1. Abstract
This study looks at differences in male and female wages using data from Statistics Canada’s annual Survey of Consumer Finance (SCF) and Survey of Labour Income Dynamics (SLID). In addition to information on annual income, this study also looks at hourly wage data, which is a more precise measure as the earnings data series takes into account the price of labour as well as quantity (i.e. individuals’ work/leisure preferences). This study looks at the variables of race, highest achieved level of education as well as age to examine the existence of a wage gap. Like other studies, we have found that males have a higher wage in each of these areas, with females earning an average of 80 – 87% of the males’ average. Furthermore, we have examined the existence and size of a wage gap in three industries; law, nursing and the education industry. Finally, we looked at the Canadian gender-based wage gap statistics compared to International gender-based wage gap statistics. We deduced that there is, indeed, a wage gap in each of the mentioned industries, and can be partially attributed to human capital theory and occupational segmentation theory, however, a substantial portion of the gap remains unexplained.

2. General Existence of Gender-Based Wage Differentials in Canada
The existence of gender based wage differentials in North America have been well documented for decades. Although female-male wage ratios have closed significantly since the mid 1980s, progress in wage equalization has seen some stabilization in recent years. Many past studies on wage differentials in Canada, including Statistic’s Canada’s “Income Trends in Canada” report, use male and female annual earnings data as opposed to hourly wage data. Baker and Drolet (2010) show that these two different data series create two very different trends in terms of male and female income. These differences can primarily be attributed to the fact that the earnings data series takes into account the price of labour as well as quantity (i.e. individuals’ work/leisure preferences), whereas the data series based solely on wage information can more accurately articulate the actual price of labour alone without being skewed by possible preference trends. Based on the earnings data collected by way of the Survey of Consumer Finances (SCF) and the Survey of Labour and Income Dynamics (SLID), the female-male ratio based on full-year full-time (FYFT) workers’ annual earnings has steadied to around 70% since 1992 as seen in Figure 1. This prolonged period of relative stability can be somewhat perplexing given the policy changes enacted by Canadian governments to improve pay equity, “For example, pay equity laws now cover federal workers, public sector workers in many provinces, and private sector workers in Ontario and Quebec.” (Baker, Fortin 2004). This is especially intriguing when it is clear that wage-based ratios tell a much different story. Figure 1 clearly displays a significant amount of discrepancy between earnings- and wage-based ratios. The wage-based ratio is consistently over 10 percentage points higher and shows a gentle upward trend indicating gradual progress in pay equity over the years compared to the earnings-based ratio which seems to stall at around 70%. The higher degree of variation found in the earnings-based ratio during the mid 90s can be attributed to increases in male unemployment levels which lower the difference between earnings- and wage-based ratios, most likely caused by a decrease of the gender difference in hours during recessionary periods as suggested by Baker and Drolet (2010). There is a crucial distinction to be made when wage-based data shows the apparent effectiveness of pay equity legislation whereas earnings-based pay does not. The distinction, as mentioned previously, amounts to earnings data encompassing the price of labour as well as individuals’ decisions on how much to work, which directly correlates to gender gaps in labour supply. This adds more variability and difference in data because work/leisure preferences between genders are, of course, not equal. Wage-based data solely takes into account the price of labour which essentially “...defines gender-based labour market discrimination.”(Baker and Drolet 2010). It is quite possible that public perceptions of gender based wage gaps have been heavily influenced by earnings based data. Until only recently, most media stories, studies and even
Canadian policy debate have been driven by earnings based ratios rather than ratios based directly on hourly wages which are, in actuality, the foundation of pay equity legislation. The importance of the differences between these two data series cannot be understated when there is easily an opportunity for the public to be misled in regards to pay inequity and the effectiveness of pay equity legislation in Canada.

3. Evidence of Male-Female Wage Differentials

3.1 Race
Women and black men have lower average hourly earnings than white men with the same number of years of education (Weinberger, 1998; as cited by Corcoran and Duncan 1979; Blau and Ferber 1987). Dr. Hilary Lips of Radford University observed in 2001 that, in the United States and Canada, Hispanic Women had the lowest wage gap between their male counter-parts, earning 85% of the male wage. Black women earned 83% of what Black men earned, and Asian/Pacific Island women earned 74% of what Asian/Pacific Island men earned. The largest wage gap was help by White women who earned 73.4% of what White men earned (See Figure 2). Although the gap can be partially explained by traditional family values and occupation segmentation theory, there is much left unexplained.

3.2 Level of Education
Higher levels of education are strongly correlated with higher wages for women, but even more so for men. In fact, as men and women attain greater amounts of education, the wage gap between them widens. As seen in Figure 3, Dr. Lips discovered that women earned 76% of what men earned when both groups possessed less than a grade 9 level of education, 73% at the high school graduate level, slightly more at 75% with a Bachelor’s degree, 72% with a Master’s degree and only 60% with a Professional degree. Statistics Canada partially attributes the chosen field of study to these results.

