Executive summary
This analysis examines hourly pay in 2023, with a view to understanding differences between public and private pay practices. The public sector is broadly defined, including public administration at all three levels of government, protective services, and publicly funded health and education.
The analysis is using the Labour Force Survey and adjusts for 15 common factors to ensure we are comparing like-to-like workers: gender, public/private sector, age, marital status, education, tenure, job permanence, full/part time, workplace size, industry, occupation, immigration, province, CMA, unionization using two standard economic techniques ordinary least squares and unconditional quantile regression.
Before delving into public vs. private pay practices, it is clear that discrimination is alive and well in Canada. Women were paid 8.5 per cent less than men in 2023, even after adjusting for the 15 factors. Wage discrimination is also in play for recent immigrants, who are paid eight per cent less than Canadian-born workers, after adjusting for the factors above. The adjusted average shows little difference between public and private sector wages but it obscures important underlying differences.
Public and private sectors have substantially different discriminatory pay gaps hiding below the surface.
In the private sector, men make 10 per cent more than women. In the public sector, the gender pay gap is only five per cent. Put another way, women in public sector make four per cent more than women in private sector. This reduction in the gender pay gap is offset by men’s wages in the public sector—they make slightly less in the public sector compared to the private sector. Therefore, the gender pay gap is smaller in public sector due to the fact that women’s wages are raised and men’s are slightly lowered.
An important part of lower pay for women is the presence of children. Women often suffer a motherhood penalty: their pay drops when they have children, whereas men experience a fatherhood premium. There is some evidence of a motherhood penalty in the private sector, but the fatherhood premium is a massive 15 per cent in the private sector and smaller in the public sector, at 7 per cent.
The public sector’s impact on gender pay equity is very concentrated among middle- to middle-low income earners who were making around $20 an hour in 2023. At that income level, women in the public sector make roughly the same as men in both the public and private sectors, achieve pay equity. It’s a rare phenomenon.
In the upper half of the income spectrum, women and men in the public sector make less than their private sector counterparts. Also, the gender pay gap widens in both sectors at higher-income levels.
The public sector also closes the discriminatory pay gap for new Canadians. In the private sector, landed immigrants are paid eight per cent less, even after adjusting for our 15 factors. By contrast, the public sector pays new Canadians three per cent less than private sector Canadian-born workers in 2023.
An examination of occupations reveals similar patterns, where the public sector is lifting bottom-end wages while keeping high-end wages in check. Senior managers are paid a whopping 29 per cent less in the public sector. Health professionals, like doctors, dentists and optometrists, are also paid less in the public sector, likely due to public Medicare constraining their wages.
On flip side, educators, including those in primary, secondary, university and colleges, are paid more in the public sector. Key areas of education are heavily dominated by women, who seem to be getting a fairer shake in public schools, compared to private schools. Social workers/councillors are also better paid in the public sector.
When you compare like-to-like factors, there is little difference between average public sector and private sector hourly pay, however, important discriminatory pay gaps couldn’t be more different behind these broad averages. The public sector raises pay for those experiencing discrimination: women, mothers, and new Canadians while it lowers pay for men, fathers, executives and medical professionals. Public sector pay does this mostly by providing pay equity for women making around $20 an hour while reducing pay for those making over $100,000 a year. The private sector does the opposite, increasing discrimination, overpaying executives and boosting high-end wages even higher. These are two very different ways to get to the same average place, one with more equality through wage compression and one with less equality through pay extremes.
The public sector hasn’t erased discrimination and ensured gender equality, but it performs better on this measure than the private sector. While there is still work to be done to eliminate the gender pay gap, the public sector is further along than the private sector, where the pay gap is twice as big as the public sector.
It’s time for the private sector to pay more like the public sector—that’s the key to reducing income inequality in the workplace.
Introduction
Several high-profile public sector strikes in 2023 have highlighted the importance of pay in the public sector. Public sector average hourly pay has fallen behind private sector pay since 2021, when the pandemic re-opening hit its stride, but inflation started to peak above three per cent.
By the end of 2023, private sector workers had managed to claw their way back from the impact of inflation, returning to the purchasing power, based on hourly wages, that they had in 2021. Once inflation is included, this equates to a one per cent wage gain since 2021, which isn’t tremendous, but at least they hadn’t taken a pay cut.
Once inflation is considered, public sector workers can buy four per cent fewer goods and services than they could in 2021. This is a slight improvement from the more than six per cent real wage cut that they suffered in June and July of 2022, but it leaves those workers with a real pay cut of four per cent over the past two years.
