Income Research Paper Series
Annual wages, salaries and commissions of T1 tax filers, 2017

by Eric Fecteau and Dominique Pinard, Income Statistics Division

Release date: January 29, 2019

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Introduction

In 2017, the largest income source for the majority of tax filers in Canada is “wages, salaries and commissions”,Note  which are gained from being an employee (see Data sources, methods and definitions). This income source accounted for approximately two out of three dollars of annual income of tax filers. Understanding the characteristics of wage-earnersNote  and the differences in annual earnings by province, sex, age and industry can help to describe how the Canadian population interacts with the labour market.

Annual wage-earnings is one of many key variables for exploring differences in the economic situation of men and women and different generations within the Canadian workforce. For example, a higher proportion of men are wage-earners, regardless of age group (70.0% of tax filing men, compared with 61.9% of tax filing women), and women had a lower annual median income from wage-earnings than men ($31,340 and $43,690, respectively). Comparing annual wage-earnings across industry sectors, as well as between the provinces or territories, also allows for the description of different situations.

This paper uses the version of the T1 Family File (T1FF) for 2017 that is based on the preliminary databases from the T1 Income Tax and Benefit Return and T4 Statement of Remuneration Paid files that Statistics Canada receives from the Canada Revenue AgencyNote . It provides an overview of annual income from wage-earnings according to selected characteristics. The target population for the analysis is tax filers with wages, salaries and commissions, corresponding to approximately 17.6 million individuals. This target excludes tax filers below the age of 15 years (as of December 31 of the tax year), tax fillers that are only self-employed, tax filers who died during the tax year and tax filers who provided a mailing address outside Canada. To allow for comparison, the preliminary T1FF data for 2015 and 2016 will also be used.Note  The intent is to publish data tables on wages, salaries and commission on an annual basis in future years using preliminary T1FF data. Because of the nature of tax information, the analysis focusses on all wage-earnings gained from one or many employers in a calendar year and does not take into account employment characteristics that are often used in other studies. For example, it is not possible to draw conclusions according to hourly wage rates, full-time or part-time status of employees, or full-year or part-year employment.

Year-over-year differences for 2015, 2016 and 2017 were small

The median annual wage-earnings was $36,980 in 2017, up less than one percent from 2016. Only slight fluctuations in the median annual wage-earnings of individuals were observed over the last three years: $36,740 for 2015, $36,630 for 2016 and $36,980 for 2017.

The median annual wage-earnings of women represented 71.7% of wage-earnings of men, the gap being the largest among the age groups from 35 to 54 years

The 2017 median wage-earnings was highest among wage-earners aged 35 to 44 years ($50,470) and 45 to 54 years ($52,820). As shown in Chart 1, it was lowest among the youngest and two oldest age groups ($12,000 for wage-earners aged 15 to 24 years, $11,500 for those aged 65 to 74 years and $460 for those aged 75 years and older).

In general, women had lower median wage-earnings than men ($31,340 and $43,690, respectively). This gap was largest among the groups aged 35 to 44 years ($19,030) and 45 to 54 years ($19,070). It was smallest among the youngest and two oldest age groups ($2,450 for wage-earners aged 15 to 24 years, $1,720 for those aged 65 to 74 years and $80 for those aged 75 years and older). According to Patterson (2018) and Moyser (2017), women were more likely to work part time, largely as a result of caring for children, especially among women aged 30 to 39 years. Moyser also identified that women were more likely to have more frequent career interruptions and for a longer total length and be underrepresented in leadership positions in the private sector. From 2015 to 2017, in constant dollars, men had nearly no gains in median wage-earnings (from $43,680 to $43,690), while women had a slight gain (from $30,850 to $31,340).

Men were more likely to have wage-earnings than women (70.0% of tax filing men, compared with 61.9% of tax filing women).Note  This gap was largest among the group aged 65 to 74 years (34.9% of tax filing men, compared with 23.1% of tax filing women) and smallest among the groups aged 15 to 24 years (86.2% of tax filing men, compared with 85.9% of tax filing women) and 45 to 54 years (80.7% of tax filing men, compared with 77.4% of tax filing women).

