Economic and Social Reports
Gender earnings ratio differences among population groups in Canada

Abstract

This study explores differences in mean annual earnings from paid employment between women and men within 11 population groups in Canada. Substantial differences were found in the gender earnings ratio within different population groups. The highest earnings ratio was observed among Black workers, where Black men had the lowest mean earnings of men in the 11 groups. The lowest earnings ratio was among Japanese workers, where men of Japanese origin had the highest mean annual earnings of all groups, surpassing those of White men. Differences in weekly hours worked and sector of employment explained substantial shares of the earnings differences between women and men in all population groups. Differences in occupational distribution further explained some of the gender earnings gaps for many groups. While the overall gender earnings ratio increased in Canada from 1996 to 2016, these gains were not distributed evenly across population groups. Southeast Asian and White women saw the biggest increases in their earnings relative to men in their population groups. There was essentially no change among Black and South Asian workers, and small declines were seen in the gender earnings ratio among Japanese, Latin American, and Arab and West Asian employees.

Keywords: gender gap, earnings, population group

Author

Aneta Bonikowska is with the Social Analysis and Modelling Division, Analytical Studies and Modelling Branch, at Statistics Canada.

Acknowledgement

This study was funded by Women and Gender Equality Canada.

The author thanks René Morissette, Marc Frenette, Marie Drolet and Mandana Mardare Amini for helpful discussions and suggestions on earlier drafts of this study.

Introduction

In the early 2010s, the average annual earnings of women aged 25 to 64 in Canada, as a fraction of similarly aged men’s earnings, hovered at a little above 68% (Bonikowska et al., 2019). Recent Canadian studies have also explored how the hourly wages and earnings of women from various broad subgroups of the population—immigrant, Indigenous and non-White non-Indigenous—compared with those of a common comparison group such as White Canadian-born men (Schirle & Sogaolu, 2020; Drolet & Mardare Amini, 2023). Qiu and Schellenberg (2022) looked at more disaggregated groups of younger Canadian-born workers, which showed notable heterogeneity in the weekly earnings of men and women from different non-White non-Indigenous population groups. However, gender pay gaps within more detailed population groups in Canada have not been explored directly.

This study examines earnings differences between men and women within 11 population groups. To gain a better understanding of the relative position of women in these groups in the labour force, the earnings of women in detailed population groups could be compared with, for example, those of men in the majority group, men in the group with the highest mean earnings (which may or may not be the majority group), men from the same population group, or women in the majority or highest paid population group. The group to be adopted as a reference partly depends on the objectives of the analysis, but each comparison would add another puzzle piece to the overall picture. No single comparison can tell the complete story of the earnings heterogeneity across groups if there is no consistent “gender effect” on wages or earnings across population groups or a consistent “ethnic or racial effect” by gender.

Breaking down the overall gender pay difference by population group offers new insights. First, cultural differences regarding gender roles across population groups may contribute to differences in the earnings of women from different groups and, thus, to the overall gender gap. Antecol (2001) showed that the gender wage gap in the United States varied across population groups, could not be entirely explained by differences in various individual characteristics and showed convergence to the mean among the second generation. Antecol argued that this pattern is consistent with cultural differences playing a role in explaining the overall gender wage gap in the United States. In Canada, large differences in labour force participation exist between immigrant wives from different source countries, ranging from just over 45% to over 90% (Morissette & Galarneau, 2016). These differences may extend further to weekly hours worked by women and their choice of occupation, both of which would contribute to differences in the gender pay gap across population groups. Second, comparing the earnings or wages of women from different population groups with those of men from the same groups controls for some unobservable factors more than is generally possible when comparing earnings of women from different population groups with a common comparison group, such as White Canadian-born men. For example, network effects are typically not taken into consideration in the study of gender pay gaps. However, some groups may rely on personal networks when searching for a job more than other groups, and those networks may yield different returns, in terms of the number or quality of job leads they produce (Battu et al., 2011; Pedulla & Pager, 2019). The network effect differences may be smaller when the men and women being compared are from the same population group. Similarly, while gender gap analyses generally control for differences in education level, they typically do not control for differences in education quality when immigrants who completed their education before arriving in Canada are included in the sample. Comparing men and women from the same population group would diminish such differences.