The public sector includes those who are working directly for federal, provincial, municipal and Indigenous governments as well as anyone whose job is funded by government in some capacity, even if that person is not directly employed by a government. Roughly half of health care workers fall into this category, as do most workers in the education sector, from primary school through university and colleges. Social services, policy, emergency services all count as public sector workers under the labour force survey definition. Appendix B continues this discussion.
The public sector: closing pay gaps
This report examines the hourly wage rate differences between public and private sector workers in 2023. In 2023, the raw average hourly wage of public sector workers was $24.87, compared to $20.18 in the private sector. However, a proper comparison should involve comparing like-to-like workers.
For example, 50 per cent of public sector workers have a university degree, compared to only 29 per cent in the private sector.1 One would expect people with more education to make higher wages. To do a proper comparison of pay rates, factors like education should be adjusted for.
Creating an average hourly wage difference that takes these factors into account can be accomplished through Ordinary Least Squares (OLS) regression, a common technique in economics. This allows us to adjust for education and 14 other worker characteristics that might affect a one’s hourly wage including:
- Public vs. private sector
- Gender
- Age
- Marital status
- Education
- Job tenure
- Job permanence
- Full time/part time
- Employee count at workplace
- Job industry
- Occupation
- Immigration status
- Province
- Census Metropolitan Area
- Unionization
In the analysis below, all these factors are included, meaning that when we’re looking at any individual factor, like private vs. public sector pay, the average difference in pay adjusts for all 15 factors.
Clearly, that list is missing other items that can affect a worker’s pay, such as if a worker is racialized or Indigenous. Those variables are not available in Statistics Canada’s Labour Force Survey Public Use Microdata File (PUMF), which is used in this analysis, otherwise they would have been included because those are two important factors. Starting in the summer of 2021, Statistics Canada started to include race and Indigeneity in its underlying survey and hopefully they will soon be included in the PUMF, as this would improve our understanding of wage drivers in Canada.
There are some occupations and industries that have few workers on either the public or private sector side; these workers are still included in this section, but additional analysis of wage differences is in the “which occupations are paid more” section.
Table 1 provides our starting point for looking at wage differences between different categories of workers, other things being equal. The differences are presented in percentages, not dollars, because they include everyone up and down the income spectrum. A $1-an-hour increase in wages is a much bigger raise for someone making $15 an hour than someone making $55.
The comparisons in Table 1 are made within each variable only and are with respect to the reference category. The choice of reference category is arbitrary. Any value for the variable could be chosen and the percentage difference would remain consistent. As shown in Table 1, after adjusting for our 15 variables, men are paid 8.5 per cent more than the reference category, which, for the gender variable, is women. We could have just as easily picked men as the reference category, in which case women would be paid 8.5 per cent less.
Also note that this table tells us nothing about how women in the public sector are paid compared to men in the public sector. The percentage differences are only applicable to the reference category for that variable, although approaches later in this report allow us to investigate those differences.
This model’s adjusted R square is 0.61, meaning that 61 per cent of the differences in hourly wage for Canadian workers is explained by this model, but 39 per cent of the differences remain unexplained. This is relatively high for a model of this kind, meaning that it explains a good deal of the variation in hourly wages and the findings are robust.
Including the 15 factors that are driving pay, there is little difference between public and private sector pay, standing at only 2.5 per cent in favour of public sector employees in 2023. However, as we’ll see below, the similarity in pay ,on average, obscures systemic differences in how subgroups are paid. Private sector pay incorporates lower pay due to discrimination against some groups and overpayment to richer workers. Public sector pay closes those gaps in important ways, but those details are erased in the average, making it seem like pay levels are similar, even if they are quite different once those details are examined.
When looking at various groups facing discrimination, there is plenty of room to pay people more fairly in Canada, with the basic model showing significant pay gaps for women and new Canadians, even after adjusting for all 15 factors. The initial model reveals that men get paid 8.5 per cent more than women, after all other variables are taken into account. A woman in Canada with the same level of education, working in the same industry and occupation, of the same age with the same tenure, both working full-time in permanent jobs in the same-size workplace in the same city and province would, on average, still be paid almost 8.5 per cent less than a man in 2023. This still doesn’t tell us if the gender pay is bigger or smaller in the public sector.
As with any model of this type, there may be missing variables that, once included, could reduce the gender pay gap and explain the pay difference some other way but many of the key factors are included.
