Spousal labour supply adjustments to extended benefits weeks: Evidence from Canada
Bibliographic record
Abstract
In this paper, we study the impact of increased unemployment insurance generosity in terms of additional weeks of benefits on a spouse's labour supply adjustments after the job loss of his/her partner. We exploit the longitudinal household format of the Canadian Labour Force Survey and the Survey of Labour and Income Dynamics to study the labour force transitions of each spouse over time and spousal labour supply responses arising from an added worker effect, whereby spousal labour supply increases following the partner's job loss. We examine whether the additional weeks of benefits offered by the Extended Weeks (EW) pilot, an initiative of the Employment Insurance program implemented in a subset of regions, had a differential impact on spousal labour supply adjustments. Employing a difference-in-differences (DiD) approach, the crowding-out effect of this increased EI generosity on spousal labour supply is identified. Our fixed-effect estimation results show a statistically significant added worker effect for women of 14 to 17 hours weekly following their partner's job loss if they are not eligible to receive EI benefits. The eligibility of employment insurance benefits reduces spousal labour supply among women by 3 to 6 hours per week, with a stronger effect among mothers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".