The linked pages contain data and related to job creation, labour force changes, and related issues. Data are updated monthly, upon release by Statistics Canada of the latest Labour Force Survey report.
All values are estimates, based on household surveys carried out by Statistics Canada. The surveys generate error rates -these are not shown here but can be viewed in the Statistics Canada Tables. Disclaimer.
There may be a brief lag before the plot loads. By moving your cursor along the plot, you can see changes from the same month of the previous year. On a mobile device, you might want to rotate to horizontal.
Data Table: Employed, Workforce, Population
Trends over time for employment in New Brunswick and regions of New Brunswick
Labour Force Data for New Brunswick
Time series showing employment and impact of inflation on earnings in various job categories (e.g. forestry, retail)
Wages and Inflation
Data on labour force composition (age, gender).
Labour Force Composition – Gender and Age
The third plot compares labour force trends across provinces, using data adjusted or unadjusted for seasons.
Provincial Comparisons – Job Creation
Acknowledgements:
Statistics Canada. Table 14-10-0287-01 Labour force characteristics, monthly, seasonally adjusted and trend-cycle DOI: https://doi.org/10.25318/1410028701-eng
Statistics Canada. Table 14-10-0462-01 Labour force characteristics by economic region, three-month moving average, unadjusted for seasonality
DOI: https://doi.org/10.25318/1410046201-eng
Statistics Canada. Table 14-10-0332-01 Historical (real-time) releases of employment and average weekly earnings (including overtime) for all employees by province and territory, monthly, seasonally adjusted
DOI: https://doi.org/10.25318/1410033201-eng
Chang W, Cheng J, Allaire J, Sievert C, Schloerke B, Aden-Buie G, Xie Y, Allen J, McPherson J, Dipert A, Borges B (2026). shiny: Web Application Framework for R. R package version 1.13.0.9000, https://shiny.posit.co/.
R Core Team. 2023. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.