Redistributive Taxation under Ethical Behaviour*
Bibliographic record
Abstract
Abstract We consider the implications of ethical behaviour on the effect of a redistributive tax‐transfer system. In choosing their labour supplies, individuals take into account whether their tax liabilities correspond to what they view as ethically acceptable. If tax liabilities are viewed as ethically acceptable, a taxpayer behaves ethically, does not distort her behaviour, and chooses to work as if she were not taxed. On the other hand, if ethical behaviour results in tax liabilities that exceed those that are ethically acceptable, she behaves egoistically (partially or fully), distorts her behaviour, and chooses her labour supply taking into account the income tax. We establish taxpayers' equilibrium behaviour and obtain that labour supply is less elastic when taxpayers may behave ethically than when they act egoistically. We characterise and compare the egoistic voting equilibrium linear tax schedules under potentially ethical and egoistic behaviour. We also compare our results to those obtained under altruism, an alternative benchmark.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".