This study examines within-population-group gender differences in annual earnings among workers aged 25 to 64. Unlike studies that focus on determining whether women and men are paid equally for equal work and, thus, focus on gender gaps in hourly wages, studies that focus on annual or quarterly earnings differences between men and women instead cast a broader net. They capture also differences in labour supply, career progression and, ultimately, lifetime earnings, as well as explore where in the lifecycle gender pay gaps appear and widen, and why this occurs.^Note 

The paper proceeds as follows. The data and sample are described in the next section. The section after that presents and compares the within-population-group gender earnings ratios and the ratios of women’s earnings in the different groups compared with the earnings of White Canadian-born men. This is followed by a description of individual and job characteristics among men and women in the 11 population groups studied. A decomposition of the within-population-group earnings ratios in 2016 is presented, showing the extent to which differences between men and women in observable individual and job characteristics can account for the observed differences in earnings between them. Further details on within-group gender earnings ratios that exist within sectors and occupations are provided. Finally, changes in the within-group gender earnings ratios from 1996 to 2016 are documented.

Data and sample

The analysis is based on the 2016 Census of Population linked to the Longitudinal Worker File (LWF), an administrative dataset composed of data from four sources: the T1 and T4 tax files, the Longitudinal Employment Analysis Program, and the Record of Employment. The census is the source of crucial information on population groups. There are 11 population groups examined in this study: White, Chinese, Japanese, Black, Filipino, South Asian, Southeast Asian, Latin American, Korean, Arab and West Asian.^Note  Data on a rich set of individual characteristics were also drawn from the census: age, marital status, number of children younger than 18 in the census family, highest level of education, whether the highest level of education was obtained in Canada or abroad, temporary resident status, immigrant status, age at immigration, hours worked during the census reference week, occupation and location (consisting of indicators for province or territory of residence, and separately for residence in Vancouver, Toronto or Montréal).

Although each census contains information on annual earnings for the year prior to the census, this study uses 2016 earnings from the LWF instead.^Note  In addition, several other variables used in the analysis were also derived from the LWF, pertaining to the main job held in 2016, defined as the job (employer rather than position) with the highest earnings. These variables are union status, firm size, sector and tenure with the employer (measured in years and derived from LWF data from 1989 to 2016).

The main sample for the analysis consists of individuals aged 25 to 64 with annual earnings from paid employment of at least $500 and no self-employment income in 2016.^{Note  Note}  Earnings were top-coded to account for outliers.^Note  The sample includes Canadian-born individuals, immigrants and non-permanent residents who met the age and earnings restrictions listed above.

The gender earnings ratio

Two types of gender earnings ratios are presented in this section (Chart 1).^Note  The first is a ratio of women’s mean annual earnings by population group, each compared with the mean annual earnings of White Canadian‑born men. This places the results in the context of earlier Canadian studies on the gender wage or earnings ratio.^Note  The second type is the within-population-group gender earnings ratio, in which women’s mean earnings in a given population group are compared with the mean earnings of men in the same population group.

Compared with the annual mean earnings of White Canadian-born men, White women earned an average of $0.71 for every $1.00 earned by White men in 2016. Chinese and Japanese women were not far behind, at $0.70 and $0.67, respectively. Relative earnings dropped below 60% for other groups, with Black, Filipino and South Asian women earning an average of 58% to 59% of the earnings of White Canadian-born men. Southeast Asian, Latin American and Korean women earned about 55%, while Arab and West Asian women earned an average of about 53%.

