Labor Supply, Taxation, and the Use of Tax Revenues: A Real-Effort Experiment in Canada, France, and Germany
Bibliographic record
Abstract
We experimentally investigated three variants of a real-effort game with taxation that differed in the degree of redistribution of tax revenue. Concretely, we compared a Leviathan scenario, where no tax is redistributed, with a situation where tax revenues are used to finance a public good involving neither a direct nor immediate monetary transfer to participants and with a scenario where direct transfer payments are made to each participant. Our results confirm previous findings of a nonlinear decreasing relationship between tax rate and work effort. We found that, for tax rates above 50 percent, the level of effort was highest under direct redistribution, followed by the public-good scenario, and by the Leviathan case. Conducting the experiment in Canada, France, and Germany, we observed average effort (and thus tax revenues) to be higher in France than in Canada and Germany.
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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 | 0.000 |
| 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".