AI Analysis: Employment insurance beneficiaries (regular benefits) by province, territory and occupation, monthly, unadjusted for seasonality

Executive Summary

This Statistics Canada dataset (Table 14100455) tracks monthly Employment Insurance regular benefit recipients across 824 occupational categories nationally from January 2008 to February 2026, encompassing 179,632 records. The data reveals a historically stable average of ~593,640 monthly beneficiaries punctuated by a dramatic COVID-19 spike peaking at 1,759,470 in February 2021 — roughly three times the long-run average. As of February 2026, beneficiary counts have normalized to 666,000, remaining somewhat elevated relative to pre-pandemic baselines.

Key Findings

• The all-time peak of 1,759,470 EI beneficiaries occurred in February 2021, approximately 3x the historical monthly average of 593,640, driven directly by COVID-19 pandemic lockdowns and emergency labour market disruptions.
• As of February 2026, there are 666,000 EI beneficiaries — significantly down from the pandemic peak but still elevated compared to pre-pandemic levels, suggesting incomplete labour market normalization.
• The dataset covers 824 unique occupation categories over 218 months, with the value distribution being heavily right-skewed: the median beneficiary count per record is just 660 persons versus a mean of 4,425, and 75% of records fall at or below 2,560 beneficiaries.
• An anomalously low reading of 122,340 beneficiaries was recorded in September 2020, representing a brief inter-wave recovery window sandwiched between the first and second surges of the pandemic.
• Occupations in trades and labour-intensive industries consistently rank among the highest average EI beneficiary categories, reflecting their exposure to seasonal and cyclical employment patterns.
• A secondary outlier period during the 2008–2009 financial crisis shows claims elevated well above pre-crisis norms, confirming the dataset captures two major economic shock events across its 18-year span.
• Correlations between numerical variables are negligible (the strongest being VALUE vs. occupation hierarchy code at -0.073), confirming that EI beneficiary counts are driven by categorical and temporal factors rather than simple linear relationships.