There is a similar situation for new Canadians. Recent immigrants who arrived in Canada in the past 10 years get paid nine per cent less than a non-immigrant, on average. Again, this compares similar workers that work in the same industry and occupation, have the same age, tenure, education and gender, and live in the same province and city. There may be an additional variable, such as language at birth or racialization, that eliminates possible discrimination against immigrants, but in this example, it would just shift that discrimination to another variable, say racialization (a variable that isn’t included in the dataset being used and so can’t be included in this analysis).
The public sector and the gender pay gap
Looking at these two possible types of discrimination in Table 1 (gender and immigration status), it’s worth asking if the public sector attempts to close the pay gap compared to the private sector. Let’s start with gender. Here, we need to interact the gender and public/private sector variables to obtain Table 2. For a discussion of stratification vs. interaction, see the methodology section.
Table 2 presents a similar approach to Table 1, with the various categories of wage differences compared to the reference category, in this case women private-sector workers. As in Table 1, the 13 other factors not shown in the table are held constant: age, marital status, education, tenure, job permanence, full/part time, workplace size, industry, occupation, immigration, province, CMA, unionization. Table 2 is a summarized version of the full table available in appendix table A.
Table 2 starts to show the narrowing gender pay gap in the public sector employment. In the private sector, men are paid 9.7 per cent more than women (women private sector workers are the reference). However, the gender pay gap in the public sector is much smaller: five per cent, with men making 9.3 per cent more than the reference and women making 4.2 per cent more than the reference. Women are more fairly paid in the public sector and that is why the gender pay gap is much smaller than in the private sector. Women working in the public sector make 4.2 per cent more than women with similar characteristics who are working in the private sector. Interestingly, the public sector doesn’t just close the gap by raising women’s wages, it also does it by slightly lowering men’s wages by 0.4 per cent compared to what they’d make in the private sector.
The public sector hasn’t erased discrimination and ensured gender equality, but it performs better on this measure than the private sector. While there is still work to be done to eliminate the gender pay gap, the public sector is further along than the private sector, where the pay gap is twice as big as the public sector.
While the public sector is paid more, on average, it’s being paid more because women who are discriminated against for being women in the private sector are still being discriminated against in the public sector, just by a smaller amount.
The motherhood penalty and the fatherhood premium
One of the factors in the gender wage gap is the presence of children. While not in the base model in Table 1, the presence of children aged 18 and under is included in Table 3. The presence of children, as a variable, interacts with gender and class of worker. As before, the other 13 factors are included and held constant. There are two trends that often involve gender and children: the motherhood penalty and the fatherhood premium. Briefly, women with children make less than those without children because they are treated in the workplace as less competent and having fewer loyalties to their job while the opposite happens to men. Men make more once they have children because they are treated by employers as more competent as a result of fatherhood. A more complete discussion of this literature is available in Appendix C.
Table 3 summarizes the results of these interactions, although the complete table is available in Appendix table B. In the 2023 labour force survey data, women in the private sector experienced a mild motherhood penalty. Other things being equal, they were paid less (-0.5 per cent) after having at least one child. Women in the public sector don’t get that motherhood penalty. Instead, they see a mild motherhood premium of 1.3 per cent because they get paid more with the presence of a child, after adjusting for our 15 factors (education, age, geography etc.), other things being equal.
Since this analysis focuses on hourly wages and not income, which would include hours as well, it won’t fully capture the impact of parenthood on workers. Workers might see an impact on wages of parenthood and an impact on hours worked, something this analysis doesn’t assess.
However, the fatherhood premium is alive and well in both the public and private sectors. In the private sector, men with children are paid seven per cent more than male private sector workers, whereas men within children in the public sector make 4.5 per cent more than male public sector workers without children.
If men do not have children, they make similar amounts, at 7.4 per cent and 7.6 per cent in the private and public sectors, respectively, more than the reference group.
As with the gender-only model, the gender pay gap in the public sector is there either with or without children, but it’s smaller than the gap in the private sector. The gender pay gap for those without children is 7.4 per cent in the private sector but only 3.8 per cent in the public sector. Once workers have children, the gender pay gap in the private sector is quite large, with men seeing hourly wages 14.9 per cent higher than women, whereas in the public sector, men with children have a seven per cent higher wage than women with children.
As before, it’s not that the public sector eliminates the gap between men and women with children, it makes the gap smaller.
The public sector and new Canadians
As Table 1 shows, immigrants also face a significant wage penalty for being new to Canada, even after considering our 15 factors: education, age, industry, occupation and so on. To examine the public sector’s impact on immigrant wages, Table 4 shows the interaction between the public/private sector variable and immigration.
