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Heterogeneous Major Preferences for Extrinsic Incentives: The Effects of Wage Information on the Gender Gap in STEM Major Choice

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Abstract

Despite the growing evidence of informational interventions on college and major choices, we know little about how such light-touch interventions affect the gender gap in STEM majors. Linking survey data to administrative records of Chinese college applicants, we conducted a large-scale randomized experiment to examine the STEM gender gap in the major preference beliefs, application behaviors, and admissions outcomes. We find that female students are less likely to prefer, apply to, and enroll in STEM majors, particularly Engineering majors. In a school-level cluster randomized controlled trial, we provided treated students with major-specific wage information. Students’ major preferences are easily malleable that 39% of treated students updated their preferences after receiving the wage informational intervention. The wage informational intervention has no statistically significant impacts on female students’ STEM-related major applications and admissions. In contrast, those male students in rural areas who likely lack such information are largely shifted into STEM majors as a result of the intervention. We provide supporting evidence of heterogeneous major preferences for extrinsic incentives: even among those students who are most likely to be affected by the wage information (prefer high paying majors and lack the wage information), female students are less responsive to the informational intervention.

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References

  • Acton, R. (2020). Community college program choices in the wake of local job losses. Journal of Labor Economics.

  • Altonji, J. G., Arcidiacono, P., & Maurel, A. (2016). The analysis of field choice in college and graduate school: Determinants and wage effects. Handbook of the Economics of Education volume 5. (pp. 305–396). Elsevier.

    Google Scholar 

  • Arcidiacono, P. (2004). Ability sorting and the returns to college major. Journal of Econometrics, 121(1–2), 343–375

    Article  Google Scholar 

  • Arcidiacono, P., Hotz, V. J., & Kang, S. (2012). Modeling college major choices using elicited measures of expectations and counterfactuals. Journal of Econometrics, 166(1), 3–16

    Article  Google Scholar 

  • Arcidiacono, P., Hotz, V. J., Maurel, A., & Romano, T. (2020). Ex ante returns and occupational choice. Journal of Political Economy, 128(12), 4475–4522

    Article  Google Scholar 

  • Baker, R., Bettinger, E., Jacob, B., & Marinescu, I. (2018). The effect of labor market information on community college students’ major choice. Economics of Education Review, 65, 18–30

    Article  Google Scholar 

  • Beffy, M., Fougere, D., & Maurel, A. (2012). Choosing the field of study in postsecondary education: Do expected earnings matter? Review of Economics and Statistics, 94(1), 334–347

    Article  Google Scholar 

  • Berger, M. C. (1988). Predicted future earnings and choice of college major. ILR Review, 41(3), 418–429

    Article  Google Scholar 

  • Blagg, K., Chingos, M. M., Graves, C., & Nicotera, A. (2017). Rethinking consumer information in higher education. Urban Institute.

  • Bobbitt-Zeher, D. (2007). The gender income gap and the role of education. Sociology of Education, 80(1), 1–22

    Article  Google Scholar 

  • Bordón, P., Canals, C., & Mizala, A. (2020). The gender gap in college major choice in Chile. Economics of Education Review, 77, 102011

    Article  Google Scholar 

  • Bordón, P., & Fu, C. (2015). College-major choice to college-then-major choice. Review of Economic Studies, 82(4), 1247–1288

    Article  Google Scholar 

  • Breske, S., Koedel, C., & Parsons, E. (2019). Field interest and the choice of college major. Working paper.

  • Buckles, K. (2019). Fixing the leaky pipeline: Strategies for making Economics work for women at every stage. Journal of Economic Perspectives, 33(1), 43–60

    Article  Google Scholar 

  • Card, D., & Payne, A. A. (2021). High school choices and the gender gap in STEM. Economic Inquiry, 59(1), 9–28

    Article  Google Scholar 

  • Castleman, B. L., Long, B. T., & Mabel, Z. (2018). Can financial aid help to address the growing need for stem education? The effects of need-based grants on the completion of Science, Technology, Engineering, and Math courses and degrees. Journal of Policy Analysis and Management, 37(1), 136–166

    Article  Google Scholar 

  • Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35

    Article  Google Scholar 

  • Chipman, S. F., & Thomas, V. G. (1987). The participation of women and minorities in mathematical, scientific, and technical fields. Review of Research in Education, 14(1), 387–430

    Article  Google Scholar 

  • Conlon, J.J., 2019. Major malfunction: A field experiment correcting undergraduates’ beliefs about salaries. Journal of Human Resources, pp.0317-8599R2.