Chart 1 Median wage-earnings by sex and age group, 2017

Data table for Chart 1 
Data table for Chart 1
Table summary
This table displays the results of Data table for Chart 1. The information is grouped by Age (appearing as row headers), Both Sexes, Men and Women, calculated using dollars units of measure (appearing as column headers).
Age Both Sexes Men Women
dollars
All ages 36,980 43,690 31,340
15 to 24 years 12,000 13,380 10,930
25 to 34 years 38,130 44,560 32,330
35 to 44 years 50,470 60,760 41,730
45 to 54 years 52,820 63,370 44,300
55 to 64 years 42,080 50,380 35,580
65 to 74 years 11,500 12,270 10,550
75 years and older 460 510 430

The territories generally had greater wage distribution than the provinces

Among provinces and territories, the Northwest Territories ($51,680), Yukon ($46,220) and Alberta ($44,470) had the highest median wage-earnings in 2017 (see Chart 2). The Maritime provinces ($28,870 for Prince Edward Island, $31,430 for New Brunswick and $32,110 for Nova Scotia) and Nunavut ($30,690) had the lowest. The Northwest Territories, Yukon and Alberta also had the highest medians in 2015 and 2016. Alberta had a small rebound from 2016 to 2017 ($330), after a large drop from 2015 to 2016 (-$2,030).

The interquartile range, the difference between the 25th and 75th percentiles of wage-earnings, helps describe the heterogeneity of wage-earnings within regions or industries. While Nunavut was among the provinces and territories with the lowest median wage-earnings in Canada, it had one of the largest interquartile range of wage-earnings, along with the Northwest Territories (the difference being $79,180 and $80,190, respectively). Nova Scotia, Prince Edward Island and New Brunswick, which had among the lowest medians, also had the smallest interquartile ranges of wage-earnings (the ranges of differences were between $39,290 and $44,320).

Alberta's wage-earners ($155,500) had the highest value for the 95th percentile of earnings, followed by Northwest Territories ($150,100) and Nunavut ($143,640). Five other provinces and territories (Newfoundland and Labrador, Ontario, Saskatchewan, British Columbia and Yukon) had wage-earning values at the 95th percentile greater than $120,000.

The territories had the largest proportion of tax filers with wage-earnings during the year (78.0% for Yukon, 80.8% for the Northwest Territories and 81.4% for Nunavut). Note  Nova Scotia (63.2%), Newfoundland and Labrador (63.5%), and New Brunswick (64.3%) had the lowest proportion of tax filers with wage-earnings.

Chart 2 Interquartile range of wage-earnings (including 95th percentile) by province/territory, 2017

Data table for Chart 2 
Data table for Chart 2
Table summary
This table displays the results of Data table for Chart 2. The information is grouped by Province/territory (appearing as row headers), 25th percentile, Difference between 25th percentile and 50th percentile, Difference between 50th percentile and 75th percentile and Difference between 75th percentile and 95th percentile, calculated using dollars units of measure (appearing as column headers).
Province/territory 25th percentile Difference between 25th percentile and 50th percentile Difference between 50th percentile and 75th percentile Difference between 75th percentile and 95th percentile
dollars
Canada 14,630 22,350 28,600 59,140
Northwest Territories 16,410 35,270 44,920 53,500
Yukon 19,570 26,650 31,270 46,970
Alberta 18,490 25,980 34,690 76,340
Saskatchewan 16,210 23,370 29,600 55,930
Ontario 14,300 23,660 30,060 60,440
Manitoba 15,730 20,460 24,970 49,010
British Columbia 12,810 22,490 28,800 59,030
Quebec 14,710 20,270 24,150 49,330
Nunavut 11,940 20,350 32,060 63,490
Newfoundland and Labrador 12,970 19,140 25,180 47,890
Nova Scotia 14,110 17,320 23,710 46,860
New Brunswick 8,130 22,560 56,620 56,330
Prince Edward Island 12,610 16,260 23,030 42,900

The “mining, quarrying, and oil and gas extraction” and “utilities” industries had the highest wage-earnings

This section focusses on all wage-earnings of T1 tax filers, whether they had one or several employers, according to the industry of their main employer.Note Although tax filers may accumulate wage-earnings from multiple employers associated with different industries, all their wage-earnings were assigned to the industry of their main employer.

