Recent studies have suggested that double-majoring in college yields minimal economic benefits and might be limiting to students who would otherwise have room in their schedule to take on electives and extracurricular activities.
But Christos Makridis, a doctoral candidate in Labor and Public Economics at Stanford University, offers research supporting the other side of the argument. Double majoring does improve salary outcomes, argues Makridid—but only when students pursue two disparate fields of study rather than two that are relatively similar.
Switching majors doesn't have to hurt student progress
To conduct his research, Makridis used data from the US Census Bureau to examine two million full-time employees between the ages of 20 and 65 from 2009 to 2015.
Makridis looked into these individuals':
- Family size;
- Marital status;
- Years of schooling; and
- Undergraduate degree(s).
Translate data into action on your campus. Take the diagnostic to evaluate the effectiveness of your academic planning tools
Makridis found that double-majors combining disparate fields—for instance, STEM and liberal arts—result in significantly higher earnings than either one on its own.
- Liberal arts students who took on a second degree in STEM earned an average of 9.5% more than those who only majored in the liberal arts;
- Liberal arts students who took on a second degree in business earned an average of 7.9% more than those who only majored in the liberal arts; and
- STEM students who take on a second degree in the liberal arts earned an average of 3.6% more than those who only majored in STEM.
Makridis' study reinforces research finding that employers are desperate for employees that have both technical and soft skills. A 2015 survey by the Wall Street Journal found that 92% of employers say soft skills are just as important or even more important than technical skills, but 89% struggle to find candidates with both (Makridis, The Conversation, 3/28).
Help students select the right major from the start
Next in Today's Briefing
16 questions to help you use predictive analytics ethically