When comparing women’s earnings with those of men in the same population group, one salient observation is that the relationship between the within-group gender earnings ratios and the gender earnings ratios relative to White Canadian-born men is not linear across population groups. For example, Chinese women earned about $0.78 for every $1.00 earned by Chinese men, on average—a higher proportion than when compared with White men. Meanwhile, Japanese women earned $0.59 for every $1.00 earned by Japanese men, on average—a lower proportion than when compared with White men. Compared with men in their own population groups, Black and Filipino women earned at least 20 percentage points more than when compared with White Canadian-born men. In all remaining groups (other than White), women’s average earnings were closer to those of men in their own group than to average earnings among White Canadian-born men. The percentage point differences in the two gender ratios varied by group, ranging from 10 to 19 percentage points.^Note 

The discrepancy between the two gender earnings ratios shown in Chart 1 arises from the fact that the ranking of population groups by average earnings is different among men than it is among women. Chart 2 shows the average earnings of men and women in each population group underlying the within-population-group gender earnings ratio. The lowest gender earnings ratio was observed among workers of Japanese origin, at 59.0%. Although the observed mean annual earnings of Japanese women were by no means the lowest of all population groups studied, the mean annual earnings of Japanese men were the highest, surpassing the mean earnings of White men, who came in second. The gender earnings ratio ranged from 67.4% to 69.3% among South Asian, Arab, West Asian and Latin American workers, respectively, just below the gender earnings ratio of 70.6% observed among White workers. The highest gender earnings ratio was observed among Black workers. While Black women had the eighth-highest mean annual earnings out of the 11 groups examined, Black men had the lowest mean annual earnings among men in the 11 groups.

Data table for Chart 1

Data table for Chart 1 Table summary
This table displays the results of Data table for Chart 1 Relative to White Canadian-born men and Relative to men in own population group, calculated using percent units of measure (appearing as column headers).

	Relative to men in own population group	Relative to White Canadian-born men
	percent
Sources: Statistics Canada, 2016 Census of Population and Longitudinal Worker File.
White	70.6	71.1
Chinese	77.9	70.2
Japanese	59.0	67.1
Black	83.9	58.5
Filipino	80.0	58.1
South Asian	67.4	57.9
Southeast Asian	74.7	55.3
Latin American	69.3	55.1
Korean	72.3	54.6
Arab	67.9	53.3
West Asian	68.3	52.9

Data table for Chart 2

Data table for Chart 2 Table summary
This table displays the results of Data table for Chart 2 Annual earnings , Women's earnings, Men's earnings and Earnings ratio , calculated using percent and dollars units of measure (appearing as column headers).

	Annual earnings		Earnings ratio
	Men's earnings	Women's earnings
	dollars		percent
Sources: Statistics Canada, 2016 Census of Population and Longitudinal Worker File.
White	68,723	48,523	70.6
Chinese	61,528	47,923	77.9
Japanese	77,488	45,752	59.0
Black	47,595	39,930	83.9
Filipino	49,497	39,620	80.0
South Asian	58,536	39,469	67.4
Southeast Asian	50,576	37,760	74.7
Latin American	54,215	37,574	69.3
Korean	51,578	37,268	72.3
Arab	53,580	36,379	67.9
West Asian	52,886	36,098	68.3

Descriptive statistics

The differences in gender earnings ratios observed across population groups may result from varying degrees of gender differences in sociodemographic and job characteristics (tables 1 and 2). Higher proportions of White and Filipino women had university degrees, compared with men in these groups, by a substantial margin: 31.0% versus 23.1% among White workers and 48.3% versus 37.8% among Filipino workers. These differences were either smaller or non-existent among other groups. Notable differences in the proportions of workers with a high school diploma or less were also observed between men and women among Black, Filipino and Latin American workers, with higher proportions of men than women having completed no more than a high school diploma. Among Black workers, this difference was offset by higher proportions of women than men obtaining a college or trades credential, while among Filipino workers, higher proportions of women had university degrees. Similar proportions of men and women obtained their highest postsecondary credential within each population group, with two exceptions. A higher proportion of Black women than Black men with a postsecondary credential had completed that credential in Canada (79.0% versus 67.5%), while the opposite was true among Japanese workers—59.2% of Japanese women with a postsecondary credential completed that credential in Canada, compared with 74.2% of men. The latter difference may be related to a gap in immigrant status between Japanese men and women; 45.6% of Japanese women were immigrants, 22.1 percentage points higher than among Japanese men. The corresponding difference between Black men and women was 2.4 percentage points, and differences among other population groups were similarly low.

