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Are They Worth it?: Master’s Degrees and Labor Market Outcomes in the STEM Workforce

  • Hironao OkahanaEmail author
  • Yi Hao
Article

Abstract

Utilizing the 2013 National Survey of College Graduates (Scientists and Engineers Statistical Data System, National Science Foundation, 2015), this study examined three measures of labor market outcomes: annual earning potentials; primary work activity; and education-job match for science, technology, engineering, and mathematics (STEM) bachelor’s degree holders by their master’s degree attainment. Whereas the study found earning differentials across master’s degrees, the results suggest that one’s earnings are explained by other factors, specifically gender. Results reflect a discernible and concerning pay gap between men and women with the same level of degree attainment in the STEM workforce. Also, implications for policy and practice are addressed.

Keywords

Earnings Education-job match Gender pay gap master’s degree Primary work activity STEM 

Notes

Acknowledgments

This article is based upon work supported by the National Science Foundation under Grant No. 1538769. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation or the Council of Graduate Schools.

References

  1. American Association of University Professors (2018). The annual report on the economic status of the profession, 2017–18. Washington, DC: Authors. Retrieved from https://www.aaup.org/sites/default/files/ARES_2017-18.pdf. Accessed 11 April 2018.
  2. American Association of University Women (2017). The simple truth about the gender pay gap. Washington, DC: Authors. Retrieved from https://www.aauw.org/aauw_check/pdf_download/show_pdf.php?file=The-Simple-Truth. Accessed 9 Aug 2017.
  3. Baruch, Y. (2004). Transforming careers: From linear to multidimensional career paths. Career Development International, 9, 58–73.CrossRefGoogle Scholar
  4. Baum, S., Ma, J., & Payea, K. (2013). Education pays 2013: The benefits of higher education for individual and society. Washington DC: College Board. Retrieved from https://trends.collegeboard.org/sites/default/files/education-pays-2013-full-report.pdf. Accessed 1 June 2017.
  5. Becker, G. S. (1993). Human capital: A theoretical and empirical analysis with special reference to education (3rd ed.). Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
  6. Bender, K. A., & Heywood, J. S. (2011). Educational mismatch and the careers of scientists. Education Economics, 19, 253–274.CrossRefGoogle Scholar
  7. Carnevale, A. P., Smith, N., & Melton, M. (2011). STEM state-level analysis. Washington, DC: Center on Education and the Workforce, Georgetown University. Retrieved from https://files.eric.ed.gov/fulltext/ED525307.pdf. Accessed 1 June 2017.
  8. Council of Graduate Schools (2008). Data sources: Enrollment and degree trends in graduate education, medicine, and law. Retrieved from http://cgsnet.org/ckfinder/userfiles/files/DataSources_2008_11.pdf. Accessed 24 May 2017.
  9. Council of Graduate Schools (n.d.). GradSense. Retrieved from https://gradsense.org/gradsense. Accessed 3 Jan 2019.
  10. Delisle, J., & Holt, A. (2015, February 20). A student loan blind spot. The Washington Post. Retrieved from https://www.washingtonpost.com/opinions/the-22-billion-student-loan-blind-spot/2015/02/20/e3413e82-b6f5-11e4-aa05-1ce812b3fdd2_story.html. Accessed 1 June 2017.
  11. Gallagher, S. (2014a, August 5). Yes, Master’s: A graduate degree’s moment in the age of higher education innovation. New England Journal of Higher Education. Retrieved from: http://www.nebhe.org/thejournal/yes-masters-a-graduate-degrees-moment-in-the-age-of-higher-education-innovation/. Accessed 6 June 2017.
  12. Gallagher, S. (2014b). Major employers’ hiring practices and the evolving function of the professional master’s degree (Doctoral Dissertation, Northeastern University). Retrieved from https://repository.library.northeastern.edu/files/neu:336448/fulltext.pdf. Accessed 24 May 2017
  13. Gándara, D., & Toutkoushian, R. K. (2017). Updated estimates of the average financial return on master’s degree programs in the United States. Journal of Education Finance, 43, 21–44.Google Scholar
  14. Georgetown University Center on Education and the Workforce (2018). Women can’t win: Despite making educational gains and pursuing high-wage majors, women still earn less than men. Washington, DC: Author. Retrieved from https://cew.georgetown.edu/cew-reports/genderwagegap/. Accessed 30 May 2018.
  15. Glazer-Raymo, J. (2005). Professionalizing graduate education: The master’s degree in the market place. ASHE Higher Education Report, 31(4), 1–137.CrossRefGoogle Scholar
  16. Gujarati, D. N. (2003). Basic econometrics (4th ed.). New York, NY: McGraw-Hill.Google Scholar
  17. McMahon, W. W. (2009). Higher learning, greater good: The private and social benefits of higher education. Baltimore, MD: Johns Hopkins University Press.Google Scholar
