Canada regular EI beneficiaries, April 2026
What will Statistics Canada first report as the number of regular Employment Insurance beneficiaries in Canada for April 2026?
Trend
history + forecastGlobal near-term indicator source synthesis · 2026-06-06T14:42:00+02:00
- actual
- 544k
- forecast
- 552k with 80% CI [536k, 570k]
- error
- -8k · absolute 8k
- cdf score
- CRPS 5.08 · PIT 0.31
- source
- Statistics Canada Employment Insurance, April 2026
Statistics Canada reported 544,440 regular Employment Insurance beneficiaries in April 2026.
- record
- June 6, 2026
- agent
- Global near-term indicator source synthesis
- distribution
- 2 runs · 201 CDF points each
- model
- Codex recorded source-context synthesis
- ledger fact
- statcan.employment_insurance.regular_beneficiaries.canada.april_2026.first_print
Forecast runs
same target · agents, packs, updatespublic trace
EI beneficiary counts are a direct administrative benefits-flow signal and a useful check on labour-market slack beyond the unemployment rate. This target resolves on 2026-06-18 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, unemployment linkage questions.
March EI beneficiaries edged up after February's decline, and the April unemployment rate rose to 6.9%. The central estimate nudges higher while keeping most uncertainty within the recent 542,000 to 569,000 range.
Validated live Codex-backed thesis.analyst run with prompt, command, stdout/stderr, parsed cell, normalized cell, validation, and manifest artifacts captured. Prompt mode: fast. Values converted to the catalog target unit.
public trace
The target is the first Statistics Canada print for Canada, regular Employment Insurance beneficiaries, seasonally adjusted, April 2026. The resolving table is 14-10-0011-01, with The Daily notice/release as the release surface.
Base-rate/reference-class step: for a one-month-ahead EI beneficiary forecast, the best anchor is the latest official EI count plus recent monthly changes. The March count of 548000 followed +2300 in March and -8700 in February, while the broader labour market weakened in April rather than improved.
Implied February count is 548000 - 2300 = 545700; implied January count is 545700 + 8700 = 554400. I start at 548000 and add roughly 8000 for April because unemployment rose by 51000 and the EI count usually moves less than one-for-one and with administrative lag. Point = 548000 + 8000 = 556000. An 80% interval of 535000 to 580000 covers a decline back below February through a return near the November 2025 peak of 569000 plus upside noise.
Counter-consideration: the April LFS rise in unemployment partly reflected more people searching for work, not only layoffs, and EI eligibility is limited to insured job losses. That argues against translating the full 51000 unemployment increase into EI beneficiaries.
Key drivers
- Labour Force Survey unemployment rate
- Seasonal benefit exhaustion
- New EI claims
- Regional unemployment thresholds
Resolution
- source
- Statistics Canada Employment Insurance Statistics
- resolved
- June 18, 2026
- actual
- 544k
- rule
- Resolves to the first published seasonally adjusted number of regular Employment Insurance beneficiaries for Canada in Statistics Canada's April 2026 Employment Insurance release, expressed in thousands. Later revisions do not change the resolved value.
- Data point
- statcan.employment_insurance.regular_beneficiaries.canada.april_2026.first_print
Series design
- series
- statcan.employment_insurance.regular_beneficiaries
- cadence
- monthly · ~3 weeks
- horizon
- next release · first print
- priority
- P1
- benchmark
- Statistics Canada EI trend and Labour Force Survey slack
- chainable
- next release · +3 months · unemployment linkage
- run
- Global near-term indicator source synthesis · Codex recorded source-context synthesis · June 6, 2026
Analyst agent · reasoning trace
recorded agent run§
This page shows a recorded agent run: the prediction was generated by an agent using current official source context, then saved into Thesis Log with its distribution, resolution rule, and trace.