  • 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

    Article  Google Scholar 

  • Denning, J. T., & Turley, P. (2017). Was that SMART? Institutional financial incentives and field of study. Journal of Human Resources, 52(1), 152–186

    Article  Google Scholar 

  • Evans, B. J. (2017). SMART money: Do financial incentives encourage college students to study science? Education Finance and Policy, 12(3), 342–368

    Article  Google Scholar 

  • Freeman, J. A., & Hirsch, B. T. (2008). College majors and the knowledge content of jobs. Economics of Education Review, 27(5), 517–535

    Article  Google Scholar 

  • Fricke, H., Grogger, J., & Steinmayr, A. (2018). Exposure to academic fields and college major choice. Economics of Education Review, 64, 199–213

    Article  Google Scholar 

  • Ganley, C. M., George, C. E., Cimpian, J. R., & Makowski, M. B. (2018). Gender equity in college majors: Looking beyond the STEM/non-STEM dichotomy for answers regarding female participation. American Educational Research Journal, 55(3), 453–487

    Article  Google Scholar 

  • Gemici, A., & Wiswall, M. (2014). Evolution of gender differences in post-secondary human capital investments: College majors. International Economic Review, 55(1), 23–56

    Article  Google Scholar 

  • Griffith, A. L. (2010). Persistence of women and minorities in STEM field majors: Is it the school that matters? Economics of Education Review, 29(6), 911–922

    Article  Google Scholar 

  • Gurantz, O., Howell, J., Hurwitz, M., Larson, C., Pender, M., & White, B. (2020). A national‐level informational experiment to promote enrollment in selective colleges. Journal of Policy Analysis and Management.

  • Han, L., & Winters, J. V. (2020). Industry fluctuations and college major choices: Evidence from an energy boom and bust. Economics of Education Review, 77, 101996.

  • Hastings, J. S., Neilson, C. A., Ramirez, A., & Zimmerman, S. D. (2016). (Un) informed college and major choice: Evidence from linked survey and administrative data. Economics of Education Review, 51, 136–151

    Article  Google Scholar 

  • Hastings, J., Neilson, C. A., & Zimmerman, S. D. (2015). The effects of earnings disclosure on college enrollment decisions (No. w21300). National Bureau of Economic Research.

  • Hurwitz, M., & Smith, J. (2018). Student responsiveness to earnings data in the College Scorecard. Economic Inquiry, 56(2), 1220–1243

    Article  Google Scholar 

  • Jacob, B., McCall, B., & Stange, K. (2018). College as country club: Do colleges cater to students’ preferences for consumption? Journal of Labor Economics, 36(2), 309–348

    Article  Google Scholar 

  • Jensen, R. (2010). The (perceived) returns to education and the demand for schooling. The Quarterly Journal of Economics, 125(2), 515–548

    Article  Google Scholar 

  • Kahn, S., & Ginther, D. (2017). Women and STEM (No. w23525). National Bureau of Economic Research.

  • Kanny, M. A., Sax, L. J., & Riggers-Piehl, T. A. (2014). Investigating forty years of STEM research: How explanations for the gender gap have evolved over time. Journal of Women and Minorities in Science and Engineering, 20(2), 127–148

    Article  Google Scholar 

  • Kerr, S. P., Pekkarinen, T., Sarvimäki, M., & Uusitalo, R. (2020). Post-secondary education and information on labor market prospects: A randomized field experiment. Labour Economics, 66, 101888.

  • Kesar, S. (2017). Closing the STEM Gap: Why STEM Classes and Career Still Lack Girls and What We Can Do About it. Microsoft.