Many fields of study are dominated by either men or women and this may impact the gender pay gap. For instance, graduates of engineering, applied sciences technologies and trades fields are mostly men while on the other hand, women are over-represented among college graduates with a commerce or business administration degree, and among health and education fields. Since wages differ by field of study, the choice of major field of study by men and women may account for some of the gender pay gap.

3.3 Age
The wage gap between males and females is smallest among young workers between the ages of 18 to 24, with females earning 85% of what 18 to 24 year old men earn, according to the Survey of Labour and Income Dynamics (SLID). Drolet (1999) accredits the small gap with relatively low levels of education among both sexes, similar skills and labour market experience, as well as the effects of career advancements and family and household responsibilities having not yet taken place. The wage gap widens for males and females between 24 and 35 years of age with females earning 81% of male wages (Wage Indicator, 2011). By age 45, males have accumulated an average of 6.4 more years of work experience than females, largely due to family and household responsibilities. “This may explain why the gender pay ratio falls steadily with age – women aged 45-54 earn about 75% of the average hourly wage rate of men 45-54 (Drolet, 1999).” (See figures 4 and 5).
Although the wage gap widens considerably with age, it does so at a slowing rate (Wage Indicator, 2011), and in recent years, has begun to slow at all age levels. This is partially due to the fact that many Baby Boomers in Canada are reaching retirement age, thus leaving the work force, and making room for the next generation. Younger generations of females are setting trends by; achieving higher levels of education, focusing more on education and careers earlier in life and starting families later on, if at all, and also waiting longer to get married, thus, spending more time working to support themselves as the sole income provider (Drolet, 1999).
4. Gender-Based Wage Differentials in Different Industries

4.1 Lawyers
An investigation on gender based pay differentials in the male-dominated law field (lawyers produced initial findings indicating a rather surprising female-male earnings ratio of just .62 based on average annual earnings) (Robson and Wallace 2001). This is somewhat puzzling considering Baker and Drolet (2010) found University graduates see an average wage ratio around .85. A sizeable portion of the discrepancy between male and female earnings and the wage and earnings ratios can be attributed to characteristics of both human capital and occupational segmentation theories. The human capital theory accounts for labour supply characteristics that include individuals’ education choices, work preferences “...and how differences in workers' investments in their human resources result in different rewards.”(Robson and Wallace 2001). Based on this theory, Robson and Wallace (2001) conclude that males and females are not differentially paid based on any “career investment” characteristics such as firm-specific work experience, education and leisure time preferences. Rather they conclude that female lawyers, on average, have less significant work experience, work less hours and are more likely to take leaves of absence based on family needs such as maternity. “Therefore, although lawyer's sex does directly determine earnings, it is clearly related to many of the important predictors of lawyers' earnings.”(Robson and Wallace 2001). The occupational segmentation theory also takes into account labour demand and “...emphasizes the broader context of institutional work structures as sources of inequality and views these structures as discriminatory.” (Baron and Bielby, 1980 as cited by (Robson and Wallace 2001). Essentially the segmentation theory suggests women have constraints and barriers that may not allow for progress towards earnings levels similar to that of their male colleagues. Past studies, although dated, have found some support for this argument, finding that female lawyers are “often assigned smaller, less significant, and less complex files than their male colleagues.” (Liefland, 1986; Pollock and Ramirez, 1995 as cited by Robson and Wallace 2001). It is very difficult to determine what portion of the earnings gap between female and male lawyers can be attributed to either the human capital or occupation segmentation theories. Robson and Wallace (2001) suggest viewing both theories together as a singular hybrid model for wage and earnings discrepancies between genders. The issue then becomes determining the proportion or prevalence of each phenomenon where distinguishing between the two theories becomes near impossible.

4.2 Nursing
An investigation on gender based pay differentials in the female-dominated field of nursing found results not unlike those supported by the human capital theory employed in the research done by Baker and Drolet (2010) on gender-based pay differentials in law. Jones and Gates (2004) conclude that “...nurses who were male, prepared at higher educational levels, possessed more years of experience, employed in a management or advance practice positions, employed in certain geographic regions of the country, or employed in an MSA earned significantly higher wages than their female nurse counterparts.” Their research also concluded male registered nurses were consistently shown to have a wage premium based on findings that male registered nurses “possessed more wage-generating endowments than females”. Despite the evidence found supporting human capital theories on the observed wage differential, a large portion of the differential remains unexplained by Jones and Gates (2004). This again points to possible discriminatory phenomenon taking place and may rely more on theory of occupation segmentation to find possible explanations in future research. In an earlier study, Kalist (2002) suggests that over 90% of an observed 12% male-female wage difference could potentially be attributed to some sort of discriminatory behaviour whether it be direct or indirect.