In 2017, the industry sectors with the highest median wage-earnings were “utilities” ($97,130) and “mining, quarrying, and oil and gas extraction” ($94,050). The earnings for the 25th percentile in these two industries ($65,060 and $54,320, respectively) were higher than the median wage-earnings for nearly all other industries. The median wage-earnings for these two industries were also higher than the top quartile (P75) of all other industries. According to the Labour Force Survey (LFS), “utilities” and “forestry, fishing, mining, quarrying, oil and gas” had the highest average hourly wages and were also among the highest for average actual hours worked.Note  Among the subsectors for the “mining, quarrying, and oil and gas extraction” industry, “oil and gas extraction” had the highest median by far, at $153,860. The vast majority (83.7%) of wage-earners whose main industry subsector was in the “oil and gas extraction” resided in Alberta. In 2017, the industries with the lowest median earnings were “accommodation and food services” ($15,000); “arts, entertainment and recreation” ($16,350); and “retail trade” ($21,610). According to 2017 LFS data, “utilities” and “forestry, fishing, mining, quarrying, oil and gas” had the lowest rate of part-time workers, while “accommodation and food services” had the highest rate.Note  For unionization, “utilities” had among the highest rate, while “accommodation and food services” had among the lowest.Note 

From 2015 to 2017, “health care and social assistance” had the highest growth in the number of wage-earners (from 1,473,200 tax filers to 1,539,100 tax filers) and a small decrease in median (from $39,670 to $39,410). “Administrative and support, waste management and remediation services” had the highest decrease in the number of wage-earners (from 895,940 tax filers to 834,800 tax filers) and a small increase in median (from $25,230 to $25,450). “Public administration” had the largest increase in median wage-earnings (from $57,100 in 2015 to $59,090 in 2016 and $60,150 in 2017). The territories had by far the largest proportion of wage-earners in the “Public administration” industry (40.2% for Yukon, 40.4% for the Northwest Territories and 47.3% for Nunavut). “Management of companies and enterprises”, which is among the industries with the fewest wage-earners, had the highest decrease in median from 2015 to 2017, even though it increased in 2016 (from $58,600 in 2015 to $59,610 in 2016 and $45,170 in 2017). This industry also had the highest fluctuation in number of wage-earners (from 146,650 in 2015 to 125,330 in 2016 and 204,720 in 2017). Caution should be taken when analyzing this data as this large fluctuation may be due to changes in reporting or coding methods.

Chart 3 Interquartile range of wage-earnings (including 95th percentile) by industry, 2017

