Unemployment invariance hypothesis, added and discouraged worker effects in Canada
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the long-run relationship between unemployment rate (UR) and labor force participation rate (LFPR) for men and women in Canada. Given that there are differences in the URs and participation rates of men and women, the authors perform separate analysis for them also. Design/methodology/approach The authors use co-integration analysis to investigate the existence of a long-run relationship between UR and LFPR in Canada using time series monthly data for the past 40 years. Findings The finding that there is long-run relationship between UR and LFPR leads the authors to doubt the pertinence of the unemployment invariance hypothesis for Canada. The authors further find evidence for added-worker effect for men and discouraged-worker effect for women in Canada and the authors elaborate on the possible explanations for this seemingly contradictory finding. Practical implications The lack of support for the unemployment invariance hypotheses implies that changes in the participation rate which may be due to aging population, policies of early retirement or constraints on working time will affect the UR in the long run. Originality/value This paper investigates the unemployment invariance hypothesis in Canada to come up with policy implications about long-run UR. The authors further elaborate on the possible explanations for the added-worker effect for men and the discouraged-worker effect for women that the authors find in this study.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".