Is environmental policy a secondary trade barrier? An empirical analysis
Bibliographic record
Abstract
Abstract Should international trade agreements be extended to include negotiations over environmental policy? The answer depends on whether countries distort levels of environmental regulations as a secondary means of providing protection to domestic industries; our results suggest that they do. Previous studies of this relationship have treated the level of environmental regulation as exogenous, and found a negligible correlation between environmental regulation and trade flows. In contrast, we find that, when the level of environmental regulation is modelled as an endogenous variable, its estimated effect on trade flows is significantly higher than previously reported. JEL Classification: F1, F14, F18 Est‐ce que la politique environnementale est une barrière commerciale secondaire? Une analyse empirique Est‐ce que les accords commerciaux internationaux doivent être étendus pour couvrir la politique environnementale? La réponse dépend du degré de distorsion que les pays introduisent dans leur politique environnementale pour protéger leurs industries nationales. Nos résultats suggèrent que cet impact est important. Des études antérieures de cette relation ont traité la politique environnementale comme exogène, et ont montré qu’il existe une co‐relation négligeable entre politique environnementale et flux commerciaux. Au contraire, nous révélons que, quand la politique environnementale est considérée comme variable endogène, son effet sur les flux commerciaux est plus élevé de manière significative que ce qu’on a noté antérieurement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.002 |
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".