Excise Taxation To Preserve Health and To Protect the Environment: A Review
Bibliographic record
Abstract
Excise duties continue to be coveted sources of revenue, particularly in developing countries, because they are easy to collect and cause few economic distortions. In developed economies, on the other hand, excise duties are increasingly considered useful instruments for enhancing social and market outcomes by internalizing the financial, physical, and psychological costs that abusive consumers and producers impose on other people (that is, external costs) and, unintentionally, on themselves (that is, internal costs). By internalizing these costs in the price of goods and thereby confronting consumers with the true cost of consumption, excise duties on tobacco, alcohol, sugar, and gambling can induce these consumers to preserve the quality of their health. Similarly, excise duties on carbon, cement, transport, and plastics can correct for the human-induced degradation of the environment. In this paper, the author identifies the revenue-raising and externality- and internality-correcting features of excise taxation and reviews, in this context, some of the main developments and issues encountered in subjecting particular excisable goods and services to excise taxation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".