Data table for Chart 3 
Data table for Chart 3
Table summary
This table displays the results of Data table for Chart 3. The information is grouped by Industrie (appearing as row headers), 25th percentile, Difference between 25th percentile and 50th percentile, Difference between 50th percentile and 75th percentile and Difference between 75th percentile and 95th percentile, calculated using dollars units of measure (appearing as column headers).
Industrie 25th percentile Difference between 25th percentile and 50th percentile Difference between 50th percentile and 75th percentile Difference between 75th percentile and 95th percentile
dollars
Total, All industries 14,630 22,350 28,600 59,140
11. Agriculture, forestry, fishing and hunting 10,920 13,440 20,490 42,840
21. Mining, quarrying, and oil and gas extraction 54,320 39,730 40,770 100,860
22. Utilities 65,060 32,070 28,200 54,370
23. Construction 25,360 21,530 26,380 53,530
31-33. Manufacturing 29,110 18,110 25,110 57,110
41. Wholesale trade 27,560 20,140 28,450 84,610
44-45. Retail trade 9,630 11,980 17,460 45,410
48-49. Transportation and warehousing 23,090 21,910 23,440 54,960
51. Information and cultural industries 31,190 25,240 28,960 69,090
52. Finance and insurance 32,960 21,350 34,400 120,030
53. Real estate and rental and leasing 17,390 19,050 24,390 72,010
54. Professional, scientific and technical services 27,230 25,690 32,810 78,720
55. Management of companies and enterprises 17,980 27,190 39,560 124,060
56. Administrative and support, waste management and remediation services 10,840 14,610 19,540 55,010
61. Educational services 18,810 27,310 32,640 32,830
62. Health care and social assistance 22,430 16,980 18,950 42,600
71. Arts, entertainment and recreation 6,410 9,940 21,180 42,920
72. Accommodation and food services 7,190 7,810 11,210 25,870
81. Other services (except public administration) 13,490 17,200 21,420 51,100
91. Public administration 32,390 27,760 25,350 39,220

Conclusion

This article describes data on annual wage-earnings from the preliminary T1 Family File. Annual median income from wages, salaries and commissions varied considerably by sex, age, province or territory, and industry, but it remained fairly stable from 2015 to 2017. Women had lower median annual wage-earnings than men, and wage-earners in the age groups from 25 to 54 years had higher median wage-earnings than the youngest group of wage-earners. The Northwest Territories, Yukon and Alberta generally had the highest wage-earnings, while the Maritime provinces and Nunavut had the lowest. “Mining, quarrying, and oil and gas extraction”, and “utilities” had, by far, not only the highest median wage-earnings, but also the highest 25th and 75th percentile. “Accommodation and food services”, “arts, entertainment and recreation”, and “retail trade” had the lowest median wage-earnings.

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Data sources, methods and definitions

Data source:

This paper uses the version of the T1 Family File (T1FF) for 2017 that is based on the preliminary databases from the T1 Income Tax and Benefit Return and T4 Statement of Remuneration Paid files. The population in the preliminary version of the T1FF varies slightly from the final T1FF data: it does not capture a certain amount of late tax filers or reassessment. The preliminary T1FF contains approximately 97% of the records used to create the final T1FF. This version of the T1FF also does not include non-filing dependants and non-tax filing spouses of tax filers who may have had earnings during the year.

Because of the nature of tax information, the analysis focusses on all wage-earnings gained in a calendar year and does not take into account employment characteristics that are often used in other studies. For example, it is not possible to draw conclusions according to hourly wage rates, full-time or part-time status of employees, or full-year or part-year employment.

The distribution statistics for wage-earnings change little between the preliminary and final T1FF data. Therefore, preliminary data can help researchers analyze the evolution of market trends in a timelier fashion and can lead to a quicker turnaround in evaluating the labour market effects of policy change. Using the preliminary files does not strongly affect the findings described in this analysis, since the results would vary only slightly if reproduced with the final T1FF data. Many other important variables from the T1FF, such as total and after-tax income of individuals and families, are only available on the final T1FF.

Target population:

The target population is tax filers with wages, salaries and commissions. This target excludes tax filers below the age of 15 years (as of December 31 of the tax year), tax filers that are only self-employed, tax filers who died during the tax year and tax filers who provided a mailing address outside of Canada. The section of this paper that analyzes industries is limited to tax filers with wages, salaries and commissions with an assigned industry (NAICS) based on the employer information on their T4 slip.

Terminology:

Wages, salaries and commissions: This article refers to wages, salaries and commissions as “wage-earnings” and to individuals with wage-earnings greater than $0 as “wage-earners”. Wages, salaries and commissions includes employment pay and commissions as stated on T4 information slips, training allowances, tips, gratuities, and royalties. It also includes tax-exempt employment income earned by registered Indians. All forms of self-employment earnings are excluded. Individuals that have both wage-earnings and self-employment income are included in the analysis, but only their wages-earnings are considered. The components of employment earnings are wages and salaries (line 101 of the T1 form), other employment income (line 104 of the T1 form), and Indian exempt income (derived from the information provided on the Determination of Exemption of an Indian’s Employment Income form). Wage, salaries and commissions combines income received from multiple employers.

