How Do Academic Achievement and Gender Affect the Earnings of STEM Majors? A Propensity Score Matching Approach
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The United States government recently enacted a number of policies designed to increase the number of American born students graduating with degrees in science, technology, engineering and mathematics (STEM), especially among women and racial and ethnic minorities. This study examines how the earnings benefits of choosing a STEM major vary both by gender and across the distribution of academic achievement. I account for the selection into college major using propensity score matching. Measures of individual educational preferences based on Holland’s theory of career and educational choice provide a unique way to control for college major selection. Findings indicate that the earnings benefit to STEM major choice ranges from 5 to 28 % depending both on academic achievement and on gender and that high-achieving students benefit more from STEM major choice. Further, high achieving men benefit more from STEM majors than high-achieving women. Earnings differences in major choice may play an important role in explaining the underrepresentation of women in STEM major fields, especially among high achieving students.
KeywordsSTEM major choice Treatment effects Propensity score matching Earnings
JEL ClassificationI2 J3
I would like to thank ACT Inc. for making their data available to me. In addition, I would like to thank the editor, two anonymous referees, Steve Robbins, Jeff Allen, Paul Westrick and Mark Kurt for their support and comments.
- ACT. (2009). ACT interest inventory technical manual (Vol. 319, pp. 337–1429). Iowa City, IA: ACT, Inc.Google Scholar
- Albrecht, J., Van den Berg, G. J., & Vroman, S. (2005). The knowledge lift: The Swedish adult education program that aimed to eliminate low worker skill levels. IZA Discussion Paper No. 1503 (February). http://ssrn.com/abstract=673516. Accessed 13 Feb 2013.
- Almlund, M., Duckworth, A. L., Heckman, J., & Kautz, T. (2011). Chapter 1. Personality psychology and economics. In S. M. E. A. Hanushek & Woessmann L. (Eds.) Handbook of the economics of education (pp. 1–181). Elsevier. http://www.sciencedirect.com/science/article/pii/B9780444534446000018.
- Arcidiacono, P., Hotz V. J., & Kang, S. (2010). Modeling college major choices using elicited measures of expectations and counterfactuals. Working Paper. National Bureau of Economic Research. http://www.nber.org/papers/w15729. Accessed 6 July 2012.
- Associated Press. (2010). Obama unveils funds to train teachers. Boston Globe, January 7. http://www.boston.com/news/nation/washington/articles/2010/01/07/obama_unveils_funds_to_train_teachers/. Accessed 6 July 2012.
- Becker, S. O., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. Stata Journal, 2(4), 358–377.Google Scholar
- Bryson, A., Dorsett, R., Purdon, S., & Great Britain Department for Work and Pensions. (2002). The use of propensity score matching in the evaluation of active labour market policies. London: Department of Work and Pensions.Google Scholar
- Chen, X., & Weko, T. (2009). Students who study science, technology, engineering and mathematics (STEM) in postsecondary education. US: U.S Department of Education.Google Scholar
- Committee on Prospering in the Global Economy of the 21st Century (U.S.), & Committee on Science and Engineering. (2007). Rising above the gathering storm: Energizing and employing america for a brighter economic future. Washington, DC: National Academies Press.Google Scholar
- Crisp, G., Nora, A., & Taggart, A. (2009). Student characteristics, pre-college, college, and environmental factors as predictors of majoring in and earning a STEM degree: An analysis of students attending a hispanic serving institution. American Educational Research Journal, 46(4), 924–942. doi: 10.3102/0002831209349460.CrossRefGoogle Scholar
- Eccles, J. S. (2007). Where are all the women? Gender differences in participation in physical science and engineering. In S. J. Ceci & W. M. Williams (Eds.) Why aren’t more women in science: Top researchers debate the evidence (pp. 199–210). Washington: American Psychological Association. http://content.apa.org/books/11546-016.
- Gallo, P. J., & Hubschman, B. (2003). The relationships between alumni participation and motivation on financial giving. Chicago, IL: American Educational Research Association.Google Scholar
- Gangl, M. (2004). RBOUNDS: Stata Module to Perform Rosenbaum Sensitivity Analysis for Average Treatment Effects on the Treated. http://ideas.repec.org/c/boc/bocode/s438301.html. Accessed 6 July 2012.
