Is Revenue Neutrality in Carbon Taxation Possible in Practice? Lessons from the Canadian Experience
Bibliographic record
Abstract
While the potential economic efficiency, equity, and political acceptability benefits of a revenue-neutral carbon tax have been well studied, a deeper question remains about the feasibility of revenue neutrality in practice. This article provides perspective on this issue by assessing different definitions of revenue neutrality and presenting an in-depth discussion of the motivations for the adoption of revenue-neutral carbon taxes. Two examples of carbon taxes and revenue recycling implemented in Canada are examined: British Columbia's revenue-neutral carbon tax (a carbon tax with offsetting tax cuts) and the Canadian federal government's fuel charge and climate action incentive tax credit (a carbon tax and dividend). The BC case serves to highlight the inherent difficulties of assessing revenue neutrality owing to uncertainty about what would have occurred in the absence of the tax. As time passes following initial implementation of the tax, it becomes increasingly difficult to determine whether, and to what extent, government revenue, income tax rates, the overall tax structure, and the tax base might have differed had the tax not been adopted. The federal example suggests that a carbon tax and dividend policy would be better able to ensure revenue neutrality.
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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 | 0.020 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.020 | 0.021 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.010 |
| 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".