Median: The median is the value in the centre of a group of values (i.e., 50% of people make above this value and 50% of people make below this value).

Interquartile range: The distance between the 25th and 75th percentile is called the interquartile range. The 25th percentile is the value 25 percentage points below the median, and the 75th percentile is the value 25 percentage points above the median.

P95: The 95th percentile (P95) corresponds to the value below which 95% of the population fall.

Industry: The industries are defined using the North American Industry Classification System (NAICS) for Canada (for more information, see Statistics Canada’s industry classification). The term “industry” in this article refers to the two-digit NAICS sector (e.g., sector code 23 refers to construction) and the term “industry subsector” refers to the three-digit NAICS subsector (e.g., subsector code 236 refers to construction of buildings). This article identifies the main industry of wage-earners as the industry on the T4 slip with the highest wages and salaries (Box 14). The industry can be derived using the employer information on the T4 slip for most wage-earners. The section on industry includes only wage-earners whose T4 slip information was available and sufficient to identify an industry.Note 

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Bibliography

Moyser, Melissa. 2017. “Women in Canada: A gender-based statistical report.” Women and Paid Work. Statistics Canada Catalogue no. 89-503-X. Ottawa.

Patterson, Martha. 2018. “Who works part time and why?” Labour Statistics at a Glance. Statistics Canada Catalogue no. 71-222-X. Ottawa.

Statistics Canada. Table 14-10-0037 Actual hours worked by industry, annual.

Statistics Canada. Table 14-10-0023 Labour force characteristics by industry, annual (x 1,000).

Statistics Canada. Table 14-10-0132 Union status by industry.

Appendix A


Table 1
Median wage-earnings by age group and sex, 2015 to 2017
Table summary
This table displays the results of Median wage-earnings by age group and sex. The information is grouped by Age groups (appearing as row headers), Sex, 2015, 2016 and 2017 (appearing as column headers).
Age groups Sex 2015 2016 2017
All ages Both sexes 36,740 36,630 36,980
Men 43,680 43,210 43,690
Women 30,850 31,060 31,340
15 to 24 years Both sexes 11,910 11,790 12,000
Men 13,340 13,070 13,380
Women 10,770 10,760 10,930
25 to 34 years Both sexes 37,920 37,630 38,130
Men 44,690 43,990 44,560
Women 31,750 31,850 32,330
35 to 44 years Both sexes 50,110 49,970 50,470
Men 60,730 60,150 60,760
Women 41,200 41,390 41,730
45 to 54 years Both sexes 51,970 52,060 52,820
Men 62,650 62,360 63,370
Women 43,450 43,820 44,300
55 to 64 years Both sexes 41,590 41,830 42,080
Men 49,790 49,770 50,380
Women 35,140 35,540 35,580
65 to 74 years Both sexes 10,300 11,310 11,500
Men 11,350 12,010 12,270
Women 9,190 10,580 10,550
75 years and older Both sexes 450 470 460
Men 510 510 510
Women 450 460 430