If we look at non-immigrants in Table 4, public sector workers are paid only slightly more than private sector workers, on average, although the difference is even smaller than the initial adjusted difference of 2.5 per cent from Table 1. However, the wage penalties for being a new Canadian are severe, particularly in the private sector. The public sector also discriminates against immigrants, but to a lesser degree. In the private sector, immigrants who have been in Canada for over 10 years are paid 7.9 per cent less for being new to Canada, all other factors held equal. The public sector also pays new Canadians less, but the penalty isn’t as severe for new Canadians who landed over 10 years ago; they’re being paid 3.1 per cent less than private sector non-immigrants. Within the two sectors, the immigrant pay gap is smaller in the public sector, at five per cent, whereas it’s 7.9 per cent in the private sector.
As with the examination of gender, it’s not that the public sector eliminates the immigrant pay gap, but it narrows it, making the penalty for being new to Canada smaller in the public sector.
In addition to looking at closing gaps in areas where discrimination is measured, we can look at different occupations to determine which are paid more in the private sector and which are paid more in the public sector. Instead of stratifying the data with each new dataset containing only a single occupation, the strategy of interacting variables, as in the regressions above, is used. This allows us to improve the high explanatory value of the model instead of substantially reducing it. Interaction does not force interactions between occupation and all other variables, as is the case with stratification.
Which occupations are paid more in the public and private sector?
Table 5 presents a summary of the results, as well as the average monthly counts of workers, by occupation. If we examine the outlying occupations, where one side is paid at least 10 per cent more than the other, several stand out. We restrict this overview to occupations that have at least a monthly average of 5,000 workers on both sides. For instance, machine operators and labourers show a large difference in pay between the sectors, but there are very few of them in the public sector.
Despite several of the occupation categories employing workers almost entirely on the public or private sector sides, the pay differences presented in Table 5 remain statistically significant at the one per cent level when occupation interacts with the public/private sector variable.2 In other words, despite relatively few workers on one side or another, it is still statistically robust to say that wage differences exist between the public and private sectors in these occupations compared to the reference category (in this case senior management occupations in the public sector).
There is a temptation to exclude those workers whose occupations are without much overlap. However, this decreases the explanatory power of the model by inadvertently forcing interactions between occupation and every other variable that is included. Interacting the public/private sector variable with occupation and then examining the standard error of the bootstrapped weights should highlight if wage differences are statistically significant, even if record counts are small, without affecting the rest of the model.
Like we did earlier, we’re holding all other factors from Table 1 equal, such as age, gender, industry, tenure and so on.
Occupations where the private sector pays more
The three occupations where public sector workers are paid significantly less than private sector ones are: senior management, health care professionals, and arts, culture and sports.
The occupation in the public sector that has the largest constraint in pay is legislative and senior management, where workers are paid 29 per cent less in the public sector.3 In raw terms, senior management has the highest hourly wages of any occupation, but the public sector manages to significantly constrain these rates. Extreme pay packages, like those you can receive as a CEO on Bay Street—$14.9 million, on average4—simply aren’t possible in public sector positions. Bonus pay lavished on private sector executives is largely (although not completely) non-existent in the public sector.
Health treating and consultation services represent the second largest pay-constrained occupation, which comprises physicians, veterinarians, dentists, optometrist, audiologist, pharmacists and dietitians.5 These professionals are paid, on average, 23 per cent less in the public sector. What we’re likely seeing here is the effect of cost-containment strategies in public health care, which is constraining the pay of these otherwise highly paid occupations.
The third largest pay constraint is in occupations in arts, culture and sport.6 This occupation category is made up of museum/art workers, photographers, creative and performing arts (such as dancers), along with athletes and coaches. These workers are paid 16 per cent less in the public sector, other things being equal. There may be compositional effects of this aggregate category, particularly given the reality that professional athletes will be primarily in the private sector and paid significantly more, whereas museum workers and artists are more likely to be in the public sector and are likely to be paid less.
Occupations where the public sector pays more
There are also occupations that are paid more in the public sector, holding other factors equal. The biggest difference is found in professional occupations in social and community services, where public sector workers are paid 20 per cent more than comparable private sector workers.7 This category includes police investigators and probation officers, social workers/counsellors, and education/career counsellors. Police investigators and probation officers don’t have private sector counterparts and are likely paid more than social workers and counsellors, possibly producing compositional effects. Social workers and counsellors can be in the public and private sector. The 20 per cent higher pay on the public side may indicate that those types of workers are paid more in the public sector, although the inclusion of the police component muddies the waters.