Because the focus of this study is on annual earnings, differences in weekly hours worked between men and women will play an important role in accounting for the earnings differences between them. Women who worked during the census reference week were less likely to work full time than men in all population groups. While the majority of women worked full time, this proportion varied more among women than among men across population groups. Full-time rates were lowest among Arab, West Asian, Japanese and Korean women, ranging from 76.0% to 76.6%. The biggest gender difference in full-time employment was observed among Japanese workers, at 16.3 percentage points, followed by Arab, Korean and West Asian workers, respectively. At the other end of the scale, Filipino women were the most likely to work full time (87.1%), resulting in the smallest gender difference in full-time employment, 6.3 percentage points.

Aside from weekly hours worked, differences in job characteristics may play an important role in accounting for gender differences in earnings.^Note  Women were more likely than men to work in a unionized job in almost all population groups, with the highest gender gaps observed among Black (40.5% versus 31.2%), White (35.3% versus 27.7%) and South Asian (22.9% versus 15.6%) workers. By contrast, South Asian men and women had similar employment rates in unionized jobs, ranging from 19% to 20%. Women were also generally more likely than men to be employed by large employers (500 employees or more) in most population groups, with a gap of 6 to 9 percentage points among White, West Asian, Black, South Asian and Latin American workers.

Differences in occupation and sector of employment are further factors that likely contribute to the varying levels of gender differences in earnings across population groups. Occupational distributions varied across population groups, and in notable ways between men and women within some population groups but not others. For example, while women in all groups were more likely than men to work in personal and customer information services, particularly high proportions of Filipino (44.2%), Southeast Asian (33.0%) and Black (32.8%) women were employed in these types of occupations.^Note  These groups also saw the highest gender differences in the proportion employed in these types of occupations (with higher proportions of women than men), at 19.2, 14.6 and 13.4 percentage points, respectively.

Filipino and Southeast Asian women were less likely than women in other groups to work in professional occupations, at 12.2% and 15.3%, respectively, but so were the men in these groups (9.6% and 14.9%, respectively).^Note  The biggest gender gaps in the proportions working in professional occupations (with higher proportions of women than men) were found among White (23.9% versus 15.2%) and Black (20.1% versus 15.6%) workers. The biggest gender gaps that favoured men were smaller in magnitude, ranging from 2 to 3 percentage points, and were found among Korean, Chinese, West Asian and South Asian workers.

In all population groups, men were more likely to work in management positions (middle or senior management) than women. Among men, the highest proportion of workers in management positions was found among Korean and Japanese workers, at 18.8% and 18.3%, respectively, and the lowest among Filipino men, at 5.2%. The biggest gender difference in the proportion of workers in this occupation group was observed among Japanese workers, at 8.4 percentage points, and the smallest among Filipino workers, at less than 1 percentage point.   

Women in all groups were equally likely as men, or less likely, to work in occupations in manufacturing and utilities. Here, the largest gender gap was found among Filipino workers, with 5.9% of women and 17.8% of men employed in such occupations. Finally, 4% or less of women in all population groups worked in industrial, construction and equipment operation trades; as workers and labourers in transport and construction; and in natural resources, agriculture and related production occupations. The proportion of men who worked in these occupations varied widely across population groups, from as little as 11% to 12% of Chinese and Korean men to one-fifth to one-third of White, Black, Filipino, South Asian, Southeast Asian and Latin American men.

