Analytical Studies Branch Research Paper Series
A Gender Analysis of the Occupational Pathways of STEM Graduates in Canada

by Kristyn Frank

11F0019M No. 429
Release date: September 16, 2019

Acknowledgements

This study was funded by the Department for Women and Gender Equality. The author appreciates the constructive comments provided by reviewers from the Department for Women and Gender Equality and colleagues at Statistics Canada.

Abstract

Occupations related to science, technology, engineering and mathematics (STEM) are generally associated with high pay and contribute to the development of new technology. Continued growth is expected for STEM occupations, which would provide STEM-educated workers with additional labour market opportunities. However, less is known about the extent to which STEM graduates enter into and remain in STEM occupations in Canada. This study uses data from the 2006 and 2016 longitudinal census files to examine the occupational pathways of women and men with postsecondary credentials in STEM fields. Generally, male STEM graduates were more likely than female STEM graduates to be employed in a STEM occupation. The occupational pathways of male and female STEM graduates also differed. Among STEM graduates who were employed in a STEM occupation in 2006, women were more likely than men to have moved to a non-STEM occupation by 2016. Younger STEM graduates were more likely to exit a STEM occupation than older graduates, and men and women with college-level STEM credentials were more likely to leave a STEM occupation than their counterparts with a bachelor’s degree. Some differences in the occupational mobility of men and women with STEM credentials were associated with their field of study. For example, men who studied mathematics or computer and information sciences were less likely than their counterparts who studied engineering or engineering technology to exit a STEM occupation between 2006 and 2016. However, there was no statistically significant difference in the likelihood of leaving a STEM occupation among women who had studied in these two fields. Lastly, the wage growth of male and female STEM graduates who persisted in a STEM occupation between 2006 and 2016 was not significantly different from the wage growth of their counterparts who had moved from a STEM occupation to a non-STEM occupation.

Executive summary

Occupations related to science, technology, engineering and mathematics (STEM) are often characterized as high-quality, high-paying jobs. Continued growth is expected for STEM occupations, which suggests that there will be greater demand for STEM-educated workers in the future. Increasing women’s participation in STEM fields has been identified as one way of meeting the growing demand for STEM-trained workers. However, despite increases in women’s educational attainment and participation in scientific occupations over the past several decades, women remain underrepresented in STEM fields.

Much of the research on women in STEM fields concentrates on “leaks” in the STEM pipeline throughout their educational training. However, less is known about the loss of women from STEM after they obtain STEM credentials and how this compares with their male peers.

This study uses data from the 2006 and 2016 longitudinal census files, which integrate individuals across census years. A gender-based approach is employed to investigate the occupational pathways of women and men with postsecondary credentials in STEM fields who were aged 25 to 54 in 2006. This study addresses the following research questions:

  1. What are the occupational pathways of STEM graduates in Canada and do the pathways of men and women differ?
  2. What sociodemographic and educational characteristics are associated with the likelihood of a STEM graduate exiting a STEM occupation? Are there differences between men and women?
  3. Do the earnings of STEM graduates who persist in STEM occupations differ from their counterparts who move to non-STEM occupations? Does this differ between men and women?

Generally, male STEM graduates were more likely than female STEM graduates to be employed in a STEM occupation. While over 4 in 10 men in the longitudinal sample were employed in STEM occupations in 2006, less than 3 in 10 women worked in a STEM occupation. Previous research has found that engineering graduates are more likely than life science graduates to work in STEM occupations (Statistics Canada 2017a). Over one-third of women in the longitudinal sample had studied biological, general or integrated sciences, while more than half of men had studied engineering or engineering technology. Therefore, it is likely that the differences observed in men’s and women’s likelihood of working in a STEM occupation is partly attributable to differences in their specific field of study choices.

Furthermore, the occupational mobility of male and female STEM graduates differed—women with STEM credentials were less likely than their male counterparts to persist in STEM occupations between 2006 and 2016. About one-quarter (26.4%) of male STEM graduates who were employed in a STEM occupation in 2006 had moved to a non-STEM occupation by 2016, compared with more than one-third of women (34.7%). Some of the top non-STEM occupations to which STEM graduates moved were similar for both men and women, such as specialized middle management occupations and professional occupations in business and finance.

Generally, most sociodemographic characteristics were not associated with the likelihood of men or women exiting STEM occupations, but with one exception—younger graduates were more likely to exit these fields than older graduates. Furthermore, STEM graduates with college-level credentials were more likely to exit a STEM occupation than their counterparts with a bachelor’s degree.

Graduates who studied engineering and engineering technology were less likely to leave STEM occupations between 2006 and 2016 than graduates of physical or chemical sciences or biological, general or integrated sciences. This was observed for both men and women. However, there were differences in the occupational mobility of men and women who studied mathematics or computer and information sciences. While men who studied mathematics or computer and information sciences were less likely than their counterparts who studied engineering or engineering technology to leave a STEM occupation between 2006 and 2016, there was no statistically significant difference between women who had studied these two fields.

Lastly, the results indicated that the wage growth of women and men who persisted in a STEM occupation between 2006 and 2016 was not significantly different from the wage growth of their counterparts who had moved from a STEM occupation to a non-STEM occupation between these years. Therefore, while STEM occupations may be higher paying than non-STEM occupations on average, STEM graduates who exited a STEM occupation did not experience significantly lower wage growth than their peers who persisted in a STEM occupation.

1 Introduction

Occupations related to science, technology, engineering and mathematics (STEM) are often characterized as high-quality, high-paying jobs that foster innovation and the development of new technology (Landivar 2013). Continued growth is expected for STEM occupations, which suggests that there will be an increase in labour market opportunities for STEM-educated workers (Diekman, Weisgram and Belanger 2015). However, the extent to which STEM graduates enter into and remain in STEM occupations in Canada is largely unknown. Moreover, if the demand for STEM-educated workers increases, there will also be a rise in concerns about the retention of these workers in STEM occupations.

Increasing women’s participation in STEM fields is one way that the growing demand for STEM-educated workers can be met. Greater representation of women in STEM has also been identified as a way to make Canada more competitive in the global economy and fully take advantage of women’s skills (Council of Canadian Academies 2015), as well as address the gender pay gap, as these occupations tend to be well paid. However, despite increases in women’s educational attainment and participation in scientific occupations over the past several decades (Dionne-Simard, Galarneau and LaRochelle-Côté 2016; Turcotte 2011), women remain underrepresented in STEM fields.

Previous research examining gender differences in STEM is largely focused on the extent to which women obtain educational credentials in STEM fields of study (e.g., Hango 2013; Ferguson 2016) and issues of attrition throughout their training (e.g., Chen 2015; George-Jackson 2011; Maltese and Tai 2011; Miller and Wai 2015; Wall 2019). Although some researchers note that “leaks” in the STEM pipeline can occur at different stages of women’s lives, less is known about the loss of women from STEM occupations after they obtain STEM credentials (Blickenstaff 2005; Cech and Blair-Loy 2019; Dasgupta and Stout 2014).

These issues can be addressed with longitudinal data, which make it possible to analyze individuals over time. While some longitudinal analyses have compared the earnings of men and women in STEM and non-STEM occupations (Xu 2015), information about the occupational pathways of STEM graduates is lacking. This is particularly true in the Canadian context, where few researchers have examined the occupational mobility of women with STEM credentials and how their pathways compare with those of men.

This study used data from the longitudinal census files to examine the occupational pathways of men and women with STEM credentials between 2006 and 2016 who were aged 25 to 54 in 2006. Sex-disaggregated statistics were used in a gender-based approach to analyze the occupational stability or mobility of STEM graduates. The following research questions were addressed:

  1. What proportion of STEM graduates worked in STEM occupations or non-STEM occupations or were not in the labour force in 2006 and 2016? Was there a gap in the proportion of women and men who worked in STEM occupations in 2006 and, if so, did that gap increase or decrease between 2006 and 2016?
  2. Among STEM graduates who were employed in 2006, were certain sociodemographic or educational characteristics associated with a greater likelihood of working in a STEM occupation?
  3. What were the occupational pathways of STEM graduates who were employed in both 2006 and 2016 (i.e., persisted in a STEM occupation, exited a STEM occupation, entered a STEM occupation or did not work in a STEM occupation in either year)? Did the occupational pathways of men and women vary?
  4. Among STEM graduates who were employed in a STEM occupation in 2006, what proportion moved to a non-STEM occupation by 2016? Were certain sociodemographic or educational characteristics associated with exiting a STEM occupation or persisting in a STEM occupation?
  5. Among STEM graduates who exited a STEM occupation between 2006 and 2016, what were the top STEM occupations that they left and what were the top non-STEM occupations to which they moved?
  6. Accounting for sociodemographic and educational differences, was the wage growth of STEM graduates who persisted in STEM occupations between 2006 and 2016 greater than that of their counterparts who moved to non-STEM occupations?