4.3 Education Industry
Efforts to explain gender-based wage differentials have included the argument that women are twice as likely as men to be employed as part time educators (Hagedorn, 1996). Part-time status generally reduces the chance of promotions, thus leading to stagnant wages. Hagerdorn (as cited in Braskamp and Johnson, 1978; Snyder, Hyer, and McLaughlin, 1993) also found that salaries often also positively correlate with past and present administrative work in the form of committees and departmental leadership; all of which are rarely available to a part-time worker. A snowball effect is evident as “those with administrative authority provide powerful input in policymaking committees, as well as tenure, promotion, and search decisions (Hagerdorn, 1996).”
Another argument is in favour of occupation segmentation, claiming that females tend to teach at lower education levels than men, dominating the kindergarten to secondary levels, with 80% being female (Pytel, 2006). At the post-secondary level, females make up only 20% of full-time professors and 33% of part-time professors (Millar, 2010). Janet Steffenhagen reported in 2010 that, according to Statistics Canada, male University Professors continue to out-earn their female counterparts by as much as $20,000 in some cases. “The difference is not necessarily because of current biases in favour of men, rather; it's a result of earlier hiring practices that favoured men, the age and position of professors and their distribution throughout universities. Faculties such as business, hard sciences and engineering traditionally pay more and attract more male professors; humanities and social sciences, which are more likely to attract female professors, pay less (Hillan, as cited by Steffenhagen, 2010).”

5. Canadian Wage Differential Statistics Compared to International Statistics
In comparing annual earnings data between Canada and the United States, we see relatively similar trends up until around 1990 where the Canadian female-male earnings ratio begins to stall at around .70 while the US ratio continues to trend upward reaching over .75 (See Figure 8). Of course, some of these discrepancies can be partially attributed to human capital differences between populations, but Olivetti and Petrongolo (2008) provide a conclusion “that gender wage gaps across countries are negatively correlated with gender employment gaps.” This conclusion is supported in data from the Organization for Economic Co-operation and Development (OECD) (See Figure 6) which indicates a higher gender employment gap in the US than in Canada which corresponds to the lower earnings gap and higher female-male earnings ratio in the US.
In Europe, much of the same human capital theory can be applied to the very wide range of gender pay disparity seen from over 30% in Estonia to slightly over 5% in Italy (See Figure 7). EuroStat reports mention several human capital factors that influence these very diverse gender pay gaps such as placement of women in the labour force, consequences of temporary career leave due to child bearing and more generally, decisions that favour toward family life. Similarly to the conclusions found by Olivetti and Petrongolo (2008), EuroStat also identifies gender employment gaps as cause for disparity between nations’ gender pay gaps. Although some of the gender pay disparity among nations and individuals can be attributed to the human capital characteristics mentioned above, there is undoubtedly some level of discriminatory behaviour at play within all populations. Occupational segmentation theories can help understand the nature of this behaviour, but it is difficult to quantify the effect of these phenomena on the labour force.

6. Conclusions
Like other studies, we found that males receive a higher average wage in each race, level of education and age that we examined; with females earning an average of 80 – 87% of the males’ average. In the law industry, we found that human capital characteristics as well as occupational segmentation theory accounted for the majority of wage gap between male and female lawyers, but still leaving a sizeable portion, as with many gaps covered in our research, unexplained. Jones and Gates (2004) concluded that “...nurses who were male, prepared at higher educational levels, possessed more years of experience, employed in a management or advance practice positions, employed in certain geographic regions of the country, or employed in an MSA earned significantly higher wages than their female nurse counterparts.” In the Education sector, the wage gap was partially caused by males and females teaching at different levels; with females dominating the kindergarten to secondary level, and males being 4 times more prevalent at the post-secondary level. Males also tended to specialize in Faculties such as business, hard sciences and engineering traditionally pay more and attract more male professors; humanities and social sciences, which are more likely to attract female professors, pay less (Hillan, as cited by Steffenhagen, 2010). Overall, we found that wage gaps are beginning to close, very slowly, as females begin to prioritize education and career over marriage and starting a family at a young age. Many females are also having less children, if any at all, reducing the amount of time they take of work, and therefore, slowly shortening the average 6.4 years of extra work experience males have. Although much of the wage gap can be explained by economic theories such as the human capital theory and occupational segregation theory, much of the wage is still unexplained.

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Data Sources:
EuroStat
Organization for Economic Co-operation and Development
Statistics Canada
United States Census Bureau