- Graham, S. W., & Gisi, S. L. (2000). The effects of instructional climate and student affairs services on college outcomes and satisfaction. Journal of College Student Development, 41(3), 279–291.Google Scholar
- Hansen, W. Lee, Weisbrod, B. A., & Scanlon, W. J. (1970). Schooling and earnings of low achievers. The American Economic Review, 60(3), 409–418.Google Scholar
- Hecker, D. E. (1996). Earnings and major field of study of college graduates. Occupational Outlook Quarterly.Google Scholar
- Hill, C., Corbett, C., & St. Rose, A. (2010). Why so few? Women in science, technology, engineering, and mathematics. Washington, DC 20036: American Association of University Women. www.aauw.org.
- Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities and work environments. Odessa, FL: Psychological Assessment Resources.Google Scholar
- Honda, M. (2011). STEM Education Innovation Act of 2011, H.R. 3373. http://www.opencongress.org/bill/112-h3373/text. Accessed 6 July 2012.
- King, M., Ruggles, S., Alexander, J. T., Flood S., Genadek, K., Schroeder, M. B., Trampe, B., & Vick, R. (2010). Integrated Public Use Microdata Series, Current Population Survey: Version 3.0. [Machine-readable Database]. Minneapolis: University of Minnesota.Google Scholar
- Levine, J., & Wycokoff, J. (1991). Predicting persistence and success in Baccalaureate engineering. Education, 111(4), 461–468.Google Scholar
- Melguizo, T., & Wolniak G. C. (2011). The earnings benefits of majoring in STEM fields among high achieving minority students. Research in Higher Education (September 1). doi: 10.1007/s11162-011-9238-z. http://www.springerlink.com/index/10.1007/s11162-011-9238-z.
- Mincer, J. (1974). Schooling, experience, and earnings. New York: National Bureau of Economic Research; distributed by Columbia University Press.Google Scholar
- National Science Foundation, Division of Science Resources Statistics. (2009). Women, minorities, and persons with disabilities in science and engineering: 2009. Arlington, VA: National Science Foundation, Division of Science Resources Statistics. http://www.nsf.gov/statistics/wmpd/. Accessed 11 July 2012.
- Pascarella, E. T., & Terenzini. P.T. (2005). How college affects students: A third decade of research. The Jossey-Bass Higher and Adult Education Series. Jossey-Bass. http://books.google.com/books?id=Wn8kAQAAMAAJ. Accessed 6 July 2012.
- Rasmus, L., & Mortensen D. T. (2010). Labor market friction, firm heterogeneity and aggregate employment and productivity. Madison: University of Wisconsin.Google Scholar
- Rosser, S. V. (2004). The science glass ceiling: Academic women scientists and the struggle to succeed. Routledge. http://books.google.com/books?id=-4nlynXNjFQC. Accessed 25 April 2012.
- Seymour, E., & Hewitt, N. (1997). Talking about leaving: Why undergraduates leave the sciences. Boulder, CO: Westview Press.Google Scholar
- Smart, J. C., Feldman, K. A., & Ethington, C. A. (2000). Academic disciplines: Holland’s theory and the study of college students and faculty. Vanderbilt Issues in Higher Education: Vanderbilt University Press.Google Scholar
- Topel, R. (2012). Job mobility, search, and earnings growth: A reinterpretation of human capital earnings functions. In Research in Labor Economics, 35:401–435. Bingley: Emerald Group Publishing. http://www.emeraldinsight.com/10.1108/S0147-9121(2012)0000035038. Accessed 4 Feb 2013.
- Tracey, Terence J. G., Allen, J., & Robbins, S. B. (2012). Moderation of the relation between person–environment congruence and academic success: Environmental constraint, personal flexibility and method. Journal of Vocational Behavior, 80(1), 38–49. doi: 10.1016/j.jvb.2011.03.005.CrossRefGoogle Scholar
- White House. (2009). President Obama Launches “Educate to Innovate” Campaign for Excellence in Science, Technology, Engineering and Math (Stem) Education. The White House. http://www.whitehouse.gov/the-press-office/president-obama-launches-educate-innovate-campaign-excellence-science-technology-en. Accessed 16 Apr 2012.
- White House. (2010). President Obama to Announce Major Expansion of “Educate to Innovate” Campaign to Improve Science, Technology, Engineering and Math (STEM) Education. The White House. http://www.whitehouse.gov/the-press-office/2010/09/16/president-obama-announce-major-expansion-educate-innovate-campaign-impro. Accessed 16 Apr 2012.
- Whitten, B. L., Foster, Suzanne R., Duncombe, Margaret L., Allen, Patricia E., Heron, P., McCullough, L., et al. (2003). What works? Increasing the participation of women in undergraduate physics. Journal of Women and Minorities in Science and Engineering, 9(3–4), 239–258.Google Scholar
- Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data (1st ed.). Cambridge, MA: The MIT Press.Google Scholar