The second biggest difference is in professional occupations in education services occupations, where public sector workers are paid 14 per cent more.8 This includes educators at all levels—primary, secondary, university or college. While university education is almost entirely in the public sector, the other levels have private components, such as private secondary or private colleges and vocational schools. Educators in the public sector seem to be paid more, other things being equal. Many educators, like in primary schools, are overwhelmingly female. The effect of closing the gender pay gap in this occupation might be playing a specific role in showing a higher average pay in the public sector. Women might still be discriminated against as educators in the public sector, but it’s worse in the private sector.
The third biggest difference is in professional occupations in law, which are paid 12 per cent more in the public sector.9 This category is made up of both judges and lawyers. Judges are entirely in the public sector but lawyers are in both the public and private sector. There may be a compositional impact in that judges (public) are paid more than lawyers (public and private) and this is showing up as public sector workers are paid more than private sector workers in this category.
Closing the gender pay gap at different wage rates
The regression analysis above evaluated the average differences in pay based on various characteristics of the workers, but it did so, on average, across all income levels. To examine the effects on pay of public vs. private employment by income level, a newer regression technique is used. Specifically, an unconditional quantile regression with a re-centered influence function as the independent variable, as developed by Firpo et al. 2009, can allow us to answer such questions. See the Appendix A: methodology section for more details.
Using this different regression approach, we can see what effect switching to the public sector can have on wages at different points in the income spectrum. To simplify matters, we evaluate the impacts at five points on the wage spectrum, choosing the 10th, 25th, 50th, 75th and 90th percentile. The 50th percentile is also known as the median. For example, at the 10th percentile, 10 per cent of workers have a lower hourly wage and 90 per cent make more. At the 50th percentile (the median), half of workers make less and half make more. The 10th percentile is a relatively low hourly wage, the 50th percentile is the exact middle and the 90th percentile is at the high end of wages. This approach can better quantify an effect hinted at in the occupation analysis, that high-paid workers, like senior executives, have their pay constrained in the public sector while lower-paid workers, like social workers, are paid more.
Once again, we are adjusting for the 15 worker characteristics (age, occupation, industry, tenure, etc.) to compare similar workers to each other, although public/private sector and gender variables are the two that are presented in Figure 2. The full table of coefficients is available in Appendix table E.
The previous sections evaluated the difference in wages across all wage levels, but communicating differences even at five percentiles becomes difficult. In this section, we only take the gender pay gap in the public and private sectors, as shown in Figure 2.
In Figure 2, the reference group is women in the private sector, so all wage differences are evaluated based on how they compare to that group. If we start by looking at our lowest wage, the 10th percentile, the wage is $16 an hour, which is at or near the minimum wage for many provinces and was below the minimum wage in B.C., Ontario and Yukon in the later months of 2023.10 At this point, there is little difference in wages, whether public or private, male or female. Being right at or near minimum wage, women in the public sector get paid 1.8 per cent more than women in the private sector, whereas men in the public or private sector get paid 2.3 per cent and 2.7 per cent more, respectively, than women in the private sector. Organizations and companies may want to pay less but they can’t, due to the minimum wage. If a proportion of the population shifted from private to public, or male to female, at this point, there would be almost no impact on wages.
However, it is a very different story at the 25th percentile, where the wage is $20 an hour, with a quarter of workers making less and three quarters making more. This is perhaps the point where the public sector’s ability to close the pay gap is most evident. The gap between men and women in the public sector is under two percentage points and men and women in the public sector are paid just above men in the private sector, although all three of those groups are paid at least eight per cent more than women in the private sector, who face a heavy penalty for being female. This income level is where we see workers, no matter their gender, are similarly paid. In fact, there is a surprising phenomenon at this income level: an erasure of the gender wage gap. Women and men at that income level in the public sector are paid similarly to men at that income level in the private sector.
At the median or 50th percentile, the hourly wage is $29 an hour, with half of workers making less and half making more. At this income level, public sector workers are still being paid closer to private sector men, particularly public sector women, but the gap is growing compared to workers in the 25th percentile. If women in the public sector switched to the private sector, they would be paid seven per cent less. That said, at this income level, public sector women are paid less than men, no matter the sector. The gender pay gap in the public sector is larger at this income level, at five percentage points, even though that is much better than the private sector, where the gap between similar men and women is 12 percentage points. The pay equity from the 25th percentile rapidly erodes as we move to higher wage rates.
