insurance
Management
Occupational choice
Rational choice
Revealed preferences
Specification
Statistics for Business
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper studies the factors driving the choice of university degree or college major. Previous research shows that students choose the degree/major that reports them the maximum utility level. This evidence relies on data from revealed preferences, implicitly assuming that the degree/major a student pursues is the student’s preferred degree. However, numerus clausus and other restrictions can condition the choice of major. Under these restrictions, the revealed choice is not necessarily the alternative that maximizes utility. We analyze data from pre-enrollment student-stated preferences regarding degrees within a natural field choice experiment setting. Our findings are in line with the rational choice results obtained in the literature, thus contributing external validity in a previously unexplored setting. In addition, we also contribute a discrete choice modeling strategy and estimation method. The discrete choice model accounts for individual characteristics, degree attributes and their interaction in an specification that is as general as discrete choice models used in the literature. The estimation method can handle cases where the number of alternatives and individual observations is large while other methods are unfeasible.
ISSN:0377-7332
1435-8921
DOI:10.1007/s00181-016-1121-5