Payroll employment, earnings and hours, January 2014
Average weekly earnings of non-farm payroll employees were $925 in January, virtually unchanged from the previous month. On a year-over-year basis, weekly earnings increased 3.0%.
The 3.0% increase in weekly earnings during the 12 months to January reflected a number of factors, including wage growth, changes in the composition of employment by industry, occupation and level of job experience, as well as average hours worked per week. Non-farm payroll employees worked an average of 32.9 hours per week in January, down from 33.0 hours in December. On a year-over-year basis, the average hours worked was unchanged.
Average weekly earnings by sector
Year-over-year growth in average weekly earnings was above the national average in 5 of the 10 largest industrial sectors, led by wholesale trade and construction.
Compared with 12 months earlier, average weekly earnings grew by 6.9% in wholesale trade to $1,130. Growth over this period was driven by merchant wholesalers of personal and household goods as well as merchant wholesalers of machinery, equipment and supplies.
Average weekly earnings in construction rose by 6.7% to $1,222, with gains spread across most industries in this sector. Despite this year-over-year growth, earnings in construction have hovered around this level since October 2013.
Weekly earnings in retail trade rose 6.1% to $542. Most industries in this sector posted earnings increases over the 12-month period, led by growth in general merchandise stores as well as clothing and clothing accessories stores.
In the 12 months to January, weekly earnings in administrative and support services increased 5.7% to $765. The largest gains were recorded in office administrative services; business support services; and employment services.
Average weekly earnings increased by 3.5% to $1,294 in professional, scientific and technical services. Growth was most notable in other professional, scientific and technical services; legal services; and in architectural, engineering and related services.
Compared with 12 months earlier, weekly earnings were relatively unchanged in public administration as well as accommodation and food services.
Average weekly earnings by province
Year-over-year earnings of non-farm payroll employees increased in every province, with the highest growth in Alberta and Prince Edward Island.
In the 12 months to January, average weekly earnings in Alberta grew by 5.1% to $1,134, with growth spread across most sectors.
Average weekly earnings in Prince Edward Island rose 4.9% to $778 in the 12 months to January, with the highest growth in professional, scientific and technical services; wholesale trade; health care and social assistance; and accommodation and food services.
Compared with 12 months earlier, average weekly earnings increased by 4.4% to $818 in Nova Scotia, driven by gains in public administration, retail trade as well as accommodation and food services.
Non-farm payroll employment by sector
After edging up (+2,400) in December, total non-farm payroll employment declined slightly (-7,000) in January. The largest declines were recorded in transportation and warehousing; mining, quarrying, and oil and gas extraction; and information and culture. At the same time, there were gains in health care and social assistance; public administration and construction.
In the 12 months to January, the number of non-farm payroll employees increased by 160,100 or 1.0%.
Among all sectors, real estate and rental and leasing posted the highest 12-month growth rate in payroll employment at 4.9%. Since April 2013, this sector has had the highest year-over-year growth among all sectors. Employment growth from January 2013 to January 2014 was also notable in professional scientific and technical services (+2.6%), accommodation and food services (+2.5%) and construction (+2.1%).
Compared with January 2013, employment declined in utilities (-2.2%), information and culture (-2.0%) and in manufacturing (-1.1%).
Note to readers
The Survey of Employment, Payrolls and Hours (SEPH) is produced by a combination of a census of payroll deductions, provided by the Canada Revenue Agency, and the Business Payrolls Survey, which collects data from a sample of 15,000 establishments. Its key objective is to provide a monthly portrait of the level of earnings, the number of jobs and hours worked by detailed industry at the national, provincial and territorial level.
Estimates of average earnings and hours worked are worked based on a sample and are therefore subject to sampling variability. This analysis focuses on differences between estimates that are statistically significant at the 68% confidence level. Payroll employment estimates are based on a census of administrative data and are not subject to sampling variability.
Statistics Canada also produces employment estimates from its monthly Labour Force Survey (LFS). The LFS is a monthly household survey, the main objective of which is to divide the working-age population into three mutually exclusive groups: the employed (including the self-employed), unemployed and not in the labour force. This survey is the official source for the unemployment rate and collects data on the socio-demographic characteristics of all those in the labour market.
As a result of conceptual and methodological differences, estimates of changes from SEPH and LFS do differ from time to time. However, the trends in the data are quite similar.
Unless otherwise stated, this release presents seasonally adjusted data, which facilitates comparisons by removing the effects of seasonal variations. For more information on seasonal adjustment, see "Seasonal adjustment and identifying economic trends."
Non-farm payroll employment data are for all hourly and salaried employees, as well as the "other employees" category, which includes piece-rate and commission-only employees.
Average weekly hours data are for hourly and salaried employees only and exclude businesses that could not be classified to a North American Industry Classification System (NAICS) code.
All earnings data include overtime pay and exclude businesses that could not be classified to a NAICS code. Earnings data are based on gross taxable payroll before source deductions. Average weekly earnings are derived by dividing total weekly earnings by the number of employees.
With each release, data for the current reference month are subject to revision. Data have been revised for the previous month. Users are encouraged to request and use the most up-to-date data for each month.
With this release, SEPH has incorporated an additional method in assigning 2012 NAICS codes to businesses. The impact of this change is a reduction in the payroll employment level in the unclassified businesses category and slight increases in employment in most of the classified industries. Earnings data for some industries are also affected. This method has been applied back to 2008, and will be in place going forward. The unclassified category now accounts for 1% to 2% of payroll employment compared with 2% to 3% before the change.
At the same time, seasonally adjusted data have been revised based on the latest seasonal factors. Historical revisions have also been made to a small number of industries by province or territory. These data were revised back to 2001.
In addition, quality indicators have been added to CANSIM table 281-0039.
A data table is available from the Browse by key resource module of our website under Summary tables.
Data on payroll employment, earnings and hours for February will be released on April 29.
More information about the concepts and use of the Survey of Employment, Payrolls and Hours is available online in The Guide to the Survey of Employment, Payrolls and Hours (Catalogue number72-203-G), from the Browse by key resource module of our website under Publications.
For more information, contact us (toll-free 1-800-263-1136; 514-283-8300; email@example.com).
To enquire about the concepts, methods or data quality of this release, contact Jason Gilmore (613-951-7118; firstname.lastname@example.org), Labour Statistics Division.
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