Bibliographic record
Abstract
Over the past two decades, numerous experts and politicians have proposed “revenue-neutral carbon tax shifts,” under which a government implements a carbon tax and uses the resulting revenue to cut other taxes by an equal dollar amount. These proposals commonly include legal or political mechanisms to bind governments to revenue neutrality over time. This Article’s central claim is that revenue neutrality suffers from conceptual and epistemic confusion that should lead to reconsideration of the policy merits of carbon tax shifts. To illustrate the argument, the Article provides the first retrospective review in the legal literature of carbon tax shifts from four jurisdictions, two of which were implemented and then repealed, and two of which were rejected by voters at the ballot box. In each jurisdiction, the carbon tax shift was afflicted by confusion between two substantially different conceptions of revenue neutrality, which can be termed “backward-looking” and “sideways-looking” revenue neutrality. This confusion is difficult to resolve because the choice between the two conceptions presents governments with a dilemma: backward-looking revenue neutrality is normatively undesirable, while sideways-looking revenue neutrality is difficult to enforce through legal and political mechanisms. This Article argues that the dilemma should be taken into account when choosing between carbon tax shifts and alternative uses of carbon pricing revenues. The dilemma also has implications for revenue-neutral tax reform in other contexts: it is far harder to separate the question of “how to tax” from the question of “how much to tax” than is commonly understood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".