Thank you, Madam Chair.
Thank you, members of the committee, for hearing me today.
It's my first experience testifying in front of a committee, so bear with me.
I will make my presentation in English.
I'm fully bilingual so ask questions in either language.
What I'm going to present to you today—and you should have the notes from my presentation—are the results of the study I did. I'm going to skip the introduction on who I am; I'm a professor. It's a study I did with my colleague Brahim Boudarbat, which was published a couple of years ago in the Canadian Journal of Economics. We looked at the gender wage gap among recent post-secondary graduates in Canada. It was about men versus women, not specifically women in science, technology, engineering, and mathematics. However, I do have a few things to say about that based on the research. I'm happy to present the relevant results of the study to you.
In this study, the broad objectives are not about women in STEM. It describes the trends in the gender wage gap between 1998 and 2007. It's an empirical study. We looked at the difference between the mean wage for men and the mean wage for women. We also looked at differences in men's and women's wages for low wages and high wages.
The data we used is from the national graduates survey from Statistics Canada. This survey is a representative sample of post-secondary graduates by cohort, so you have people who graduated from post-secondary institutions in Canada in 1986, 1990, 1995, 2000, and 2005. The most recent time period in my study is the 2005 cohort, which was surveyed in 2007, two years after graduation. There is also data from 2013 on the 2009-10 cohort, but it's not part of the study. It wasn't available when we performed our analysis but it is now available.
We selected a sub-sample from the survey of full-time salaried graduates with college or university degrees, aged 50 or less at the time of graduation. In 2000, that amounted to just over 9,000 men and close to 12,000 women, for a total of 21,000 people. We looked at the differences between men's and women's hourly wages—not earnings, not income—for the mean wages, as well as for low wages, which we define as wages at the 10th percentile of wage distribution, and high wages, which are at the 90th percentile of wage distribution.
We used a methodology called a decomposition. It's a description of the differences between male and female wages. It's a sort of accounting exercise where we look at the differences we can explain and the differences we can't explain. Part of the difference that is explained is due to different characteristics of men and women. I'll give a quick example.
Suppose there's a 10% difference between men's and women's earnings. We look at the characteristics we can observe and we see that, on average, men have more experience than women. People with more experience earn more, so there could be a part of the wage difference that we can attribute to the fact that, on average, women have less experience than men. That's just an example.
We're going to try to apply that methodology to account for the differences. We're going to look at the wage gap, and then we're going to try to account for differences that come from various characteristics, which are: education level; number of years experience; province of residence; field of study; permanence of jobs, meaning whether or not someone holds a permanent job; occupation; industry; presence of children; age of the youngest child; and marital status. For this presentation today, I'm going to focus on the field of study and occupation because they are broad-level categories from which I can identify who's in STEM and who's not. We're going to show results from those.
In the general findings for the 2005 cohort in 2007, at the mean, women earned 5.9% less than men. The average wage for a woman was close to 6% less than the average wage for a man. This has been relatively constant since 1988, as shown in my study.
We also see that for what are considered to be low wages, the difference is less. The gap is smaller, 2.6% less for women. For higher wages, it is bigger, 8.2% less for women. The other thing that's interesting is that the gap for low wages has been decreasing over time, and that for high wages has been increasing over time. Another thing to note is that the gap generally increases with time after graduation.
I will skip the next slide in the interest of time, but you have it. It is the overall results from the decomposition. I'm skipping it to have more time to look at the field of study, which I think, is the most interesting for this committee. The first column shows the 10 broad categories of fields of study. I have highlighted in yellow the ones related to STEM. You have physical and life sciences and technologies; mathematics, computer and information sciences; as well as architecture, engineering and related technologies.
The two columns after that, “Men” and “Women”, show the distribution. If you look at architecture, engineering, and related technology for men, 25% of the men in my sample have a degree in architecture, engineering or related technologies. That figure is just 4.1% for women, so it's more than six times higher for men than it is for women. The same can be observed for mathematics, computer and information sciences. Almost 9% of men have a degree in that field and only 2.2% of women do. What's interesting is to look at the difference in the wage gap. The 38.5% that you see in the column, “Mean,” under “Fraction explained by %” means that, at the mean, if you consider mean wages for women and mean wages for men, 38.5% of that difference can be explained by the fact that women don't study in architecture and engineering as much as men do. If we look at the characteristic of having a degree in architecture and engineering, more men than women choose to get that degree and that translates into there being a bigger wage difference between men and women than there would be if the same proportion of women chose that degree.
I'm going to switch now, for science and technology purposes, to occupation. Now we do the decomposition again. For occupation, one of the 10 broad categories is directly related to STEM occupations. We find that the distribution is the same; 24% of men have an occupation in that category and only 7% of women hold a STEM-related job. That translates into, at the mean, an 18.7% wage difference. For low wages, the difference is 72%. For the top wages, it is only 9%. A very significant part of the gap can be explained by the fact that women don't have STEM-related occupations.
What do we do for this? I was asked to give recommendations. These don't come straight from the research that I just presented, but they're based on other research and general reflections. These are a few bullet points that you can take more time to read.
To hold a STEM job, one needs to have made the choice to study in STEM. We also know that parental aspirations and expectations matter a lot when it comes to educational attainment and choices. Beliefs and biases about gender differences in cognitive abilities are probably larger than the actual differences, and skills can be improved. We also know that impacts of policies and interventions tend to be larger when done earlier in an individual’s life.
I think that before even thinking about changing the work conditions, you need to provide girls and women with role models and you need to aim to modify their expectations and aspirations. In terms of policies that could be implemented, I think there should be a tax credit for scientific activities for kids similar to the credits for physical activities and arts, or you could just lump them all into one credit. You could also fund awareness campaigns about women in STEM to give girls access to female role models in science. You could also fund public outreach and mentoring activities through federal research granting agencies. I know of one such activity called Synapse, through the Canadian Institutes of Health Research. I don't know of a similar thing with NSERC, but I may be wrong.
You can also ask for more STEM courses in the curriculum at the high school level, especially mandatory ones, and just generally more funding for research in science and technology.
You can reach me. This is my contact information. I give you two links for reports, including one by the American Association of University Women that cites a lot of research in that area. I don't know if you're already aware of it, but it's a very worthwhile read for this topic.