This paper is organized as follows. Section 2 provides an overview of the previous research on STEM graduates and workers. The data and measures are reviewed in Section 3. The study results are presented in Section 4, and Section 5 concludes with a discussion of the findings.

2 The representation of women and men in STEM fields

Although women now account for the majority of university graduates, they are less likely than men to hold a degree in a STEM field of study (Ferguson 2016).Note  According to the 2016 Census, about one-quarter (24.8%) of bachelor’s degree holders between the ages of 25 and 54 had studied in a STEM program. Over one-third of men (37.5%) with a bachelor’s degree had studied in a STEM field, compared to 15.3% of women with a bachelor’s degree. Similar results were found among college graduates: 3 in 10 men (30.0%) had studied in a STEM field, while less than 1 in 10 (6.7%) women had studied in a STEM field.Note 

Several explanations for women’s lower likelihood of selecting a STEM field of study or persisting in it have been advanced, including cultural pressures related to stereotypical gender roles (e.g., parental expectations and peer norms), a lack of self-confidence in STEM-related subjects, a lack of female role models, and preferences and interests (Blickenstaff 2005; Dasgupta and Stout 2014; White and Massiha 2016).

The 2016 Census data also indicate that the specific STEM fields of study differed for men and women. While over half of men with a STEM bachelor’s degree studied engineering or engineering technology (52.2%), only one-quarter of women with a STEM degree had studied in this field (25.3%). The majority of women (54.1%) who had a bachelor’s degree in a STEM field had studied in science or science technology programs. The difference in the proportion of men and women with a STEM degree who had studied mathematics or computer and information sciences was less pronounced (23.8% of men and 20.6% of women).Note 

The differences in choice of STEM field of study among men and women may be associated with their likelihood of working in a STEM occupation. Canadian research has shown that among young STEM graduates (aged 25 to 34), men were more likely than women to work in STEM occupations (Statistics Canada 2017a). This was partly attributable to STEM graduates’ specific field of study. For example, engineering graduates were more likely than biological science graduates to work in a STEM occupation. Previous research also indicates that young engineering graduates were largely concentrated in engineering occupations, while physical and life science graduates tended to work across a wider range of occupations, many of which were non-STEM occupationsNote  (Frenette and Frank 2017). Therefore, since a higher proportion of women with STEM credentials studied life sciences than men (and, conversely, a higher proportion of male STEM graduates studied engineering than female STEM graduates), the likelihood of working in a STEM occupation is expected to differ between women and men.

Increasing female representation in high-paying occupations has been identified as a way to reduce the gender pay gap (Lemieux and Riddell 2015). Considering that STEM occupations are generally high paying (Xu 2015), gender differences in the likelihood of STEM graduates working in a STEM occupation may have an impact on women’s economic well-being. However, previous research has found that the positions held by women in some STEM fields are lower paying than the ones held by their male counterparts (Broyles 2009). Therefore, while increased female representation in STEM occupations may improve women’s overall economic standing, they may still encounter gender pay differences within these occupations. Furthermore, women who are among the top 1% of earners in Canada were primarily concentrated in health occupations rather than STEM occupations (Richards 2019), indicating that women with STEM credentials may also prosper in non-STEM occupations.  

Individuals who work in jobs that are closely related to their field of study have been found to have better career outcomes than those who do not (Xu 2013). Recent Canadian research concluded that over half of young graduates with a bachelor’s degree in a STEM field worked in a STEM occupation in 2016 (Statistics Canada 2017b).Note  This was primarily driven by men, who tend to select fields of study associated with a greater likelihood of working in STEM occupations than women, as discussed above. However, employment in a non-STEM occupation is not necessarily an indication that STEM graduates encountered difficulties in obtaining employment in a STEM occupation. The skills developed within STEM programs can be applied to a range of occupations, which gives STEM graduates many labour market options (Council of Canadian Academies 2015). Additionally, some STEM graduates may work in management-level positions in non-STEM occupations or prefer non-STEM jobs.

Researchers and policy makers have raised concerns about the persistence of women in STEM careers, suggesting that women’s employment in STEM occupations is not static over time (Glass et al. 2013; Mavriplis et al. 2010; Mortillaro 2018). Glass et al. (2013) found that women in STEM occupations moved to non-STEM occupations at high rates and generally did not return after leaving. Studies analyzing the employment interruptions of women in STEM occupations found that barriers arose for those who sought to return to STEM occupations later in life. For example, Dasgupta and Stout (2014, 26) noted that the career gaps of women seeking to re-enter STEM occupations may be deemed problematic by potential employers who believe that their STEM-related skills have become “rusty” or outdated. Furthermore, a loss of professional networks may hinder women from returning to STEM careers after time away. However, both women and men may face similar challenges after leaving a STEM occupation.

A report by Engineers Canada and Geoscientists Canada (2016) found that difficulties in retaining workers in STEM fields were often related to career progression obstacles following maternity or parental leaves of absence. However, women are more likely to experience career interruptions because of parenthood and often cite different reasons for leaving their fields than men, including family obligations, a lack of mentoring or guidance, a lack of flexible work hours, and the perception that science- and engineering-oriented workplaces are “unfriendly to women” (Blickenstaff 2005; Dasgupta and Stout 2014; Mavriplis et al. 2010; Preston 2004, 30). Researchers in the United States found that 42% of women left full-time STEM occupations within three years of having their first child, compared with 15% of new fathers (Cech and Blair-Loy 2019). The study also found that both new mothers and new fathers were more likely to move out of STEM occupations than their childless peers, and most did not move back into these occupations when their children reached school age. Additionally, the attrition of new mothers and fathers was not found to be driven by a specific STEM field, suggesting that this “may be a feature of STEM more broadly” (Cech and Blair-Loy 2019, 4).

3 Data and measures

This study uses the 2006 and 2016 longitudinal census files, which link individuals across the two census years. For this study, only women and men who responded to both the 2006 and 2016 census long-form questionnaires were included in the sample.Note  As a result, there could be differences between this sample and the general population. To minimize concerns about this limitation, survey weights from the 2006 Census were applied. Descriptive analyses were also conducted to compare key characteristics of the weighted longitudinal sample with the weighted 2006 Census sample. Across most characteristics, the two samples differed by less than 1 percentage point. In particular, differences between the samples were narrow for STEM fields of study, education level, visible minority status, Aboriginal identity and employment in a STEM occupation.Note 

The longitudinal sample was limited to Canadian-born and immigrant individuals aged 25 to 54 in 2006 who completed a college, CEGEP or other non-university certificate or diploma or university certificate below a bachelor’s degree, or a university degree (bachelor’s degree or above) in a STEM field of study.Note  This age range was selected to include people of prime working age over the 10-year period studied.Note  Furthermore, only those who reported the same level of education in 2006 and 2016 were included to minimize the possibility of including individuals who obtained additional educational credentials in non-STEM programs over this period. These restrictions resulted in a sample size of 48,271 (33,686 men and 14,585 women). Sample restrictions varied across different analytical sections because of the specific questions being addressed. Details about each of these samples are addressed in the results section.

Two key variables in this study are field of study and occupation. Statistics Canada’s (2018) STEM field of study classification was used to assign the field of study of each respondent’s highest certificate, diploma or degree (in 2006) to a STEM group. Some STEM groups were combined to ensure adequate sample sizes for more detailed descriptive analyses, resulting in four STEM fields: (a) physical and chemical sciences; (b) biological, general and integrated sciences; (c) engineering and engineering technology; and (d) mathematics and computer and information sciences.

The classification of STEM occupations follows Picot and Hou’s (2018; forthcoming) work, which provides a consistent categorization of STEM occupations over several census years. Appendix Table 1 provides a detailed list of STEM occupations and their corresponding 2006 National Occupational Classification for Statistics (NOC-S 2006) and 2016 National Occupational Classification (NOC 2016) codes. Generally, this classification includes occupations in the NOC’s “natural and applied sciences and related occupations” category and some STEM-related management occupations (e.g., engineering managers).

