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714 DEMIRALP ET AL. WOMEN’S ENTREPRENEURSHIP IN STEM 715

STEM educations do not, on average, attain equally in STEM (57.0% vs. 58.8%), it varies across different Table 5. Educational Attainment of the Self-Employed Table 7. Educational Attainment of the Self-Employed Women
high degrees as men. For example, men receive more graduate degrees (Table 5). Women who are self-em- in STEM Fields by Gender (2015 ACS) by Field (2015 ACS)
STEM or STEM-related doctoral degrees than women ployed in STEM are more likely to hold a master’s Wome n Men STEM Non-STEM
(16). Women who complete STEM degrees are also degree relative to self-employed men in STEM.
less likely than men to work in careers or sectors that However, they are less likely to hold a professional Self-employed in STEM 307,753 644,230 Self-employed Women 307,753 4,892,542
(Total Count)
(Total Count)
draw on STEM-relevant skill sets (3). or doctoral degree compared to self-employed men
Among students of color, the lower prevalence in STEM. Furthermore, bachelor’s degrees are less Education (%) Education (%)
of women pursuing STEM education is even more prevalent and high school and associate’s degrees are High School or Less 5.2% 3.9% High School or Less 5.2% 32.2%
marked and may represent a critical area of underuti- more prevalent among self-employed women rela- Some College 9.3% 8.4% Some College 9.3% 23.4%
lized human capital. Ong et al. argue that explanations tive to self-employed men in STEM. Associate’s Degree 8.3% 4.4% Associate’s Degree 8.3% 8.7%
for the extant under-representation of women of The results also show that self-employed women Bachelor’s Degree 20.3% 24.4% Bachelor’s Degree 20.3% 22.7%
color in STEM too often rely on the false notion in STEM are more likely to be non-white compared Master’s Degree 18.7% 11.6% Master’s Degree 18.7% 9.0%
that minority women are not interested in STEM to men who are self-employed in STEM (20.9% vs. Professional Degree 28.3% 35.8% Professional Degree 28.3% 2.5%
educations and careers (17). An examination of 16.8%) (Table 6). Asians make up the largest non-
undergraduate women of color in STEM fields argues white group among both women and men who are Doctorate Degree 10.0% 11.4% Doctorate Degree 10.0% 1.5%
that minority women students are more likely to self-employed in STEM (11.9% and 10.7%). Women Source: Authors’ analysis of 2015 American Community Source: Authors’ analysis of 2015 American Community
complete STEM majors when external assurances who are self-employed in STEM fields are also more Survey obtained from the IPUMS-USA database. Survey obtained from the IPUMS-USA database.

are present; specifically, degree completion increases likely to be black or African American (5.2% vs. Note: STEM fields are defined based on occupation Note: STEM fields are defined based on occupation
when minority women students have a supportive 3.2%) or other race (3.8% vs. 3.0%) relative to men. codes and include the following: Computer and Mathe- codes and include the following: Computer and Mathe-
matical Occupations, Architecture and Engineering
matical Occupations, Architecture and Engineering
collegiate environment, strong academic peer rela- Furthermore, a greater percentage of self-employed Occupations, Life and Physical Sciences Occupations, Occupations, Life and Physical Sciences Occupations,
tionships, and research program involvement (18). women in STEM are Hispanic relative to men (6.5% Health Occcupations. Health Occcupations.
Examining female African American students specif- vs. 5.5%).
ically, few programs that promote the psychological Compared to self-employed women in non-STEM
readiness of students or preparedness to conduct fields, self-employed women in STEM fields are older
research in non-minority-dominated fields have been (49 vs. 48) and more likely to be married (67% vs. Table 6. Race and Ethnicity of the Self-Employed in STEM Table 8. Race and Ethnicity of Self-Employed Women by
Field (2015 ACS)
Fields by Gender (2015 ACS)
demonstrated to be effective (19). 61%). As explained above, however, the average age

and likelihood to be married among self-employed Wom en Men STEM Non-STEM
OWNER CHARACTERISTICS OF WOMEN- women in STEM is lower than that for self-employed Self-employed in STEM 307,753 644,230 Self-employed in STEM 307,753 4,892,542
OWNED STEM BUSINESSES men in STEM. The analysis results reveal large dif- (Total Count) (Total Count)
This section presents results from the analysis of ferences between STEM and non-STEM women Race (%) Race (%)
2015 ACS and 2007 SBO data to examine the char- entrepreneurs in terms of educational attainment White 79.1% 83.2% White 79.1% 80.2%
acteristics of business owners across genders and (Table 7). The majority of self-employed women in Black or African American 5.2% 3.2% Black or African American 5.2% 6.2%

STEM and non-STEM fields. The analysis is aimed STEM fields (57%) have a graduate degree, while Asian 11.9% 10.7% Asian 11.9% 6.3%
to provide insight into the potential factors associ- 13% of self-employed women in non-STEM fields Other 3.8% 3.0% Other 3.8% 7.3%
ated with STEM entrepreneurship among women. have a similar degree. In contrast, more than half of Hispanic (%) 6.5% 5.5% Hispanic (%) 6.5% 15.5%
self-employed women in non-STEM fields have at

American Community Survey Analysis Results most a high school degree (including some college) Source: Authors’ analysis of 2015 American Community Source: Authors’ analysis of 2015 American Community
The analysis of 2015 ACS data reveals differences (55.6%), while only 14.45% of self-employed women Survey obtained from the IPUMS-USA database. Survey obtained from the IPUMS-USA database.
between self-employed men and women in STEM as in STEM fields have similar educational attainment. Note: STEM fields are defined based on occupation Note: STEM fields are defined based on occupation
well as between self-employed women in STEM and These findings underscore the important role that codes and include the following: Computer and Mathe- codes and include the following: Computer and Mathe-
non-STEM fields. First, the results show that self-em- higher education plays in STEM entrepreneurship. matical Occupations, Architecture and Engineering matical Occupations, Architecture and Engineering
Occupations, Life and Physical Sciences Occupations,
Occupations, Life and Physical Sciences Occupations,
ployed women in STEM are slightly younger than Racial distribution of self-employed women in Health Occupations. Other races include American Health Occupations. Other races include American
self-employed men in STEM (49 vs. 52). Second, they STEM and non-STEM fields reveals that the preva- Indian/Alaska Native, other race not elsewhere classified, Indian/Alaska Native, other race not elsewhere classified,
are less likely to be married compared to self-em- lence of minority entrepreneurship is similar in both and individuals with two or more major races. and individuals with two or more major races.
ployed men in STEM (67% vs. 76%). groups (Table 8). Among self-employed women in
While the frequency of graduate degree holders STEM, 20.9% are likely to be non-white compared to
is similar between self-employed men and women 19.8% among self-employed women in non-STEM