  • Kim, C., Tamborini, C. R., & Sakamoto, A. (2015). Field of study in college and lifetime earnings in the United States. Sociology of Education, 88(4), 320–339

    Article  Google Scholar 

  • Kinsler, J., & Pavan, R. (2015). The specificity of general human capital: Evidence from college major choice. Journal of Labor Economics, 33(4), 933–972

    Article  Google Scholar 

  • Krussig, T., & Neilson, C. (2021). The rise of centralized choice and assignment mechanisms in education markets around the world. Working paper.

  • Kugler, A. D., Tinsley, C. H., and Ukhaneva, O. (2017). Choice of majors: Are women really different from men? (No. w23735). National Bureau of Economic Research.

  • Loewenstein, G., Sunstein, C. R., & Golman, R. (2014). Disclosure: Psychology changes everything. Annual Review of Economics, 6(1), 391–419

    Article  Google Scholar 

  • Long, B. T. (2004). How have college decisions changed over time? An application of the conditional logistic choice model. Journal of Econometrics, 121(1–2), 271–296

    Article  Google Scholar 

  • Long, M. C., Goldhaber, D., & Huntington-Klein, N. (2015). Do completed college majors respond to changes in wages? Economics of Education Review, 49, 1–14

    Article  Google Scholar 

  • Mabel, Z., Libassi, C. J., & Hurwitz, M. (2020). The value of using early-career earnings data in the College Scorecard to guide college choices. Economics of Education Review, 75, 101958

    Article  Google Scholar 

  • Mann, A., & DiPrete, T. A. (2013). Trends in gender segregation in the choice of science and engineering majors. Social Science Research, 42(6), 1519–1541

    Article  Google Scholar 

  • McNally, S. (2020). Gender differences in tertiary education: what explains STEM participation. IZA Policy Paper No. 165.

  • Melguizo, T., & Wolniak, G. C. (2012). The earnings benefits of majoring in STEM fields among high achieving minority students. Research in Higher Education, 53(4), 383–405

    Article  Google Scholar 

  • Montmarquette, C., Cannings, K., & Mahseredjian, S. (2002). How do young people choose college majors? Economics of Education Review, 21(6), 543–556

    Article  Google Scholar 

  • Mostafa, T. (2019). Why don’t more girls choose to pursue a science career?. PISA in Focus, No. 93, OECD Publishing, Paris, Doi:https://doi.org/10.1787/02bd2b68-en.

  • Mouganie, P., & Wang, Y. (2020). High-performing peers and female STEM choices in school. Journal of Labor Economics, 38(3), 805–841

    Article  Google Scholar 

  • Page, L. C., & Scott-Clayton, J. (2016). Improving college access in the United States: Barriers and policy responses. Economics of Education Review, 51, 4–22

    Article  Google Scholar 

  • Patnaik, A., Wiswall, M. J., & Zafar, B. (2020). College majors. NBER Working Paper w27645.

  • Perna, L. W. (2006). Studying college access and choice: A proposed conceptual model. Higher education. (pp. 99–157). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Rask, K. (2010). Attrition in STEM fields at a liberal arts college: The importance of grades and pre-collegiate preferences. Economics of Education Review, 29(6), 892–900

    Article  Google Scholar 

  • Reuben, E., Wiswall, M., & Zafar, B. (2017). Preferences and biases in educational choices and labour market expectations: Shrinking the black box of gender. The Economic Journal, 127(604), 2153–2186

    Article  Google Scholar 

  • Riegle-Crumb, C., & King, B. (2010). Questioning a white male advantage in STEM: Examining disparities in college major by gender and race/ethnicity. Educational Researcher, 39(9), 656–664

    Article  Google Scholar 

  • Simpson, J. C. (2001). Segregated by subject: Racial differences in the factors influencing academic major between European Americans, Asian Americans, and African, Hispanic, and Native Americans. Journal of Higher Education, 72(1), 63–100

    Google Scholar 

  • Sloane, C., Hurst, E., & Black, D. (2019). A cross-cohort analysis of human capital specialization and the college gender wage gap (No. w26348). National Bureau of Economic Research.

