Earnings of Academic Scientists and Engineers: Intersectionality of Gender and Race/Ethnicity Effects

Abstract

While research increasingly examines the intersection of gender and race/ethnicity in science and engineering, not much is known regarding how they work together to affect career outcomes. This article examines gender earnings gaps among academic scientists and engineers by race/ethnicity. Using data from National Science Foundation’s Survey of Doctorate Recipients (2003, 2006, 2008, 2010, and 2013), I find that White women earned less than their male counterparts in 2003 and 2006, but the earnings gap closed over time. African American women did not earn less than their male counterparts in any year. Asian American women earned less only in 2013 (due to the high income of Asian American men), and Hispanic women earned less only in 2010 (due to their low income relative to other groups). The findings of relative improvement in gender earnings equality are analyzed in the context of disadvantages women face in other aspects of their careers.

Women in economics: a UK perspective

“…In the US, Ceci, et al (2014) use data on the 2010 Survey of Doctorate Recipients show that the gender gap among economics professors is worse than that for professors in Engineering, Geoscience, and Physical Science and associate professors in Life Sciences. Tao (2018) uses several waves of data from the National Science Foundation from 2003 to 2013 to document that women earn about 5 per cent less then men after controlling for demographic, educational, productivity and employment-related characteristics.…”

Pay and Job Rank among Academic Economists in the UK: Is Gender Relevant?

“…This decline is argued to be partly due to improved explanatory variables but may also reflect greater equality in pay setting over time (Ginther and Hayes ). Tao () uses five waves of NSF SDR data (2003, 2006, 2008, 2010 and 2013) to extend the analysis of academic salaries in Science and Engineering. She finds unconditional gaps increase slightly from 14 to 17 per cent but conditional gaps remain stable over the time period at 4–5 per cent.…”

Female Mechanical Engineering Students’ Career Decisions and Development: A Case Study of University Undergraduate Students

“…both interview and focus group activity data). Second, the researcher employed the open-coding technique (Strauss & Corbin, 1990) in order to merge massive data into first-level themes and subthemes. At this stage, 20 themes and 21 subthemes were grouped.…”

“…Third, the researcher continued to employ the axial-coding technique (Strauss & Corbin, 1990) for further data analysis. After the researcher further narrowed down the first-level themes and subthemes.…”