AI Analysis: Labour force characteristics, selected census subdivisions, three-month moving averages, monthly, unadjusted for seasonality

Executive Summary

Statistics Canada's Table 14100445 tracks monthly labour force characteristics across 38 Canadian census subdivisions from January 2022 to April 2026, revealing steady employment growth of 26,200 persons alongside a rising unemployment rate from 6.0% to 7.1%, suggesting labour supply is outpacing job creation. Count-based metrics such as Employment, Labour Force, and Population are almost perfectly correlated (r ≥ 0.99), meaning regional size is the dominant driver of variation across subdivisions. While most labour market indicators trended modestly upward, participation and employment rates remained essentially flat, and 75 statistical outliers in unemployment rates point to pockets of meaningful labour market volatility in specific regions and time periods.

Key Findings

• Employment grew by 26,200 persons (+10.4%) from 252,600 to 278,800 between January 2022 and April 2026, while the labour force expanded even faster by 32,100 persons, pushing the unemployment rate up from 6.0% to 7.1%.
• Despite overall population growth of 51,000 persons, the participation rate held nearly flat (65.5% → 65.3%) and the employment rate slightly declined (61.6% → 60.7%), indicating that new labour market entrants are not being fully absorbed into employment.
• Employment and Labour Force are almost perfectly correlated (r = 1.000), and 22 variable pairs overall show correlations of 0.90 or higher, confirming that regional population size is the primary driver of all count-based labour metrics.
• Population values range from 14,300 to 2,913,400 persons across the 38 census subdivisions, producing a heavily right-skewed dataset where the overall mean (59.59) is nearly 10 times the median (5.90).
• Rate-based indicators are tightly distributed relative to count metrics — the unemployment rate averages 6.25% (range: 1.8%–14.1%), while employment and participation rates cluster around 62% and 66% respectively.
• 75 data points were flagged as statistical outliers (|Z-score| > 2) in regional unemployment rates, and because the dataset uses 3-month moving averages, these anomalies represent sustained labour market disruptions rather than single-month noise.
• The dataset contains 54,720 records spanning 52 monthly periods, with each observation available as an Estimate, Standard Error of Estimate, or Standard Error of Year-over-Year Change, providing a robust framework for assessing data reliability alongside trends.