Cross-border externalities and trade liberalization: the strategic control of pollution
Bibliographic record
Abstract
We examine international trade in a commodity whose production creates a negative externality for the importing country; and we consider the nations’ strategic policy choices, when they can restrict trade, and when they are bound by a free-trade agreement. When pollution-abatement technology is available, the exporting country induces its adoption, despite national indifference to the externality, in order to reduce the tariff. In a free-trade agreement, environmental policy is used to exploit monopoly power in trade. An alternative policy instrument, a process standard is introduced. National competition in controlling emissions leads to very restrictive anti-pollution measures. Extemalités trans-frontières et libéralisation du commerce international: le contrôle stratégique de la pollution . Les auteurs examinent le commerce international d’un bien dont la production engendre un effet externe négatif pour le pays importateur. Ils considèrent les choix de stratégies politiques pour ces nations quand elles peuvent restreindre le commerce et quand elles sont liées par un accord de libre échange. Quand une technolgie qui réduit la pollution est disponible, le pays exportateur promeut son adoption, même s’il est indifférent par rapport à l’effet externe, de façon à réduire le droit de douane. Dans le cadre d’un accord de libre-échange, la politique environnementale est utilisée pour exploiter un pouvoir de monopole dans le commerce. On introduit un instrument de rechange de politique publique, des normes appliquées au processus de production. La concurrence nationale pour le contrôle des émissions va tendre à engendrer la mise en place de mesures anti-pollution fort strictes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".