AI Analysis: Labour force characteristics by census metropolitan area, three-month moving average, unadjusted for seasonality

Executive Summary

Statistics Canada Table 14100458 provides over 15 years of monthly labour force data across 43 Canadian census metropolitan areas, revealing generally improving employment conditions from 2011 onward, with unemployment rates declining from 8.1% to 7.2% and employment growing by 86.4 thousand persons on average across CMAs. The dataset spans 10 labour force characteristics and exposes significant regional disparities in unemployment and population size, from Canada's largest metros like Toronto to smaller areas like Belleville and Abbotsford-Mission. Sharp outlier spikes — most notably around 2020 — underscore the dataset's value in capturing structural labour market shocks such as the COVID-19 pandemic.

Key Findings

• The dataset contains approximately 221,761–250,000 records covering 43 Canadian census metropolitan areas from March 2011 to February 2026, cross-tabulated across 10 labour force characteristics, 3 gender categories, and 9 age groups.
• Average employment grew by 86.4 thousand persons and the unemployment rate fell from 8.1% to 7.2% (a 1.0 percentage point improvement) between March 2011 and December 2012, indicating early-period labour market recovery.
• The overall value distribution is heavily right-skewed, with a mean of 68.7 versus a median of 26.6 (in thousands of persons), driven by large CMAs such as Toronto pushing upper-end values as high as 4,849.3.
• Population, Labour Force, and Employment categories show the widest spreads and most outliers, while rate-based metrics like Unemployment Rate and Employment Rate are tightly distributed in the approximate range of 1.5% to 98.2%.
• Correlation analysis confirms classic labour market relationships: Employment and Labour Force size are strongly positively correlated, while Unemployment Rate and Employment Rate exhibit a clear negative correlation across CMAs and time periods.
• Regional unemployment disparities are pronounced, with the top 5 highest-unemployment CMAs sitting well above the national average over the full 2011–2026 period, while the bottom 5 lowest-unemployment cities maintain consistently narrow and stable unemployment ranges.
• Statistical outlier detection (z-score > 2.5) identified sharp unemployment spikes — most likely corresponding to the COVID-19 period around 2020 — as extreme deviations from each CMA's own historical norm, visible across multiple regions simultaneously.