Different population groups were also distributed differently across sectors. Again, varying degrees of gender differences in sector concentration were observed across groups. Women were more likely to work in the health care and social assistance sector than men. This was particularly true of Black and Filipino women, who were more likely than women in other groups to work in the sector and far more likely than their male counterparts to do so: 33.5% of Black women worked in the sector (versus 7.6% of Black men), as did 30.6% of Filipino women (versus 8.5% of Filipino men). White women were a distant third place, with 20.8% employed in the sector. The educational services sector also generally employed higher proportions of women than men: 14.3% of Arab women, 13.5% of Japanese women and 12.8% of White women, proportions that were several percentage points higher than for men in each of these groups. By contrast, 2.6% of Filipino women worked in this sector, as did 2.4% of Filipino men. While lower proportions of women than men worked in the manufacturing sector overall, a large gender gap was observed in two groups: 17.5% of Southeast Asian women worked in the sector, compared with 31.4% of Southeast Asian men, and 8.3% of Filipino women worked in the sector, compared with 25.8% of Filipino men.

Decomposing the within-population-group gender earnings ratio

Gender differences in individual characteristics, job characteristics and labour supply (weekly hours worked) documented in the previous section contribute to the observed earnings differences between men and women within the various population groups. How much of the gap can be accounted for by such differences and how does this vary across groups? To answer this question, an Oaxaca–Blinder decomposition was conducted on the earnings difference between women and men for each population group.^Note 

The total portion of the within-population-group gender earnings difference that could be accounted for by differences in observed individual and job characteristics varied from 31% (representing $2,354 in annual earnings) among Black workers and among White workers (representing $6,311 in annual earnings) to nearly three-quarters for Korean workers (representing $10,402 in annual earnings).

Two factors stand out as most important in accounting for the observed differences in pay between men and women in all population groups.

The first is weekly hours worked. As shown in tables 1 and 2, average weekly hours worked were lower among women than men in all population groups, whether because of a higher incidence of part-time employment among women or because of fewer hours of overtime worked, which in turn could lead to less overtime pay (where applicable) and potentially fewer bonuses (Grund, 2015).^Note  Differences in weekly hours worked explained from 16% of the differences in earnings between women and men (or $5,189) among Japanese workers to 34% (or $2,630 in annual earnings) among Black workers.^Note 

The second factor was the sector of employment. Differences in sector of employment accounted for from 10% of the difference in earnings among Japanese workers (representing $3,232) to 40% among Black workers (representing $3,101).

Differences in the distribution of occupations among women and men accounted for more than 10% of the pay difference among West Asian, South Asian, Chinese, Korean and Japanese workers. Among White workers, differences in occupations accounted for very little of the gap, while among Black workers, differences in occupational distribution predicted higher earnings for women than men. Occupational differences that favoured women were also observed among Filipino workers, accounting for 8% of the pay difference. In addition, differences in education level that favoured Filipino women (rather than men) implied that the pay gap should be smaller than that observed.

Firm size differences generally accounted for a small proportion of the observed pay differences, with a couple of exceptions. These differences favoured women (rather than men) in several groups, accounting for the most substantial proportion of the pay difference for Black women. By contrast, firm size differences explained 13% of the earnings gap between Filipino women and men. Differences in tenure with employer between men and women also generally did not explain much of the observed earnings differences, with the exception of Black workers, where differences in tenure predicted higher pay among women than men.

Gender earnings ratios across sectors and occupation groups

Differences in sector of employment between men and women played a substantial role in explaining earnings differences between them, as shown in the previous section, and this section documents differences in pay between men and women in different population groups within sectors (Table 4).

The gender earnings ratios were, on average, highest and varied least across population groups among public administration employees, ranging from mid-70% to mid-80%. Similarly high ratios were also observed among employees in educational services, with the exception of Arab employees, where women earned on average 66.5% of what men earned in that sector. More variation in the gender earnings ratio was observed in the health care and social assistance sector, with the highest ratio at 86.1% among Filipino workers and the lowest at 56.3% among Arab workers.

Sorting into different occupations within sectors may explain part of the differences in average earnings between men and women across sectors. Although sample sizes would not allow for a detailed examination of occupational distributions within sectors by population group, Table 5 shows how gender pay ratios compare across broad occupation and population groups. Workers in administration and administrative support and in personal and customer information services registered relatively high gender earnings ratios that varied relatively little across population groups. High gender earnings ratios were also observed in professional and management occupations, with more variation across population groups. For example, the gender earnings ratio among Chinese workers in management occupations was 90.9%, but it was 65.0% among Japanese workers.