This study takes a gender-based analytical approach, presenting sex-disaggregated statistics for men and women. These results represent only STEM graduates and do not account for men and women with non-STEM credentials who may be employed in STEM occupations.Note 

4 Results

4.1 Description of sample characteristics

The main characteristics of the longitudinal sample are provided in Table 1. Results are presented for two samples. The first includes all STEM graduates, regardless of whether they were employed in 2006 or 2016, and the second includes only STEM graduates who were employed in both 2006 and 2016. Few differences were found between these two samples.

Generally, the majority (7 in 10) of STEM graduates were men, while 3 in 10 were women. Just over three-quarters of the sample were married or in a common-law relationship in 2006. About 17% were single.Note  Nearly two-thirds of the sample did not have children younger than 6 in either 2006 or 2016, and about one-third had a young child in either 2006 or 2016. Only 2.1% had children younger than 6 in both years.

One-quarter of respondents reported being a member of a visible minority group, while just over one-third of the sample were immigrants. Compared with men, a slightly higher proportion of women with STEM credentials were immigrants.

A small proportion of STEM graduates identified as a member of an Aboriginal groupNote  in the longitudinal sample (just over 1%). Similar proportions of men and women reported being a member of an Aboriginal group.

About 2 in 10 respondents achieved their highest level of education outside Canada. This proportion was slightly higher among women than men (22.8% and 20.1%, respectively). A higher proportion of STEM graduates reported a college diploma or university certificate below the bachelor’s level (43.2%) than a bachelor’s degree (41.6%) as their highest level of education. However, men were more likely than women to have college-level credentials, while women were more likely to hold a bachelor’s degree.

Overall, the largest proportion of STEM graduates had studied engineering or engineering technology (47.9%). However, this was largely driven by men. Over half of male STEM graduates had studied engineering or engineering technology, compared with just under one-quarter of women with STEM credentials. Conversely, women were much more likely to have studied biological, general or integrated sciences than men (37.5% and 12.5%, respectively). About one-quarter of STEM graduates had studied mathematics or computer and information sciences, while less than 1 in 10 had studied physical or chemical sciences.


Table 1
Key characteristics of the longitudinal sample of STEM graduates
Table summary
This table displays the results of Key characteristics of the longitudinal sample of STEM graduates Sample including all
STEM graduates, Sample including only STEM graduates employed in
2006 and 2016, Overall, Men and Women, calculated using percent and number units of measure (appearing as column headers).
Sample including all
STEM graduates
Sample including only STEM graduates employed in
2006 and 2016
Overall Men Women Overall Men Women
percent percent
Sex
Female 30.2 Note ...: not applicable 100.0 28.0 Note ...: not applicable 100.0
Male 69.8 100.0 Note ...: not applicable 72.0 100.0 Note ...: not applicable
Age group (2006)
25 to 34 30.0 28.4 33.8 31.7 30.2 35.5
35 to 44 38.8 38.8 38.9 40.8 40.7 41.0
45 to 54 31.2 32.8 27.3 27.5 29.1 23.5
Marital status (2006)
Single, never married 17.1 17.3 16.6 17.1 16.8 17.7
Married or common law 77.5 78.3 75.4 77.8 79.1 74.4
Separated, divorced or widowed 5.5 4.4 8.0 5.1 4.1 7.9
Immigrant status
Canadian-born 65.8 66.7 63.6 66.3 66.7 65.2
Immigrant 34.2 33.3 36.5 33.7 33.3 34.8
Aboriginal identity
Does not identify as member of an Aboriginal group 98.9 99.0 98.7 98.9 99.0 98.7
Identifies as member of an Aboriginal group 1.1 1.0 1.3 1.1 1.0 1.3
Visible minority status
Not a visible minority 74.8 75.5 73.2 75.2 75.5 74.4
Visible minority 25.2 24.6 26.8 24.9 24.6 25.6
Presence of children younger than 6
Had children younger than 6 in 2006 and 2016 2.1 2.1 2.1 2.1 2.2 1.9
Had children younger than 6 in 2006, not in 2016 22.0 21.8 22.3 22.9 23.3 22.0
Had children younger than age 6 in 2016, not in 2006 10.6 10.9 9.8 11.4 11.7 10.7
Did not have children younger than 6 in 2006 or 2016 65.3 65.1 65.8 63.5 62.8 65.4
Highest certificate, diploma or degree
College, CEGEP or other non-university certificate or diploma or university certificate below a bachelor's degree 43.2 45.3 38.2 42.6 44.6 37.6
Bachelor's degree 41.6 40.2 45.0 41.7 40.5 44.8
University degree above a bachelor's degree 15.2 14.5 16.8 15.7 14.9 17.6
Location of postsecondary study
Canada 79.1 79.9 77.2 79.7 79.9 79.2
Outside Canada 20.9 20.1 22.8 20.3 20.1 20.8
STEM field of study
Physical and chemical sciences 7.0 6.3 8.6 6.9 6.2 8.5
Biological, general and integrated sciences 20.0 12.5 37.5 19.7 12.5 38.0
Engineering and engineering technology 47.9 58.2 24.1 48.6 58.1 24.3
Mathematics and computer and information sciences 25.1 23.0 29.8 24.9 23.2 29.2
Area of residence (2006)
Newfoundland and Labrador 1.1 1.1 1.2 1.2 1.1 1.3
Prince Edward Island 0.3 0.3 0.4 0.3 0.3 0.4
Nova Scotia 2.5 2.4 2.8 2.5 2.4 2.9
New Brunswick 1.9 2.0 1.8 2.0 2.0 2.0
Quebec 23.3 23.8 22.0 23.2 23.6 22.3
Ontario 44.3 43.8 45.3 44.1 43.8 44.7
Manitoba 2.6 2.6 2.5 2.6 2.6 2.6
Saskatchewan 1.7 1.7 1.8 1.8 1.8 1.9
Alberta 11.4 11.6 10.8 11.5 11.8 10.7
British Columbia 10.7 10.5 11.1 10.7 10.6 11.1
Territories 0.2 0.2 0.3 0.2 0.2 0.3
   number
Sample size 48,271 33,686 14,585 42,142 30,312 11,830

4.2 Proportion of STEM graduates working in STEM occupations, 2006 and 2016

This section presents the proportion of STEM graduates in the longitudinal sample who worked in STEM occupations, non-STEM occupations, or who were not in the labour force.Note  Results for both 2006 and 2016 are reported. For this analysis, the sample included all STEM graduates regardless of their employment status in 2006 and 2016, allowing for potential movement into and out of the labour force.

Overall, just over 4 in 10 STEM graduates in the longitudinal sample were employed in a STEM occupation in 2006 (41.1%; Chart 1). A smaller proportion (35.8%) worked in a STEM occupation in 2016, representing a 12.7% decrease between 2006 and 2016.

There were notable differences in the proportion of men and women with STEM credentials working in STEM occupations (Chart 1).Note  While nearly half of male STEM graduates worked in a STEM occupation in 2006 (46.9%), less than 3 in 10 women with STEM credentials worked in similar occupations (27.6%). Both women and men were less likely to be employed in a STEM occupation in 2016—women experienced a 17.4% decrease, while men experienced an 11.5% decrease.Note  Generally, the gap between men and women was similar between 2006 and 2016 (about 19 percentage points).

Detailed information about the occupations of STEM graduates is presented in Chart 2. In both 2006 and 2016, half of male STEM graduates worked in non-STEM occupations.Note  In comparison, over 6 in 10 women with STEM credentials worked in non-STEM occupations in the two years. Overall, a higher proportion of men than women had managerial occupations in both 2006 and 2016. Moreover, women with STEM credentials were more likely than their male counterparts to be unemployed or not in the labour force.Note 

Chart 1

Data table for Chart 1 
Data table for Chart 1
Table summary
This table displays the results of Data table for Chart 1. The information is grouped by Sex (appearing as row headers), 2006 and 2016, calculated using percent units of measure (appearing as column headers).
Sex 2006 2016
percent
Overall 41.1 35.8
Men 46.9 41.5
Women 27.6 22.8

Chart 2

Data table for Chart 2 
Data table for Chart 2
Table summary
This table displays the results of Data table for Chart 2 Men, Women, 2006 and 2016, calculated using percent units of measure (appearing as column headers).
Men Women
2006 2016 2006 2016
percent
STEM management occupation 3.2 4.1 1.7 2.1
STEM non-management occupation 43.7 37.4 25.9 20.6
Non-STEM management occupation 11.4 13.4 6.5 8.7
Non-STEM non-management occupation 38.9 36.9 56.6 54.8
Unemployed/not in labour force 2.8 8.3 9.4 13.7

Female and male STEM graduates who worked in non-STEM occupations in 2006 were generally in similar occupational groups (Chart 3).Note  Three of the top five occupational groups were the same for both women and men: legislators and senior management; sales, marketing and advertising managers; and managers in retail trade. However, a higher proportion of men than women worked in the legislators and senior management group (18.4% and 12.5%, respectively), while a higher proportion of women than men worked in the managers in retail trade group (16.7% and 11.8%, respectively).

