Why it Pays to Major in Economics

Abstract

In this article, the authors use a large, recent, and accessible data set to examine the effect of economics major on individual earnings. They find a significant positive earnings gain for economics majors relative to other majors, and this advantage increases with the level of education. Their findings are consistent with Black, Sanders, and Taylor (2003), documenting that about two-thirds of the bachelor's degree premium for economics majors can be attributed to the type of job economics majors perform, and about one-third is a premium that economics majors earn over other workers within the same job.

Keywords:

• American Community Survey data base
• economics majors
• individual earnings

JEL code:

• J31

ACKNOWLEDGEMENTS

The authors thank Luis Lopez, Bernard Malamud, Economics Department seminar participants at the University of Nevada, Las Vegas, an anonymous referee, and one of the editors of this journal for helpful comments and suggestions that improved this article.

Notes

¹Because our data set only identifies the undergraduate major and does not identify the undergraduate institution, we are unable to test this assertion in our study.

²An interesting strand of literature relates civic returns to education (e.g., Ashenfelter and Kelley 1975; Dee 2004). In particular, Allgood and colleagues (2012) found that economics coursework or majoring in economics was significantly associated with civic behaviors such as attitudes toward policy issues or donation to a political party or campaign.

³The variable “dis” is coded as 1 if the subject reports disabilities seeing, hearing, doing errands, remembering, or walking.

⁴Other potential endogenous variables include marital status and number of children.

⁵Personal characteristics include age, indicators for race (black, Native American and Native Alaskan, Asian, Hawaiian, other nonwhites, and individuals with multiple races), Hispanic ethnicity, citizenship status, facility with English, and occupational disabilities. We estimated separate equations for men and women.

⁶There are 18,127 unique codes for male workers and 15,143 occupation codes for female workers, all of whom have bachelor's degrees or better.

⁷oipuma = oi + pumax1012, which gives us an index which uniquely identifies location (the first four digits), occupation, the fifth through eighth digits, and industry (the last four digits). This index generates 153,747.

⁸We used the Stata “areg” command to control for over 100,000 controls for the combination of industry, occupation, and location. For instance, occupation controls adjust for the difference in earnings between economists working in finance from those working in other business disciplines like marketing. Industry controls adjust for the differences between business finance and government finance. Location controls adjust for the difference in pay for a financial economist working in New York and her counterpart working in Chicago.