At the 75th percentile, the wage is $42 an hour and 75 per cent of workers make less than that. Someone working full-time at this hourly wage would make $76,000 a year. At this higher end of the income spectrum, private sector men are decisively paid more than comparable men working in the public sector and private sector men at this income level make much more than comparable women doing similar work in either sector. At this income level, public and private sector women are paid roughly the same. This illustrates the initial impact of the public sector’s constraint on higher-paid workers. For men, in particular, their pay rates are constrained in the public sector. Even at these higher wages, the gender pay gap in the public sector remains smaller, at 6.6 per cent compared to the 10.6 per cent gap in the private sector. However, this smaller public sector gap is far bigger than what we found at the 25th percentile.
The 90th percentile wage is $55 an hour, or $100,000 a year, if someone is working full-time. At this higher income level, both men and women are paid less in the public sector than in the private sector. At these higher wages, we’re seeing the continued impact of public sector pay constraints at the top, like in occupations of senior managers as noted above. Men in the public sector are paid five percentage points less than men in the private sector with women in the public sector being paid 2.2 per cent less than comparable women in the private sector. So, both men and women at this income level are paid less in the public sector, but the constraint is slightly larger for men. The gender pay gap at this income level is substantial in both sectors, sitting at 10 per cent and 13 per cent, for public and private sectors respectively, with women in these higher-wage categories facing a significant penalty for being female.
Broadly, the public sector lifts wages of workers in the middle- and middle-low wage range and has a particularly strong effect on women. Women in the public sector see rough wage equality with men at the 25th percentile. On the other hand, the public sector also pushes down wages at the top, particularly for those at the 90th percentile making $100,000 a year. The wage containment at the top is larger for men but is still there for women. At the top of the income spectrum, the gender pay gap is at its largest in both the public and private sectors.
Conclusion
The public sector is better at narrowing the gender pay gap than the private sector. The public sector does so by lifting lower-wage earners and constraining pay for high-wage earners. Although, without examining subgroups, there is actually little difference between adjusted average wages in the public and private sectors.
After adjusting for 15 worker characteristics (age, occupation, industry, tenure, etc.) in Table 1, women make less by virtue of being female. Compared to the private sector, public sector employment raises women’s wages and closes the gap with men, although it doesn’t eliminate the gender pay gap. On the other hand, men get paid slightly less in the public sector than in the private sector. The public sector also constrains the fatherhood premium while erasing the motherhood penalty that exists in the private sector.
We see a similar gap closing function for new Canadians. They still face significant wage penalties, when other observable factors are adjusted for, but that penalty is less in the public sector.
Workers in some occupations are paid more in the private sector and some less. Senior executives and medical professionals, such as physicians and dentists, are paid significantly less in the public sector. This is likely due to the aversion to extreme bonuses in the public sector and Medicare cost constraints on highly paid health professionals.
On the other hand, workers in occupations like social work/counselling and educators are paid more in the public sector. Also, educators and social workers have strong female representation and women face less wage discrimination in the public sector.
Examining the public sector’s impact across the wage spectrum, and including gender, we find that the public sector has the biggest impact on wages for women in the lower middle of hourly wages. At that income level, an unusual situation unfolds: roughly, public sector women experience pay equity with men. Unfortunately, women in the private sector at this pay rate experience a large wage penalty for being women. At the high end of the wage spectrum, public sector workers are paid less than private sector workers, other factors held equal. This is particularly true for men. The gender pay gap is largest at the top of the income spectrum, which is true in public and private sectors alike.
If we’re concerned about more equality and less discrimination in Canadian pay practices, the private sector should become like the public sector. It should better attempt to close discriminatory pay gaps because a worker is a woman, a mother or a new Canadian. Constraints in pay at the top end, in senior executive positions for instance, are how the public sector offsets those anti-discrimination pay improvements.
Appendix A
Methodology
Precise variance estimates, such as the Rao-Wu-Yue Bootstrap variance, must be produced from the Labour Force Survey (LFS) master file and requires detailed knowledge of the design of the survey sample. To protect the confidentiality of respondents, details of the sample design cannot be shared in the LFS Public Use Microdata Files (PUMFs). Instead, the PUMFs create a synthetic record set that should properly represent the microdata when the assigned weight is used. However, any individual record in the PUMF may or may not represent an observation of a surveyed worker. Reliable standard errors aren’t directly available in the PUMF, nor are the bootstrapped weights provided with the PUMF as they sometimes are in other Statistics Canada PUMFs.