Some differences in women’s and men’s non-STEM occupations were also observed. For example, while administrative services managers and managers in financial and business services were among the top five occupational groups of women working in non-STEM occupations, they were not among the top occupational groups for their male counterparts (Chart 3). About one-quarter of male STEM graduates in non-STEM occupations had worked as managers in manufacturing and utilities or as managers in construction and transportation, which were not in the top occupational groups of women employed in non-STEM occupations.

Chart 3

Data table for Chart 3 
Data table for Chart 3
Table summary
This table displays the results of Data table for Chart 3. The information is grouped by Occupational groups of men and women (appearing as row headers), Percent (appearing as column headers).
Occupational groups of men and women Percent
Men
Legislators and senior management 18.4
Managers in manufacturing and utilities 13.9
Sales, marketing and advertising managers 12.4
Managers in construction and transportation 11.8
Managers in retail trade 11.8
Women
Managers in retail trade 16.7
Administrative services managers 14.3
Sales, marketing and advertising managers 12.9
Legislators and senior management 12.5
Managers in financial and business services 8.5

To determine whether sociodemographic and educational characteristics were associated with the likelihood of working in a STEM occupation in 2006,Note  ordinary least squares (OLS) regression models were employed.Note  The variables entered in the model include age group in 2006 (25 to 34, 35 to 44 or 45 to 54); marital status in 2006 (single; married or common law; or divorced, separated or widowed); binary variables for immigrant status, Aboriginal identity and visible minority status; number of children younger than 6 in 2006 (none, one, two, or three or more); highest certificate, diploma or degree in 2006 (college diploma or university certificate below a bachelor’s degree, bachelor’s degree, or university degree above a bachelor’s degree); STEM field of study (physical and chemical sciences; biological, general and integrated sciences; engineering and engineering technology; or mathematics and computer and information sciences); location of study (within Canada or outside Canada); and province or territoryNote  of residence in 2006. For these models, only individuals who were employed in 2006 were included in the sample.

Results for the regression models are presented in Table 2. Among both men and women, STEM graduates in older age groups were less likely than their counterparts aged 25 to 34 to work in a STEM occupation.Note  Furthermore, men and women who identified as visible minorities were less likely than their counterparts who did not identify as a minority to work in a STEM occupation.

Differences between men and women with STEM credentials were observed in the relationship between Aboriginal identity and the likelihood of working in a STEM occupation. While Aboriginal men with STEM credentials were less likely than their non-Aboriginal counterparts to be employed in a STEM occupation in 2006, there was no statistically significant difference between Aboriginal women and non-Aboriginal women.

The relationship between the number of children younger than age 6 and the likelihood of working in a STEM occupation also differed between women and men. Men who had one or two children younger than 6 were more likely than men with no young children to work in a STEM occupation. Similarly, women with one child younger than 6 were more likely to be employed in a STEM occupation than women with no young children. However, women who had three or more children younger than 6 were less likely than those with no young children to be employed in a STEM occupation.

Level of education also mattered. Compared with bachelor’s degree holders, STEM graduates who held a college diploma or a university certificate below the bachelor’s level were less likely to be employed in a STEM occupation, while those with a university degree above a bachelor’s degree were more likely to work in a STEM occupation. This was true for both men and women. Furthermore, men and women who obtained their STEM credentials in Canada were more likely than their counterparts who studied outside Canada to work in a STEM occupation. This may be an indication of a preference among STEM employers for Canadian-educated workers.


Table 2
Ordinary least squares regression of the likelihood of working in a STEM occupation in 2006 on sociodemographic and educational factors, STEM graduates who were employed in 2006
Table summary
This table displays the results of Ordinary least squares regression of the likelihood of working in a STEM occupation in 2006 on sociodemographic and educational factors Men and Women, calculated using coefficient and standard error units of measure (appearing as column headers).
Men Women
coefficient standard error coefficient standard error
Age group (2006) (reference group: 25 to 34)
35 to 44 -0.033Note *** 0.007 -0.028Note ** 0.010
45 to 54 -0.074Note *** 0.008 -0.069Note *** 0.012
Marital status (2006) (reference group: married or common law)
Single or never married -0.003 0.009 -0.019 0.012
Separated, divorced or widowed -0.025Table 2 Note  0.014 -0.021 0.016
Number of children younger than 6 (2006) (reference group: none)
One 0.024Note ** 0.009 0.023Table 2 Note  0.013
Two 0.022Table 2 Note  0.012 0.001 0.019
Three or more 0.000 0.034 -0.114Note * 0.053
Visible minority status (reference group: not a visible minority) -0.062Note *** 0.009 -0.025Table 2 Note  0.014
Aboriginal identity (reference group: does not identify as member of an Aboriginal group) -0.085Note ** 0.027 -0.045 0.036
Immigrant status (reference group: Canadian-born) 0.016 0.010 0.019 0.015
Highest certificate, diploma or degree (reference group: bachelor's degree)
College, CEGEP or other non-university certificate or diploma or university certificate below a bachelor's degree -0.177Note *** 0.007 -0.126Note *** 0.010
University degree above a bachelor's degree 0.031Note ** 0.009 0.046Note *** 0.013
Location of study (reference group: outside Canada) 0.106Note *** 0.010 0.140Note *** 0.014
STEM field of study (reference group: engineering and engineering technology)
Physical and chemical sciences -0.080Note *** 0.013 -0.101Note *** 0.018
Biological, general and integrated sciences -0.316Note *** 0.009 -0.315Note *** 0.011
Mathematics and computer and information sciences 0.129Note *** 0.007 -0.037Note ** 0.013
Area of residence (2006) (reference group: Ontario)
Newfoundland and Labrador 0.015 0.028 -0.097Note ** 0.032
Prince Edward Island -0.011 0.054 0.013 0.067
Nova Scotia -0.059Note ** 0.019 -0.080Note ** 0.024
New Brunswick -0.007 0.021 -0.080Note ** 0.027
Quebec 0.011 0.008 0.052Note *** 0.012
Manitoba 0.040Note * 0.019 0.050Table 2 Note  0.027
Saskatchewan 0.039Table 2 Note  0.023 0.084Note * 0.034
Alberta 0.091Note *** 0.010 0.040Note ** 0.014
British Columbia 0.017Table 2 Note  0.010 0.002 0.014
Territories 0.038 0.054 0.109 0.073

Men and women who studied physical or chemical sciences or biological, general or integrated sciences were less likely to be working in STEM occupations than their counterparts who studied engineering or engineering technology. However, differences between women and men were found for mathematics and computer and information science graduates. Men who studied mathematics or computer and information sciences were more likely than men who studied engineering or engineering technology to be working in a STEM occupation. By comparison, women who studied mathematics or computer and information sciences were less likely to be employed in a STEM occupation than women who had studied engineering or engineering technology.

While the results presented in this section provide an overview of the occupational attainment of STEM graduates in 2006 and 2016, different factors may play a role in the proportion of individuals working in STEM occupations in each of the two years. For example, while some individuals leave STEM occupations, others may enter from non-STEM occupations. To better understand the occupational changes of STEM graduates, the remaining sections concentrate on the pathways of STEM graduates who were employed in both 2006 and 2016.

4.3 Occupational pathways of STEM graduates

This section examines only the STEM graduates who reported an occupation in both 2006 and 2016. Since the primary goal of this study is to understand the occupational changes of STEM graduates, focusing on this group provides insight into the pathways of individuals who had an occupation in both years.

Descriptive analyses are presented for four occupational pathways: (a) employed in a STEM occupation in both 2006 and 2016 (persisted in STEM), (b) employed in a STEM occupation in 2006 and employed in a non-STEM occupation in 2016 (exited STEM), (c) employed in a non-STEM occupation in 2006 and employed in a STEM occupation in 2016 (entered STEM), and (d) worked in a non-STEM occupation in 2006 and 2016 (never in STEMNote ).

