I'm going extra slowly just for that reason.
For those of you who are following along, I'm on slide 4, which shows a graph comparing the entrance into STEM fields for girls and boys and women and men according to their grade 10 mathematics scores. Essentially, the graphic shows that even women with high grade 10 math scores were less likely to enter STEM fields than were men or boys who had high grade 10 math scores at the same time.
Going on to slide 5, in the next two slides I will discuss wage and occupational differences between men and women. In 2016, the average hourly wage of full-time women workers was 88% that of men. I'd like to highlight that there are different ways to calculate the gender wage gap. The one that I'm choosing to present here shows the hourly wage of women working full time, but you could also look at the annual earnings of women overall and you could look at the annual earnings of women who worked only full year, full time. They would give different levels. An important feature is that the wage gap is narrowing regardless of which level you use.
The wage gap persists even between men and women with the same level of education. For example, in comparing men and women with a bachelor’s degree, women’s hourly wages were still 88% that of men in 2016. Likewise, women working in university-level STEM-related occupations earned on average $61,000 annually, compared to $71,000 earned by men. Part of the gender wage difference might be associated with the share of women who attain senior management positions. In the government sector, where employment equity legislation is in place, women are slightly more likely than men to be incumbent in leadership positions. In the private sector, only 26% of senior managers were women. Indeed, turning to slide 6, while the share of the top 1% of earners who were women rose steadily from 10% in the mid-1980s to more than 20% in recent years, the share is still well below 50%.
Moving to slide 7, I'll switch to talking a bit about low income. Low income, of course, is a strong signal of low economic well-being. It is important to underscore that low income is measured at the family level, so family characteristics play an important role in understanding low income. Many of the numbers I present are family-level statistics rather than those for women specifically.
Although family incomes have grown steadily over the past two decades, low income for women has been fairly steady, neither rising nor falling. In 2014, 13.5% of women lived in families with low income. This compares to 12.5% of men. Low income is higher for women and men in certain socio-economic groups, such as aboriginal persons, recent immigrants, persons with disabilities, unattached persons, lone parents, and persons belonging to a visible minority group. Lone-parent families, unattached seniors, and women aged 75 and over stand out as groups where low income is much higher for women than men. For example, women aged 75 and over had a low-income rate of 17%, compared to 9.4% for men.
Going to slide 8, it is well known that federal government transfers reduce low income. Different transfer programs affect different family types. For example, older families may receive OAS and GIS, while younger families are more likely to receive child benefits or employment insurance. In slide 8, we show how much higher the low-income rate would have been for different family types if their income did not include their main federal transfers. OAS and GIS reduce the low-income rates of elderly unattached and couples by a large margin, while child benefits reduce the low-income rates among lone parents and couples, though by a lesser degree.
Looking at elderly unattached women, we see that their low-income rate was 30%, but without their OAS and GIS it would have been 25% higher. Looking at women in lone-mother families, we see that their low-income rate was 40% in 2014, but would have been 8% higher without child benefits. In some cases, the transfer is not enough to lift the family above the low-income threshold, but it still reduces the gap, that is, the dollar shortfall below the low-income threshold for that family. For example, for women in lone-mother families, the low-income gap averaged $11,400. That means their shortfall, on average, was $11,400 below the low-income threshold, but it would have been nearly $20,000 without the child benefits they received.
On slide 9, I introduce our final topic today, which is retirement preparedness. Briefly, moving to slide 10, unattached women and lone mothers were less confident about their retirement prospects than other family groups were. They were less likely to be planning for their retirement. They were less likely to think their retirement income would be adequate, and for earlier retirees living unattached, they were less likely to think their current retirement income was adequate.
That brings me to the end of my discussion. Thank you very much.