By contrast, technical and paraprofessional occupations recorded substantially lower earnings ratios than professional occupations for all population groups. Some of the lowest gender earnings ratios were found among workers in sales, ranging from 49.0% to 75.4%. Natural resources, agriculture and related production occupations, as well as occupations in manufacturing and utilities, also registered below-average (across occupation groups) gender earnings ratios for many population groups.

Changes in the gender earnings ratio from 1996 to 2016

The ratio of women’s mean annual earnings to those of men among workers aged 25 to 64 has increased from 1996 to 2016, moving from 64.7% to 71.0% overall. However, these relative gains were not distributed evenly across population groups (Chart 3).^Note  The biggest increase in women’s mean annual earnings relative to those of men was observed among Southeast Asian employees, rising by 8.1 percentage points from a base of 66.6%, followed by White workers, rising by 6.6 percentage points from a base of 64.0%. Smaller increases were also observed among Korean, Chinese and Filipino employees. Essentially no change was observed for South Asian and Black workers. Meanwhile, the gender earnings ratio fell by nearly 3 percentage points from a base of 70.9% among Arab and West Asian workers, with smaller declines registered among Latin American and Japanese workers. Mean real earnings (in 2016 dollars) increased for men and women in each group from 1996 to 2016. The differences in direction of the changes in gender earnings ratios across groups stem from whether women’s or men’s average earnings increased faster over this period.

Data table for Chart 3

Data table for Chart 3 Table summary
This table displays the results of Data table for Chart 3 2016 and 1996, calculated using percent units of measure (appearing as column headers).

	1996	2016
	percent
Sources: Statistics Canada, 1996 and 2016 censuses of population, and Longitudinal Worker File.
White	63.9	70.6
Chinese	75.0	77.9
Japanese	60.9	59.0
Black	83.7	83.9
Filipino	77.6	80.0
South Asian	67.1	67.4
Southeast Asian	66.6	74.7
Latin American	71.2	69.3
Korean	68.9	72.3
Arab and West Asian	70.9	68.0

Conclusion

Although much has been written about the evolution of the gender pay gap in Canada, no studies have looked explicitly at how the gender pay gap varies by population group in Canada. Cultural differences that lead to varying levels of labour supply of women across population groups—at least among immigrants, but also possibly among subsequent generations raised in Canada—are one factor that could contribute to varying differences in the annual earnings of women and men from different population groups.

This study fills this gap in the literature by exploring differences in average annual earnings from paid employment between women and men within 11 population groups. The within-population-group gender earnings ratios varied from 59.0% among Japanese workers to 83.9% among Black workers. Black women recorded mean earnings that were higher than those of women from several other groups, while Black men had the lowest mean earnings of men in the 11 groups. By contrast, among Japanese workers, men had the highest mean annual earnings of all groups, and women had mean annual earnings that surpassed the mean across all groups. Women in the various population groups ranked differently when their earnings were compared with those of White Canadian-born men instead. Japanese women fared better in this comparison than they did relative to Japanese men. All other groups fared worse, by varying amounts.

Differences in weekly hours worked and sector of employment explained substantial shares of the earnings differences between women and men within all population groups. Occupation differences also explained non-trivial portions of the gaps for many groups.

While the gender earnings ratio has increased in Canada from 1996 to 2016, these gains were not distributed evenly across population groups. Southeast Asian and White women saw the biggest increases in their earnings relative to their male counterparts. There was essentially no change for Black and South Asian workers, and small declines were observed in the gender earnings ratios for Japanese, Latin American, and Arab and West Asian workers.

Looking ahead, gender earnings ratio estimates by population group among individuals aged 25 to 64 in 2019 and 2021 (not reported) showed relatively little change from the 2016 estimates. For some groups, the gender earnings ratio fell somewhat over time, while for others it increased. However, these small changes could be due to differences in sample composition driven by data availability or temporary effects of the COVID‑19 pandemic. More data will be needed to explore the longer-term evolution of the within-population-group gender earnings ratios since 2016.

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