The occupational pathways of men and women with STEM credentials differed.Note 

Generally, a higher proportion of men (35.9%) than women (20.2%) worked in a STEM occupation in both 2006 and 2016 (persisted in STEM, Chart 4). Notably, just over 6 in 10 women with STEM credentials did not work in a STEM occupation in either year, compared with about 4 in 10 men (never in STEM, Chart 4). The differences observed in the proportion of men and women who exited or entered STEM occupations between 2006 and 2016 were less pronounced.Note 

The occupational pathways of STEM graduates also varied by field of study. Among men, about half of mathematics and computer and information science graduates and just over one-third of engineering and engineering technology graduates persisted in a STEM occupation between 2006 and 2016 (Chart 5).Note  Notably, about two-thirds of men who studied biological, general or integrated sciences did not have a STEM occupation in either 2006 or 2016. Across STEM fields, men who studied mathematics or computer and information sciences had the lowest proportion of graduates who had never worked in a STEM occupation (28.9%).

The highest proportion of women who persisted in a STEM occupation between 2006 and 2016 was for engineering and engineering technology graduates (30.7%; Chart 6). Over one-quarter of women who studied mathematics or computer and information sciences also persisted in STEM occupations over the 10-year period. Among women who studied biological, general or integrated sciences, less than 1 in 10 had a STEM occupation in both 2006 and 2016, while over three-quarters never worked in a STEM occupation.Note  More than half of women who studied physical or chemical sciences or mathematics or computer and information sciences did not have a STEM occupation in either 2006 or 2016.

Overall, women from all four STEM fields were less likely than their male counterparts to persist in STEM occupations. They were also more likely than men who studied in the same STEM field to have never worked in a STEM occupation. This was particularly noticeable among men and women who studied mathematics or computer and information sciences. However, similar proportions of men and women with STEM credentials in physical or chemical sciences exited a STEM occupation between 2006 and 2016.Note 

Chart 4

Data table for Chart 4 
Data table for Chart 4
Table summary
This table displays the results of Data table for Chart 4 Men and Women, calculated using percent units of measure (appearing as column headers).
Men Women
percent
Never in STEM (Non-STEM occupation in 2006 and 2016) 41.6 62.3
Entered STEM (Non-STEM occupation in 2006, STEM occupation in 2016) 9.6 6.9
Exited STEM (STEM occupation in 2006, Non-STEM occupation in 2016) 12.8 10.7
Persisted in STEM (STEM occupation in 2006 and 2016) 35.9 20.2

Chart 5

Data table for Chart 5 
Data table for Chart 5
Table summary
This table displays the results of Data table for Chart 5. The information is grouped by Occupational pathways (appearing as row headers), Persisted in STEM
(STEM occupation in 2006 and 2016), Exited STEM
(STEM occupation in 2006, non-STEM occupation in 2016), Entered STEM
(non-STEM occupation in 2006, STEM occupation in 2016) and Never in STEM
(non-STEM occupation in 2006 and 2016), calculated using percent units of measure (appearing as column headers).
Occupational pathways Persisted in STEM
(STEM occupation in 2006 and 2016)
Exited STEM
(STEM occupation in 2006, non-STEM occupation in 2016)
Entered STEM
(non-STEM occupation in 2006, STEM occupation in 2016)
Never in STEM
(non-STEM occupation in 2006 and 2016)
percent
Physical and chemical sciences 33.0 13.1 9.5 44.5
Biological, general and integrated sciences 14.0 10.4 7.8 67.8
Engineering and engineering technology 35.2 13.3 10.7 40.8
Mathematics and computer and information sciences 50.2 13.0 7.9 28.9

Chart 6

Data table for Chart 6 
Data table for Chart 6
Table summary
This table displays the results of Data table for Chart 6. The information is grouped by Occupational pathways (appearing as row headers), Persisted in STEM
(STEM occupation in 2006 and 2016), Exited STEM
(STEM occupation in 2006, non-STEM occupation in 2016), Entered STEM
(non-STEM occupation in 2006, STEM occupation in 2016) and Never in STEM
(non-STEM occupation in 2006 and 2016), calculated using percent units of measure (appearing as column headers).
Occupational pathways Persisted in STEM
(STEM occupation in 2006 and 2016)
Exited STEM
(STEM occupation in 2006, non-STEM occupation in 2016)
Entered STEM
(non-STEM occupation in 2006, STEM occupation in 2016)
Never in STEM
(non-STEM occupation in 2006 and 2016)
percent
Physical and chemical sciences 21.5 13.2 7.7 57.6
Biological, general and integrated sciences 8.0 8.3 5.6 78.1
Engineering and engineering technology 30.7 12.8 8.4 48.1
Mathematics and computer and information sciences 26.9 11.5 7.0 54.7

4.4 Factors associated with STEM graduates exiting a STEM occupation

While the previous section provides insight into the occupational pathways of STEM graduates, this section focuses on STEM graduates who were employed in a STEM occupation in 2006 and had either persisted in or exited a STEM occupation by 2016.

In addition to providing descriptive information on the occupational pathways of these STEM graduates, this section presents OLS regression results to determine whether certain sociodemographic and educational characteristics were associated with the likelihood of exiting a STEM occupation between 2006 and 2016.Note  For these models, the same set of sociodemographic and educational variables used in the regression model described in Section 4.2 (Table 2) was analyzed, except the variable for the number of young children. For the models presented in this section, a variable was created to account for potential changes in the presence of young children between 2006 and 2016. This variable includes the following categories: children younger than 6 in both 2006 and 2016, children younger than 6 in 2006 only, children younger than 6 in 2016 only, and no children younger than 6 in 2006 or 2016.Note 

The occupational pathways of STEM graduates who were employed in a STEM occupation in 2006 are presented in Chart 7.Note  The majority of men and women who were employed in a STEM occupation in 2006 persisted in STEM occupations. However, women were more likely than men to have exited a STEM occupation between 2006 and 2016. Just over one-third of women (34.7%) who were employed in a STEM occupation in 2006 had moved to a non-STEM occupation 10 years later, while about one-quarter of men (26.4%) followed the same occupational pathway.Note 

Chart 8 shows the proportion of women and men with STEM credentials who exited a STEM occupation by field of study. Generally, a higher proportion of women than men exited a STEM occupation across all STEM fields. The gap was widest among women and men who studied physical or chemical sciences (38.1% and 28.4%, respectively). The narrowest gap was between women and men who studied engineering or engineering technology; however, the difference in exit rates between male and female engineering graduates was not statistically significant.

The multivariate models presented in Table 3 indicate that age was associated with the likelihood of men and women exiting STEM occupations. Generally, men aged 35 to 44 and women aged 45 to 54 were less likely to exit STEM occupations than their younger (25 to 34) counterparts. However, other sociodemographic characteristics, such as Aboriginal identity, immigrant status and visible minority status, did not show statistically significant associations with exiting a STEM occupation for men or women.

Chart 7

Data table for Chart 7 
Data table for Chart 7
Table summary
This table displays the results of Data table for Chart 7. The information is grouped by Occupational pathways (appearing as row headers), Men and Women, calculated using percent units of measure (appearing as column headers).
Occupational pathways Men Women
percent
Persisted in STEM occupation 73.6 65.3
Exited STEM occupation 26.4 34.7

Chart 8

Data table for Chart 8 
Data table for Chart 8
Table summary
This table displays the results of Data table for Chart 8. The information is grouped by Fiels of study (appearing as row headers), Men and Women, calculated using percent units of measure (appearing as column headers).
Fiels of study Men Women
percent
Physical and chemical sciences 28.4 38.1
Biological, general and integrated sciences 42.5 50.7
Engineering and engineering technology 27.4 29.4
Mathematics and computer and information sciences 20.6 29.9

The previous literature suggests that women’s occupational pathways may be associated with family obligations, such as caring for young children (e.g., Xu 2015). Interestingly, having children younger than 6 was not significantly associated with the likelihood of women or men exiting STEM occupations. However, marital status mattered. Single women were less likely to exit a STEM occupation between 2006 and 2016 than women who were married or in a common law relationship. Men who were separated, divorced or widowed were more likely to exit a STEM occupation than their married or common law counterparts.

Since this section focuses only on those who were employed in a STEM occupation in 2006, selection bias may affect the results for the presence of young children variable. For example, as the results in Table 2 showed, women with three or more young children were less likely to be employed in a STEM occupation in 2006 than women with no young children. Therefore, it is possible that some women with young children self-selected out of STEM occupations to begin with.Note  As a result, the potential influence of the presence of young children may be minimized in this set of results.

