Environmental Policy Instrument Choice and International Trade
Bibliographic record
Abstract
We develop a dynamic stochastic general equilibrium model to understand how environmental policy instrument choice affects trade. We extend the existing literature by employing an open economy model to evaluate three environmental policy instruments: cap-and-trade, pollution taxes, and an emissions intensity standard in the face of two types of exogenous shocks. We calibrate the model to Canadian data and simulate productivity and import price shocks. We evaluate the evolution of key macroeconomic variables, including the trade balance in response to the shocks under each policy instrument. Our findings for the evolution of output and emissions under a productivity shock are consistent with previous closed economy models. Our open economy framework allows us to find that a cap-and-trade policy dampens the international trade effects of the business cycle relative to an emissions tax or intensity standard. Under an import shock, pollution taxes and intensity targets are as effective as cap-and-trade policies in reducing variance in consumption and employment. The cap-and-trade policy limits the intensity of the import competition shock suggesting that particular policy instrument might serve as a barrier to trade.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".