THE BERKELEY ECONOMIC REVIEW
widely considered to be more difficult than other majors with lower average grade point averages (GPA). If students are faced with the uncertainty of a recession, they may be unwilling to take on the additional uncertainty of pursuing a STEM degree as compared to another field that would be a relatively safe choice in terms of perceived difficulty. Main and Ost (2014), however, provides evidence that letter grades do not significantly influence student’s course taking or major selection behavior. This would suggest that the differences in average GPA may not be taken into account during a recession. Some recessions are either the result or cause of the contraction of specific industries. In these instances, it may be the case that if a certain industry is in distress, the accompanying degrees relevant to the industry may also see a fall in student pursuit. Kinsler and Pavan (2015) find that students with a degree in STEM fields earn 30% less working in an unrelated field, business majors earn 3% less, and other majors earn an average of 11% less working in fields unrelated to the individual’s degree. Similar studies done by Robst (2006), Yakusheva and Nordin (2010), and Persson and Rooth (2010) estimate wage penalties around 20% for business, engineering, health, computer science, and law professionals. These results might imply that students will choose to major in the highest paying field having the most reasonable expectation of employment. The body of literature synthesizes nicely into a backdrop for my primary question: during fluctuations in the business cycle, what changes can be observed in the proportion of degrees conferred by field of study? During dips in the business cycle, individuals are more likely to enroll in college to invest in human capital. Individuals decide what field to study mostly based on expected returns on wages. STEM majors will be most favored, since those fields have the highest return on investment and the industries involving most STEM fields are less likely than another industry—such as manufacturing—to experience a relatively severe contraction during such a downturn. My paper complements the literature as I will focus on observing actual changes in field of degree composition in response to varying local unemployment rates using institution-level IPEDS panel data from 1997 through 2015. Similar to Hillman and Orians (2013), Reiling and Strøm (2015), Messer and Wolter (2010), and Webber (2014), the fixed-effects panel data model will be used to analyze the IPEDS data. This approach will extend the existing literature and provide a
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