With respect to education, men and women with a college diploma or university certificate below the bachelor’s level were more likely to exit a STEM occupation than their counterparts with a bachelor’s degree (Table 3). Field of study was also an important factor in graduates’ persistence in STEM occupations. Similar to the descriptive results, men and women who studied physical or chemical sciences or biological, general or integrated sciences were more likely to exit a STEM occupation than their counterparts who studied engineering or engineering technology. However, differences were observed between women and men who studied mathematics or computer and information sciences. Men who studied in these fields were less likely to exit STEM occupations than men who studied engineering or engineering technology. In contrast, there was no statistically significant difference in the likelihood of exiting a STEM occupation between women who studied mathematics or computer and information sciences and women who studied engineering or engineering technology.

One question that arises regarding STEM graduates who left STEM occupations is whether they were concentrated in particular STEM occupations prior to their exit. Moreover, because of a lack of longitudinal data with occupational information, previous studies do not provide much information about the non-STEM occupations to which they moved. Charts 9 and 10 show the most common STEM and non-STEM occupations of men and women who worked in STEM occupations in 2006 and moved to a non-STEM occupation by 2016.

The top two STEM occupational groups in 2006 for individuals who exited STEM occupations were the same for both men and women: information systems analysts and consultants, and computer programmers and interactive media developers (Chart 9).Note  Among men who exited STEM occupations, about 1 in 10 worked as either electrical and electronics engineering technologists or civil engineers in 2006. Biologists and related scientists, chemical technologists and technicians, and chemists were also among the top occupational groups that female STEM graduates exited.

The top five non-STEM occupational groups in which STEM “leavers” worked in 2016 are presented in Chart 10.Note  Just over 2 in 10 women moved into either specialized middle management occupations or professional occupations in law and social, community and government services. Professional occupations in business and finance, as well as administrative and financial supervisors and administrative occupations, were also among the top occupations of women who exited STEM occupations. About 2 in 10 men moved into middle management occupations in trades, transportation, production and utilities, or into specialized middle management occupations, while 7.5% of men moved into senior management occupations.

Additional results showing the top five occupational groups of men and women who exited STEM occupations are presented in Appendix Table 2 by field of study. Some differences were observed across STEM fields. For example, senior management occupations was one of the top five occupational groups to which men moved across all STEM fields, but was not among the top five for women. Conversely, office support occupations was in the top five occupational groups for women who studied physical or chemical sciences, engineering or engineering technology, or mathematics or computer and information science programs, but was not in the top five for men. The results also indicated that many women who studied physical or chemical sciences or biological, general or integrated sciences moved into professional occupations in education services.


Table 3
Ordinary least squares regression of the likelihood of STEM graduates exiting a STEM occupation on sociodemographic and educational characteristics, men and women who held a STEM occupation in 2006 and were employed in 2016
Table summary
This table displays the results of Ordinary least squares regression of the likelihood of STEM graduates exiting a STEM occupation on sociodemographic and educational characteristics Men and Women, calculated using coefficient and standard error units of measure (appearing as column headers).
Men Women
coefficient standard error coefficient standard error
Age group (2006) (reference group: 25 to 34)
35 to 44 -0.019Table 3 Note  0.010 -0.030 0.022
45 to 54 -0.018 0.013 -0.072Note ** 0.028
Marital status (2006) (reference group: married or common law)
Single or never married -0.009 0.011 -0.043Table 3 Note  0.024
Separated, divorced or widowed 0.041Table 3 Note  0.022 -0.016 0.035
Presence of children younger than 6 (reference group: did not have children younger than 6 in 2006 or 2016)
Had children younger than 6 in 2006 and 2016 -0.0003 0.027 0.048 0.063
Had children younger than 6 in 2006, not in 2016 0.008 0.011 0.001 0.024
Had children younger than 6 in 2016, not in 2006 -0.007 0.013 -0.030 0.030
Visible minority status (reference group: not a visible minority) -0.009 0.012 -0.029 0.027
Aboriginal identity (reference group: does not identify as member of Aboriginal group) 0.021 0.043 0.013 0.083
Immigrant status (reference group: Canadian-born) 0.008 0.014 0.017 0.030
Highest certificate, diploma or degree (reference group: bachelor's degree)
College, CEGEP or other non-university certificate or diploma or university certificate below a bachelor's degree 0.098Note *** 0.009 0.052Note * 0.021
University degree above a bachelor's degree -0.018 0.012 -0.008 0.024
Location of study (reference group: outside Canada) -0.016 0.013 0.016 0.029
STEM field of study (reference group: engineering and engineering technology)
Physical and chemical sciences 0.040Note * 0.018 0.093Note ** 0.033
Biological, general and integrated sciences 0.183Note *** 0.019 0.223Note *** 0.026
Mathematics and computer and information sciences -0.079Note *** 0.009 -0.004 0.021
Area of residence (in 2006) (reference group: Ontario)
Newfoundland and Labrador 0.0003 0.038 0.086 0.096
Prince Edward Island 0.032 0.083 -0.308Note ** 0.116
Nova Scotia -0.023 0.029 0.020 0.066
New Brunswick 0.033 0.031 0.059 0.073
Quebec 0.009 0.011 -0.023 0.023
Manitoba -0.004 0.025 -0.074 0.053
Saskatchewan 0.005 0.031 0.035 0.065
Alberta -0.023Table 3 Note  0.012 -0.047Table 3 Note  0.028
British Columbia -0.020 0.013 -0.045 0.031
Territories 0.096 0.090 -0.003 0.140

Chart 9

Data table for Chart 9 
Data table for Chart 9
Table summary
This table displays the results of Data table for Chart 9. The information is grouped by SREM occupations of men and women (appearing as row headers), Percent (appearing as column headers).
STEM occupations of men and women Percent
Men
Information systems analysts and consultants 10.4
Computer programmers and interactive media developers 6.9
Electrical and electronics engineering technologists 5.4
Civil engineers 5.3
Computer and information systems managers 4.7
Women
Information systems analysts and consultants 14.0
Computer programmers and interactive media developers 8.5
Biologists and related scientists 8.2
Chemical technologists and technicians 8.0
Chemists 5.5

Chart 10

Data table for Chart 10 
Data table for Chart 10
Table summary
This table displays the results of Data table for Chart 10. The information is grouped by Non-STEM occupational groups of men and women
(appearing as row headers), Percent (appearing as column headers).
Non-STEM occupational groups of men and women
Percent
Men
Middle management occupations in trades, transportation,
production and utilities
11.3
Specialized middle management occupations 9.9
Senior management occupations 7.5
Professional occupations in business and finance 6.4
Industrial, electrical and construction trades 5.2
Women
Specialized middle management occupations 10.3
Professional occupations in law and social, community
and government services
10.2
Professional occupations in business and finance 9.8
Administrative and financial supervisors and administrative occupations 9.0
Professional occupations in education services 7.0

4.5 An examination of the earnings of STEM graduates: Does persisting in a STEM occupation pay off?

Studies comparing the earnings of postsecondary graduates by field of study found that STEM graduates earn more than non-STEM graduates (e.g., Hango 2013; Statistics Canada 2017a). However, graduates of some STEM fields work in higher-paying jobs than graduates of other STEM fields (Frenette and Frank 2016). Graduates working in STEM sectors have also been found to earn more than those working in other types of occupations (Caranci, Judge and Kobelak 2017). While these results suggest a general earnings advantage for STEM graduates, little is known about whether their persistence in a STEM occupation is positively associated with greater wage growth than their peers who left STEM occupations.

The primary purpose of the results presented in this section is to determine whether STEM graduates who persisted in a STEM occupation between 2006 and 2016 experienced greater wageNote  growth than their counterparts who had moved to a non-STEM occupation by 2016, after accounting for their differences in sociodemographic and educational characteristics. For this part of the analysis, only STEM graduates who had a STEM occupation in 2006, were employed full year, full timeNote  in both 2006 and 2016, and had positive wages in both 2006 and 2016 were included in the sample.

The dependent variable for this model measures the difference in respondents’ log wages between 2006 and 2016 (i.e., 2016 log wages minus 2006 log wages). The independent variables for this model include age group; marital status; presence of children younger than 6 in 2006; visible minority status; Aboriginal identity status; immigrant status; highest certificate, diploma or degree; STEM field of study; province or territory of birth (those born outside Canada are identified as a separate group);Note  and a binary variable that identifies whether the respondent persisted in or exited a STEM occupation between 2006 and 2016.

Regression results for both men and women are presented in Table 4.