However, a generalized replication method, recommended by Statistics Canada for LFS PUMFs, namely the Poisson bootstrap method, can be used to approximate the true variance.11 Briefly, the process to create the bootstrap weights is three step and is as follows as follows for each LFS record in the PUMF:
Where:
poisson factork = has a 50% probability of being 1 or -1
finalwtk = is the fweight variable for the record k in the LFS PUMF
Bootstrap weights must then be calibrated as follows:
Where:
Bootstrap weight is from each record from equation 2
Finalwt is the fweight from the LFS PUMF
Domains are groupings for each province, age and gender by month as recommended by Statistics Canada.
Using this approach 1,000 new calibrated bootstrap weights are created for each LFS record and standard errors are calculated based on variance of the coefficients of the 1,000 regressions based on each of those calibrated bootstrapped weights. For a detailed example, see “Bootstrap Variance Estimation: Labour Force Survey Public Use Microdata File.”12 All standard errors published above utilize this method with 1,000 replicates.
The first part of the paper examines various OLS regressions, examining different possible interaction between class of worker and other independent variables of interest. Here, instead of stratification (or sub-group analysis) by cutting the dataset into two different parts based on the variables of interest, the regressions use an interaction approach. Stratification may have an intuitive appeal in that it’s easier to understand, but it reduces the explanatory power of the model while also running a universal interaction between the stratification variable, the variable of interest, and all other variables.
On the other hand, interacting variables are slightly more complicated to implement, but with dummy variables, the interpretation remains relatively straightforward. Simple matrices are produced above to better communicate results. Also, instead of substantially reducing the explanatory power, as stratification does, variable interaction maintains or slightly increases it.
OLS regression is a standard choice for wage regressions of this type. However, it evaluates the impact of the various independent variables at the mean of the dependent variable, in this case the natural log of hourly wage. However, there may be different effects of those independent variables at different points in the distribution of the dependent variable. More recent innovations allow us to examine the impact of the independent variables at any quantile along the hourly wage distribution. Specifically, we can use unconditional quantile regression using a re-centered influence function, as presented in the Firpo et al. 2009. Similar approaches are used elsewhere in Canadian LFS literature; see, for instance, Mueller 2021.
This approach creates a new dependent variable at the quantile of interest that is then used in an OLS regression instead of using the original dependent variable; here, the natural log of hourly wage. Briefly, the creation of the new dependent variable is accomplished as follows:
Where:
Y = the dependent variable, in our case the natural log of hourly wage
τ= the quantile we’re interested in, in this paper we use the 10th, 25th, 50th 75th and 90th percentiles or 0.1, 0.25, 0.5, 0.75 and 0.9 respectively
qτ = the value of the Y at the quantile of interest. In our case the natural log of hourly wages at the various percentiles
𝟙{Y≤qτ} = a dummy that equals 1 if the dependent variable (natural log of hourly wages) is below the quantile value of interest, otherwise it equals 0.
fY(qτ) = is the density of Y at the quantile of interest. Here we are estimating the density using a kernel density function with an epanechnikov kernel and a kernel bandwidth of 1.
This results in two possible values for RIF(Y; qτ, FY), one when the dependent variable (ln hourly wage) is below the quantile value and one where it is above it.
In this paper, five versions of RIF(Y; qτ, FY) are created, one for each threshold of interest (10th, 25th, 50th 75th and 90th percentiles). Then five OLS regressions are performed, with the same covariates as the original OLS using these five new RIFs as the dependent variable.
Appendix B
Data source
This analysis uses the Canadian Labour Force Survey (LFS), although other Canadian data sources exist with some version of income and various available socio demographic factors that can be used as covariates. There are several key upsides to the LFS, the first being that the PUMFs are rapidly produced and it provides a decent collection of socio-demographic variables. It is also the only survey with a readily available variable for public and private sector workers, unlike the census. However, the census PUMF does provide data on indigenous and racial identity, something that is sorely missing in the LFS PUMF.
The LFS tracks roughly 45,000 households on a monthly basis. It is a compulsory survey although response rates are down substantially compared to pre-pandemic levels.13 The survey tracks individuals 15 years old or older in the civilian, non-institutionalized population. This paper includes all 12 months of 2023. It only includes workers in the public or private sector, not those who are self-employed or working for a family business. Public sector workers are identified as those employed by federal, provincial, territorial and indigenous governments, crown corporations and other government institutions like schools, universities, hospitals and libraries. The definition is based on who funds an organization rather than who owns it.14 Workers are otherwise private sector workers.