Table 2
Quartiles of wage-earnings by province/territory, 2015 to 2017
Table summary
This table displays the results of Quartiles of wage-earnings by province/territory 2015, 2016 and 2017 (appearing as column headers).
Province/territory 2015 2016 2017
P25 Median P75 P25 Median P75 P25 Median P75
Canada 14,300 36,740 65,280 14,420 36,630 64,900 14,630 36,980 65,580
Newfoundland and Labrador 12,360 33,160 66,920 12,340 32,840 64,910 11,940 32,290 64,350
Prince Edward Island 12,280 28,410 50,880 12,330 28,510 50,680 12,610 28,870 51,900
Nova Scotia 12,860 31,960 57,330 13,060 32,000 56,900 12,970 32,110 57,290
New Brunswick 13,450 30,900 54,770 13,650 31,380 54,790 14,110 31,430 55,140
Quebec 14,090 34,130 57,780 14,450 34,580 58,480 14,710 34,980 59,130
Ontario 13,850 37,420 67,410 14,190 37,680 67,320 14,300 37,960 68,020
Manitoba 15,550 36,050 60,510 15,270 35,750 60,260 15,730 36,190 61,160
Saskatchewan 16,430 40,240 70,060 15,620 39,030 68,380 16,210 39,580 69,180
Alberta 19,400 46,170 81,800 18,280 44,140 78,260 18,490 44,470 79,160
British Columbia 12,360 34,460 63,480 12,510 34,530 63,100 12,810 35,300 64,100
Yukon 18,290 45,000 76,430 18,780 44,920 76,460 19,570 46,220 77,490
Northwest Territories 16,080 52,080 99,470 16,620 51,980 97,070 16,410 51,680 96,600
Nunavut 7,350 29,550 88,850 7,490 30,440 87,610 8,130 30,690 87,310

Table 3
Quartiles of wage-earnings by industry, 2015 to 2017
Table summary
This table displays the results of Quartiles of wage-earnings by industry 2015, 2016 and 2017 (appearing as column headers).
Industry 2015 2016 2017
P25 Median P75 P25 Median P75 P25 Median P75
11. Agriculture, forestry, fishing and hunting 10,370 23,190 43,470 10,620 23,660 43,890 10,920 24,360 44,850
21. Mining, quarrying, and oil and gas extraction 53,640 94,950 137,790 51,460 90,790 131,200 54,320 94,050 134,820
22. Utilities 64,110 95,490 123,990 64,440 96,540 125,150 65,060 97,130 125,330
23. Construction 24,720 46,280 73,770 24,580 45,890 72,540 25,360 46,890 73,270
31-33. Manufacturing 28,580 47,260 72,350 28,740 47,170 72,270 29,110 47,220 72,330
41. Wholesale trade 26,620 46,780 75,140 26,820 47,130 75,750 27,560 47,700 76,150
44-45. Retail trade 9,680 21,480 39,080 9,700 21,540 39,070 9,630 21,610 39,070
48-49. Transportation and warehousing 23,190 45,790 68,920 22,900 44,890 67,890 23,090 45,000 68,440
51. Information and cultural industries 31,440 57,060 86,750 31,600 56,910 86,320 31,190 56,430 85,390
52. Finance and insurance 31,940 53,030 87,220 31,660 52,910 86,490 32,960 54,310 88,710
53. Real estate and rental and leasing 15,590 34,730 58,970 15,990 35,250 59,380 17,390 36,440 60,830
54. Professional, scientific and technical services 25,760 51,530 84,630 26,130 51,580 84,150 27,230 52,920 85,730
55. Management of companies and enterprises 27,640 58,600 106,250 28,780 59,610 107,440 17,980 45,170 84,730
56. Administrative and support, waste management and remediation services 10,680 25,230 45,450 10,750 25,240 44,980 10,840 25,450 44,990
61. Educational services 18,860 46,130 78,000 18,590 46,120 78,980 18,810 46,120 78,760
62. Health care and social assistance 22,390 39,670 58,910 22,360 39,590 58,580 22,430 39,410 58,360
71. Arts, entertainment and recreation 6,460 16,410 37,970 6,420 16,410 37,770 6,410 16,350 37,530
72. Accommodation and food services 7,030 14,640 25,670 7,070 14,680 25,660 7,190 15,000 26,210
81. Other services (except public administration) 13,100 29,820 51,110 13,120 30,010 51,070 13,490 30,690 52,110
91. Public administration 27,470 57,100 83,280 33,040 59,090 83,900 32,390 60,150 85,500

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