The analysis of wage changes between 2006 and 2016 indicated that individuals who persisted in a STEM occupation did not experience significantly greater earnings growth than their counterparts who had moved to a non-STEM occupation by 2016. This was true for both men and women, indicating that the wage growth of STEM graduates who exited a STEM occupation was similar to that of STEM graduates who remained in a STEM occupation.

The results also showed interesting relationships between STEM graduates’ sociodemographic characteristics and wage growth. For example, older men and women experienced lower earnings growth than their younger counterparts. However, visible minority status, Aboriginal identity and immigrant status were not statistically significant. This may be because the sample was limited to individuals who were working in similar occupations (STEM occupations) in 2006.

Moreover, the wage growth of single men was higher than that of married men, while women who were divorced, separated or widowed had lower earnings growth than their married counterparts. Furthermore, while the presence of young children was not significantly associated with the wage growth of men, women who had children younger than 6 in 2006 experienced higher wage growth than their counterparts who did not have young children. Again, this finding may be attributable to the particular sample examined, as only women who were employed in a STEM occupation in 2006 were included in this part of the analysis.

The field of study results also indicated that, among men, mathematics and computer and information science graduates experienced lower wage growth than their engineering and engineering technology counterparts. Similarly, the wage growth of women who studied physical or chemical sciences was lower than that of women who studied engineering or engineering technology.

Lastly, since senior management occupations was one of the top occupational groups to which male STEM “leavers” moved (see Chart 10), additional models were run which excluded individuals who had moved to these occupations by 2016Note  because they likely earn much higher wages than individuals who moved into other types of non-STEM occupations. The results from these models supported the conclusion that the wage growth of men and women who persisted in a STEM occupation did not differ significantly from their counterparts who moved to a non-STEM occupation.


Table 4
Ordinary least squares regressions of difference between 2006 and 2016 log wages on sociodemographic, educational, and employment characteristics, STEM graduates who worked in a STEM occupation in 2006 and were employed full-year, full-time in both 2006 and 2016
Table summary
This table displays the results of Ordinary least squares regressions of difference between 2006 and 2016 log wages on sociodemographic Men and Women, calculated using coefficient and standard error units of measure (appearing as column headers).
Men Women
coefficient standard error coefficient standard error
Age group (2006) (reference group: 25 to 34)
35 to 44 -0.202Note *** 0.020 -0.103Note ** 0.036
45 to 54 -0.326Note *** 0.024 -0.192Note *** 0.044
Marital status (2006) (reference group: married or common law)
Single or never married 0.071Note ** 0.022 -0.006 0.038
Separated, divorced or widowed -0.033 0.057 -0.086Table 4 Note  0.049
Presence of young children in 2006 (reference group: did not have children younger than 6) -0.005 0.019 0.171Note *** 0.048
Visible minority status (reference group: not a visible minority) -0.014 0.024 -0.026 0.063
Aboriginal identity (reference group: does not identify as member of Aboriginal group) 0.062 0.057 0.085 0.069
Immigrant status (reference group: Canadian-born) -0.016 0.078 -0.174 0.176
Highest certificate, diploma or degree (reference group: bachelor's degree)
College, CEGEP or other non-university certificate or diploma or university certificate below a bachelor's degree -0.031 0.019 0.000 0.031
University degree above a bachelor's degree 0.050Table 4 Note  0.026 0.033 0.049
Location of study (reference group: outside Canada) -0.011 0.029 -0.087 0.067
STEM field of study (reference group: engineering and engineering technology)
Physical and chemical sciences -0.027 0.048 -0.130Note * 0.051
Biological, general and integrated sciences -0.038 0.042 -0.015 0.055
Mathematics and computer and information sciences -0.047Note ** 0.017 -0.047 0.032
Area of birth (reference group: Ontario)
Newfoundland and Labrador 0.077Table 4 Note  0.042 0.099 0.096
Prince Edward Island 0.230 0.145 0.247Table 4 Note  0.144
Nova Scotia -0.031 0.081 0.076 0.099
New Brunswick 0.036 0.032 0.028 0.053
Quebec 0.002 0.022 0.035 0.032
Manitoba 0.060 0.041 0.072 0.115
Saskatchewan 0.051 0.064 0.076 0.111
Alberta 0.138Note ** 0.044 0.072 0.051
British Columbia 0.015 0.048 0.132Note * 0.060
Territories 0.171 0.118 0.020 0.108
Born outside Canada 0.054 0.077 0.255 0.164
Persisted in a STEM occupation -0.012 0.022 0.050 0.037

5 Conclusion

Although many studies have examined women’s persistence in STEM fields throughout their education, less is known about the occupational pathways of women with STEM credentials and how they compare with their male peers. This study addressed this gap by conducting a gender analysis of the occupational mobility of STEM graduates in Canada and providing detailed results by different STEM fields of study.

Similar to previous research (e.g., Statistics Canada 2017a), the results indicated that men were more likely than women to be employed in a STEM occupation. Furthermore, the occupational pathways of women and men with STEM credentials differed. For example, more than 3 in 10 men were employed in a STEM occupation in both 2006 and 2016, compared with 2 in 10 women. The majority of women were not employed in a STEM occupation in either year.

Differences in the occupational pathways of men and women with STEM credentials were attributable in part to their specific field of study choices. In this study, over half of male STEM graduates had studied engineering or engineering technology, compared with less than one-quarter of female STEM graduates. Conversely, over one-third of female STEM graduates had studied biological, general or integrated sciences, compared with 12.5% of men. However, previous research indicates that engineering graduates were generally more likely than life science graduates to work in STEM occupations (Statistics Canada 2017a). Furthermore, Frenette and Frank (2017) found that physical and life science graduates tended to be employed across a wider range of occupations than engineering graduates, and many of these occupations were in non-STEM fields.

Among STEM graduates who were employed in a STEM occupation in 2006, women were more likely than men to have moved to a non-STEM occupation by 2016. Previous literature indicates that this difference may be due to differing career goals or interests. For example, Fouad et al. (2017) found that women had a greater tendency to leave engineering occupations and attributed this decision to factors such as an interest in applying their skills in another field, a desire to find work that makes a greater contribution to the community, or unmet expectations related to promotions or status within their field. Previous longitudinal research also found that much of the attrition of women in STEM occupations in the United States occurred during their first few years on the job (Glass et al. 2013). While data on job tenure were not available for this study, further research into this finding in the Canadian context would lead to a better understanding of women’s retention in STEM occupations.

This study also found that STEM graduates who had studied physical or chemical sciences or biological, general or integrated sciences were more likely to exit STEM occupations than their engineering or engineering technology counterparts. This was true for both women and men. However, some field of study differences were observed. Men who studied mathematics or computer and information sciences were less likely than their counterparts who studied engineering or engineering technology to exit a STEM occupation between 2006 and 2016, while there was no statistically significant difference among women who studied in these two fields. The degree of occupational mobility among graduates of particular STEM fields could depend on the extent to which these graduates can apply their skills to a range of jobs, their professional networks or their preference for different types of work.

Family obligations are often identified as an important factor in women’s labour market decisions. Research from the United States found that mothers and fathers of young children were more likely than their childless peers to exit STEM occupations (Cech and Blair-Loy 2019). However, results from this study showed that the presence of young children was not associated with the likelihood of exiting a STEM occupation for either women or men. Data limitations may be the reason for these differing results. Cech and Blair-Loy (2019) used data on parental leave, as well as knowledge of exactly when STEM workers’ children were born. In addition to this lack of detail in the longitudinal census data files, the longer period of study may have also contributed to different findings. Furthermore, the divergent results could stem from differences in the parental leave policies of Canada and the United States.

Previous research has also found that graduates who work in occupations closely related to their fields of study have higher earnings than those who do not (Xu 2013). This study measured wage growth, providing an indication of how STEM graduates’ wages changed between 2006 and 2016, depending on whether they remained in a STEM occupation or moved to a non-STEM occupation. The findings indicated that the wage growth of women and men who persisted in a STEM occupation between these years did not differ significantly from that of their counterparts who had moved to non-STEM occupations. Therefore, while STEM occupations may be higher paying than non-STEM occupations on average (Xu 2015), STEM graduates who exited a STEM occupation did not experience lower wage growth than their peers who persisted in a STEM occupation.

