Production Externalities, Environmental Taxes, and the Gains from Trade
Bibliographic record
Abstract
We analyze the effects of environmental taxation on the pattern of and gains from trade in a two-country Ricardian framework, where production in a polluting sector (e.g. manufacturing) adversely affects productivity in an environmentally sensitive sector (e.g. agriculture). The two countries differ in terms of their production technology so that the productivity loss suffered by the environmentally sensitive sector is higher in the dirtier country. When the countries do not pursue any environmental policy, the dirtier country has a comparative advantage in the polluting good and exports that good in the trading equilibrium. If preference for the polluting good is low, the dirtier country loses from trade while its trading partner gains. Global gains from trade are also negative as the market determined pattern of trade is inefficient. Introduction of a unilateral pollution tax by the dirtier country can enable it to reverse the pattern of trade and the distribution of the gains from trade, such that international trade becomes welfare-improving for that country as well as globally. The conventional pollution haven result may get reversed in the presence of cross-sectoral externalities, as each country has an incentive to set the tax such that it exports the good that is more preferred by consumers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".