  • Soldner, M., Rowan-Kenyon, H., Inkelas, K. K., Garvey, J., & Robbins, C. (2012). Supporting students’ intentions to persist in STEM disciplines: The role of living-learning programs among other social-cognitive factors. Journal of Higher Education, 83(3), 311–336

    Article  Google Scholar 

  • Speer, J. D. (2017). The gender gap in college major: Revisiting the role of pre-college factors. Labour Economics, 44, 69–88

    Article  Google Scholar 

  • Speer, J. D. (2020). Bye Bye Ms. American Sci: Women and the leaky STEM pipeline. Working paper.

  • Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.

    Google Scholar 

  • Turner, S. E., & Bowen, W. G. (1999). Choice of major: The changing (unchanging) gender gap. ILR Review, 52(2), 289–313

    Article  Google Scholar 

  • United Nations Educational, Scientific and Cultural Organization. (2015). UNESCO Science Report: Towards 2030.

  • Wang, X. (2013). Why students choose STEM majors: Motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5), 1081–1121

    Article  Google Scholar 

  • Watt, H. M., Shapka, J. D., Morris, Z. A., Durik, A. M., Keating, D. P., & Eccles, J. S. (2012). Gendered motivational processes affecting high school mathematics participation, educational aspirations, and career plans: A comparison of samples from Australia, Canada, and the United States. Developmental Psychology, 48(6), 1594

    Article  Google Scholar 

  • Wiswall, M., & Zafar, B. (2014). Determinants of college major choice: Identification using an information experiment. The Review of Economic Studies, 82(2), 791–824

    Article  Google Scholar 

  • Wiswall, M., & Zafar, B. (2015). How do college students respond to public information about earnings? Journal of Human Capital, 9(2), 117–169

    Article  Google Scholar 

  • Wiswall, M., & Zafar, B. (2018). Preference for the workplace, investment in human capital, and gender. The Quarterly Journal of Economics, 133(1), 457–507

    Article  Google Scholar 

  • Wiswall, M., & Zafar, B. (2021). Human capital investments and expectations about career and family. Journal of Political Economy, 129(5), 1361–1424

    Article  Google Scholar 

  • World Bank. (2019). Improving the pathway from school to STEM careers for girls and women. Retrieved from https://blogs.worldbank.org/opendata/improving-pathway-school-stem-careers-girls-and-women

  • Xie, Y., & Shauman, K. A. (2003). Women in science: Career processes and outcomes. Harvard University Press,

  • Yue, C. (2015). Expansion and equality in Chinese higher education. International Journal of Educational Development, 40, 50–58

    Article  Google Scholar 

  • Zafar, B. (2013). College major choice and the gender gap. Journal of Human Resources, 48(3), 545–595

    Article  Google Scholar 

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Acknowledgements

We thank Will Doyle (the editor), two anonymous referees, for their insightful comments, Wei Li (Ningxia University), Bingqing Dai and Wei Geng (Ningxia Department of Education) for their extraordinary effort in initiating the project, a team of research assistants (Si Chen, Honghui Li, Fengming Lu, Le Kang, Qiongqiong Wang) and partners for the Bright Future of China Project. We also thank the Institute of Economics of Education at Peking University and Ningxia Department of Education for providing the data used in this paper. This project would simply not have been possible without approval and collaboration from Ningxia Department of Education. Yan Zhang has been a great help with data. This research was made possible with generous funding from China NSF (71673013) and China Ministry of Education (16JJD880001). The research was approved by the University of Michigan IRB (HUM00127559). Equal authorship applies. All errors and omissions are our own.

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Authors and Affiliations

  1. Institute of Economics of Education, Graduate School of Education, Peking University, Beijing, China

    Yanqing Ding, Yinduo Wu & Jin Yang

  2. University of Florida, Gainesville, FL, USA

    Wei Li

  3. UCLA, Los Angeles, CA, USA

    Xin Li

  4. Institute of Education Economics and Management, University of Science and Technology Beijing, Beijing, China

    Jin Yang

  5. Annenberg Institute for School Reform, Brown University, Box 1985, Providence, RI, 02912, USA

    Xiaoyang Ye

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Ding, Y., Li, W., Li, X. et al. Heterogeneous Major Preferences for Extrinsic Incentives: The Effects of Wage Information on the Gender Gap in STEM Major Choice. Res High Educ 62, 1113–1145 (2021). https://doi.org/10.1007/s11162-021-09636-w

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