Minimum Wage and Household Consumption in Canada: Evidence from High and Low Wage Provinces
Bibliographic record
Abstract
The minimum wage is a major factor for the successful implementation of much of the sustainable development goals (SDGs). The present research will investigate whether minimum wage (MW) as a sustainable wage policy improves household consumption. Thus, a panel-based analysis comparing high wage (Alberta, British Columbia, Ontario, and Saskatchewan) and low wage provinces (Manitoba, New Brunswick, Newfound land/Lab, Nova Scotia, Prince Edward Island, and Quebec) is employed for the Canadian case within the study period from 1981 to 2019. We analyze the long-term and short-term effects of MW on household consumption using the Dynamic Autoregressive Distributed Lag techniques of the Pooled Mean Group, Dynamic Fixed Effects, and Mean Group estimators. Results show that the long-term impact of MW on household consumption is positive in both the low- and high-wage provinces. The short-term effect is negative in both wage groups, but not significant for the low-wage group. This offers significant debate on the relevance of the MW towards economic stabilization and consumption-led growth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".