The results of this study help fill the information gap on the occupational mobility of STEM graduates in Canada. However, data limitations hindered a more thorough investigation of some questions of interest. For example, restricting the sample to only those who responded to the 2006 and 2016 census long-form questionnaires prevented additional occupational information from being analyzed. While the inclusion of 2011 National Household Survey data could provide a more detailed picture of the occupational mobility of STEM graduates over time, it would also substantially decrease the sample size, potentially preventing specific groups from being analyzed (e.g., women in particular STEM fields). Additionally, data on parental leave would provide a more nuanced understanding of the relationship between parenthood—particularly among new parents—and the occupational changes of STEM graduates. Lastly, because of a lack of historical information on job vacancies in STEM occupations, it is difficult to ascertain how labour market opportunities may have affected the employment of STEM graduates in these occupations over the years studied. Future research would benefit from addressing these data and knowledge gaps.

The results of this study can help inform educators and policy makers about how the occupational pathways of different groups of STEM graduates vary, which would provide a better understanding of where policy interventions may be needed.

Appendices


Appendix Table 1
List of STEM occupations, National Occupational Classification for Statistics (NOC-S) 2006 and National Occupational Classification (NOC) 2016
Table summary
This table displays the results of List of STEM occupations. The information is grouped by NOC-S 2006 (appearing as row headers), NOC 2016 (appearing as column headers).
NOC-S 2006 NOC 2016
Code Occupational title Code Occupational title
A121 Engineering managers 0211 Engineering managers
A122 Computer and information systems managers 0212 Architecture and science managers
A123 Architecture and science managers 0213 Computer and information systems managers
C011 Physicists and astronomers 2111 Physicists and astronomers
C012 Chemists 2112 Chemists
C013 Geologists, geochemists and geophysicists 2113 Geoscientists and oceanographers
C014 Meteorologists 2114 Meteorologists and climatologists
C015 Other professional occupations in physical sciences 2115 Other professional occupations in physical sciences
C021 Biologists and related scientists 2121 Biologists and related scientists
C022 Forestry professionals 2122 Forestry professionals
C023 Agricultural representatives, consultants and specialists 2123 Agricultural representatives, consultants and specialists
C031 Civil engineers 2131 Civil engineers
C032 Mechanical engineers 2132 Mechanical engineers
C033 Electrical and electronics engineers 2133 Electrical and electronics engineers
C034 Chemical engineers 2134 Chemical engineers
C041 Industrial and manufacturing engineers 2141 Industrial and manufacturing engineers
C042 Metallurgical and materials engineers 2142 Metallurgical and materials engineers
C043 Mining engineers 2143 Mining engineers
C044 Geological engineers 2144 Geological engineers
C045 Petroleum engineers 2145 Petroleum engineers
C046 Aerospace engineers 2146 Aerospace engineers
C047 Computer engineers (except software engineers and designers) 2147 Computer engineers (except software engineers and designers)
C048 Other professional engineers, n.e.c. 2148 Other professional engineers, n.e.c.
C051 Architects 2151 Architects
C052 Landscape architects 2152 Landscape architects
C053 Urban and land use planners 2153 Urban and land use planners
C054 Land surveyors 2154 Land surveyors
C061 Mathematicians, statisticians and actuaries 2161 Mathematicians, statisticians and actuaries
C071 Information systems analysts and consultants 2171 Information systems analysts and consultants
C072 Database analysts and data administrators 2172 Database analysts and data administrators
C073 Software engineers and designers 2173 Software engineers and designers
C074 Computer programmers and interactive media developers 2174 Computer programmers and interactive media developers
C075 Web designers and developers 2175 Web designers and developers
C111 Chemical technologists and technicians 2211 Chemical technologists and technicians
C112 Geological and mineral technologists and technicians 2212 Geological and mineral technologists and technicians
C113 Meteorological technicians N/A Not applicable
C121 Biological technologists and technicians 2221 Biological technologists and technicians
C122 Agricultural and fish products inspectors 2222 Agricultural and fish products inspectors
C123 Forestry technologists and technicians 2223 Forestry technologists and technicians
C124 Conservation and fishery officers 2224 Conservation and fishery officers
C125 Landscape and horticultural technicians and specialists 2225 Landscape and horticulture technicians and specialists
C131 Civil engineering technologists and technicians 2231 Civil engineering technologists and technicians
C132 Mechanical engineering technologists and technicians 2232 Mechanical engineering technologists and technicians
C133 Industrial engineering and manufacturing technologists and technicians 2233 Industrial engineering and manufacturing technologists and technicians
C141 Electrical and electronics engineering technologists and technicians 2241 Electrical and electronics engineering technologists and technicians
C142 Electronic service technicians (household and business equipment) 2242 Electronic service technicians (household and business equipment)
C143 Industrial instrument technicians and mechanics 2243 Industrial instrument technicians and mechanics
C144 Aircraft instrument, electrical and avionics mechanics, technicians and inspectors 2244 Aircraft instrument, electrical and avionics mechanics, technicians and inspectors
C151 Architectural technologists and technicians 2251 Architectural technologists and technicians
C152 Industrial designers 2252 Industrial designers
C153 Drafting technologists and technicians 2253 Drafting technologists and technicians
C154 Land survey technologists and technicians 2254 Land survey technologists and technicians
C155 Mapping and related technologists and technicians 2255 Technical occupations in geomatics and meteorology
C161 Non-destructive testers and inspectors 2261 Non-destructive testers and inspection technicians
C162 Engineering inspectors and regulatory officers 2262 Engineering inspectors and regulatory officers
C171 Air pilots, flight engineers and flying instructors 2271 Air pilots, flight engineers and flying instructors
C172 Air traffic control and related occupations 2272 Air traffic controllers and related occupations
C181 Computer network technicians 2281 Computer network technicians
C182 User support technicians 2282 User support technicians
C183 Systems testing technicians 2283 Information systems testing technicians

Appendix Table 2
Top non-STEM occupational groups to which STEM graduates who exited a STEM occupation moved, by field of study (occupations held in 2016)
Table summary
This table displays the results of Top non-STEM occupational groups to which STEM graduates who exited a STEM occupation moved. The information is grouped by Non-STEM occupational groups (appearing as row headers), Share, calculated using percent units of measure (appearing as column headers).
Non-STEM occupational groups Share
percent
Men
Physical and chemical sciences
Professional occupations in law and social, community and government services 12.0
Middle management occupations in trades, transportation, production and utilities 8.8
Senior management occupations 7.6
Professional occupations in education services 6.8
Processing, manufacturing and utilities supervisors and central control operators 6.4
Biological, general and integrated sciences
Professional occupations in law and social, community and government services 14.2
Specialized middle management occupations 11.1
Senior management occupations 8.3
Middle management occupations in trades, transportation, production and utilities 6.2
Professional occupations in business and finance 5.7
Engineering and engineering technology
Middle management occupations in trades, transportation, production and utilities 15.0
Specialized middle management occupations 8.1
Senior management occupations 7.2
Industrial, electrical and construction trades 7.0
Maintenance and equipment operation trades 5.6
Mathematics and computer and information sciences
Specialized middle management occupations 15.8
Professional occupations in business and finance 12.1
Senior management occupations 8.1
Administrative and financial supervisors and administrative occupations 6.2
Middle management occupations in retail and wholesale trade and customer services 5.3
Women
Physical and chemical sciences
Specialized middle management occupations 10.9
Professional occupations in education services 10.1
Office support occupations 7.8
Professional occupations in law and social, community and government services 7.8
Care providers and educational, legal and public protection support occupations 6.2
Biological, general and integrated sciences
Professional occupations in law and social, community and government services 18.1
Professional occupations in education services 9.7
Technical occupations in health 8.6
Specialized middle management occupations 7.0
Professional occupations in business and finance 7.0
Engineering and engineering technology
Middle management occupations in trades, transportation, production and utilities 11.5
Specialized middle management occupations 10.6
Professional occupations in business and finance 9.8
Administrative and financial supervisors and administrative occupations 8.9
Office support occupations 6.1
Mathematics and related studies, computer and information sciences
Professional occupations in business and finance 16.9
Administrative and financial supervisors and administrative occupations 15.1
Specialized middle management occupations 13.6
Office support occupations 6.5
Professional occupations in law and social, community and government services 6.5

Chart A1

Data table for Chart A1 
Data table for Appendix Chart A-1
Table summary
This table displays the results of Data table for Appendix Chart A-1. The information is grouped by Labour market pathways (appearing as row headers), Men and Women, calculated using percent units of measure (appearing as column headers).
Labour market pathways Men Women
percent
Persisted in STEM occupation 69.0 59.4
Exited STEM occupation 24.7 31.5
Exited the labour force 6.4 9.1

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