Appendix C
Public vs. private sector pay literature
In Canada, a number of research studies have looked at differences in compensation practices between the public sector and the private sector. It is well established that Canadian public sector workers earn higher average wages than private sector workers for similar jobs.15 Regression analysis has consistently been used to compare wages for public and private sector employees with similar backgrounds and qualifications. By controlling for worker characteristics, such as age, sex, marital status, education, economic family type, immigrant status, industry, occupation, and unionization status, regression analysis can identify explanatory factors for wage differentials between the public and private sector.
The main explanatory factor identified in the research on the public-private pay gap in Canada is the public sector’s commitment to pay equity.16 In general, white, heterosexual men who are born in Canada continue to earn a wage premium in nearly every sector of the labour market while women, racialized people, Indigenous Peoples, and immigrants continue to face a wage gap.17 This means that, despite being equal in terms of their background, qualifications, and occupation, women, racialized people, Indigenous Peoples, and immigrants are generally paid less than their white male counterparts.18 However, in the public sector, these wage gaps are significantly reduced and sometimes eliminated.19 In Ontario, low-wage workers benefit from higher wages in the public sector, whereas higher-wage workers see little difference between public and private employment.20 Since public sector hiring and compensation practices are governed by specific standards and legislation on pay equity; groups of workers who face discrimination in the private sector earn better wages when they work in the public sector.
In the private sector, senior executives can earn higher salaries than the highest-paid public sector workers.21 However, women, racialized people, Indigenous Peoples, and immigrants are more likely to earn lower wages in the private sector.22 As a result, when regression analysis is used to compare public and private sector workers with similar backgrounds, experience, and positions, public sector workers earn higher average wages than private sector workers.
While women in Canada continue to face a gender wage gap, that gap is smaller in the public sector. In general, women of working age in Canada earn less than their male counterparts, with larger gaps for immigrant women and Indigenous women compared to Canadian-born men.23 Comparing the gender wage gap between sectors, Mueller (2021) finds that there is a gap of almost a third in the private sector but a much smaller overall gap in the public sector. Promisingly, these findings suggest that public sector employment is narrowing the gender wage gap in Canada as women are also more likely to be public sector employees, making up over half of the public sector population.24
The gender wage gap in Canada is exacerbated by parenthood, meaning that women who have children face an even greater gap in wages compared to their male counterparts. Mothers with at least one child under the age of 18 earn around a fifth less than fathers.25 While women in Canada who have children face a decrease in potential earnings, men who have children earn a wage premium.26 Following motherhood, women are perceived as warmer but less competent while men are perceived at the same level of competence but gain perceived warmth with fatherhood.27 These deeply entrenched gender stereotypes and expectations mean that women with children, especially lone mothers and Indigenous women,28 face an unfair wage penalty while men with children experience an increase in potential earnings due to parenthood. Mothers in Canada are disproportionately employed in low-wage workplaces.29 Interestingly, Fuller (2018) finds that wage gaps between mothers and fathers that are due to women’s segregation in lower-paying establishments are only evident in the private sector. Women’s employment in the public sector helps to narrow the gender wage gap by reducing the motherhood penalty.
Research has also outlined how public sector wages are key to narrowing the immigrant wage gap. Many immigrants who are as qualified or more qualified than their Canadian-born counterparts earn significantly lower wages.30 Dostie et al. (2023) find that firm-specific pay and hiring patterns contribute to the earnings gap between immigrants and Canadian-born workers. As a group, immigrants are less likely to be hired at high-paying firms—especially immigrants from non-Western countries who lack a university-level education.31 However, there is higher wage equity between immigrants and their Canadian-born counterparts in the public sector.32 In the private sector, wages are higher for Canadian-born workers than immigrants whereas, in the public sector, there is almost no gap.33 However, the relative increase in professional groups of new Canadians has been raising relative wages.34 As women and immigrants in Canada continue to be under-compensated in comparison to their equally qualified counterparts in similar jobs, public sector wages serve as an important driver in advancing Canada’s progress towards pay equity.
This research has been replicated internationally, leading to similar findings. In other Global North countries, such as England, Australia, Germany, France, and Italy, regression analysis shows that there is a public-private wage gap that is largely explained by the greater employment and earnings of women in the public sector.35 Furthermore, in Global North countries outside of Canada, public sector employment plays an important role in narrowing the immigrant wage gap.36 Similar to Canada, the public-private wage gap in other advanced economies is best understood as a result of pay equity in the public sector.
Appendix D
Full model data tables
References
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