  18. National Academies of Sciences, Engineering, & Medicine (2001). From scarcity to visibility: Gender differences in the careers of doctoral scientists and engineers (pp. 101–122). Washington, DC: National Academies Press.  https://doi.org/10.17226/5363
  19. National Academies of Sciences, Engineering, & Medicine (2018). Graduate STEM education in the 21 st century. Washington, DC: National Academies Press.  https://doi.org/10.17226/25038
  20. National Academy of Engineering and National Research Council (2012). Assuring the U.S. Department of Defense a strong science, technology, engineering, and mathematics (STEM) workforce. Washington, DC: National Academies Press.  https://doi.org/10.17226/13467
  21. National Center for Education Statistics (n.d.). National Postsecondary Student Aid Study, 2015–16 [Data file]. Accessed via NCES PowerStats http://nces.ed.gov/datalab/. Accessed 30 May 2018.
  22. National Science Foundation, National Center for Science and Engineering Statistics (2017). Women, minorities, and persons with disabilities in science and engineering: 2017 (Special Report NSF 17–310). Retrieved from www.nsf.gov/statistics/wmpd/. Accessed 13 June 2018.
  23. National Science Foundation, National Science Board (2015). Revisiting the STEM workforce: A companion to Science & Engineering Indicators 2014. (NSB-2015-10). Retrieved from https://www.nsf.gov/pubs/2015/nsb201510/nsb201510.pdf. Accessed 19 April 2017.
  24. National Science Foundation, National Science Board (2018). Science and engineering indicators 2018. (NSB-2018-1). Retrieved from https://www.nsf.gov/statistics/indicators/. Accessed 13 June 2018.
  25. Nordin, M., Persson, I., & Rooth, D. O. (2010). Education–occupation mismatch: Is there an income penalty? Economics of Education Review, 29, 1047–1059.CrossRefGoogle Scholar
  26. Porter, M. E. (2000). Location, competition, and economic development: Local clusters in a global economy. Economic Development Quarterly, 14, 15–34.CrossRefGoogle Scholar
  27. Robst, J. (2007). Education and job match: The relatedness of college major and work. Economics of Education Review, 26, 397–407.CrossRefGoogle Scholar
  28. Sallie Mae & Ipsos. (2017). How America pays for graduate school: Sallie Mae’s national study of graduate school students. Washington, DC: Author. Retrieved from https://www.salliemae.com/assets/Research/HAPGS/HAPGRAD_SchoolReport.pdf. Accessed 13 June 2018.
  29. Scientists and Engineers Statistical Data System, National Science Foundation (2015). National Survey of College Graduates: 2013 [data file]. Retrieved from https://ncsesdata.nsf.gov/datadownload/. Accessed 26 May 2017.
  30. StataCorp (2013). Stata Statistical Software: Release 13. College Station, TX: StataCorp LP.Google Scholar
  31. Titus, M. A. (2007). Detecting election bias, using propensity score matching, and estimating treatment effects: An application to the private returns to a master’s degree. Research in Higher Education, 48, 487–521.CrossRefGoogle Scholar
  32. U.S. Bureau of Labor Statistics (2016). Earnings and unemployment rates by educational attainment, 2015. Retrieved from http://www.bls.gov/emp/ep_chart_001.htm. Accessed 13 June 2018.
  33. U.S. Bureau of Labor Statistics (2018). Educational attainment for workers 25 years and older by detailed occupation. Retrieved from https://www.bls.gov/emp/tables/educational-attainment.htm. Accessed 13 June 2018.
  34. U.S. Department of Education (2015). Student assistance general provisions, Federal Family Education Loan Program, and William D. Ford Federal Direct Loan Program. Federal Register, 80, 39608–39641.Google Scholar
  35. U.S. Department of Education, Office of Innovation and Improvement (2016). STEM 2026: A vision for innovation in STEM education. Washington, DC: Author. Retrieved from https://innovation.ed.gov/files/2016/09/AIR-STEM2026_Report_2016.pdf. Accessed 13 June 2018.
  36. Xu, Y. J. (2013). Career outcomes of STEM and non-STEM college graduates: Persistence in majored-field and influential factors in career choices. Research in Higher Education, 54, 349–382.CrossRefGoogle Scholar
  37. Xue, Y., & Larson, R. (2015, May). STEM crisis or STEM surplus? Yes and yes. Monthly Labor Review. Washington, DC: U.S. Bureau of Labor Statistics.  https://doi.org/10.21916/mlr.2015.14
  38. Rosenbaum, J. E. (1986). Institutional career structures and the social construction of ability. In Richardson, J. (Ed.) Handbook of theory and research for the sociology of education (pp. 139-171). New York, NY: Greenwood.Google Scholar
  39. Paulsen, M. B. (2001). The economics of human capital and investment in higher education. In M. B. Paulsen & J. C. Smart, (Eds.), The finance of higher education: Theory, research, policy, and practice (55-94). New York, NY: Agathon Press.Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Council of Graduate SchoolsWashingtonUSA
  2. 2.College of William & MaryWilliamsburgUSA

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