Transboundary pollution, tax competition and the efficiency of uncoordinated environmental regulation
Bibliographic record
Abstract
Abstract Under capital tax competition, surprisingly, Ogawa and Wildasin (2009) find that uncoordinated policymaking leads to a first‐best outcome even in the presence of transboundary pollution. However, I show that if the level of environmental regulation is endogenized, the regulation level becomes too loose compared with the optimum (“race to the bottom”). Thus, despite the efficiency result of Ogawa and Wildasin (2009), efforts to achieve international environmental policy coordination are needed. I then examine the dependence of this result on the level of decisive voter's capital endowment. The regulation is inefficiently loose in many cases, but it can be too strict if the decisive voter's capital endowment is above the average. Thus, the possibility of “race to the top” cannot be eliminated. The inefficiency result does not generally depend on the timing of policymaking, although the efficiency may be restored in the limit case where the decisive voter has no capital at all.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".