Impacts of Environmental Agreements on Bilateral Trade of Climate Industry
Bibliographic record
Abstract
We investigated the effect of agreements related to climate change on bilateral trade, using the Poisson pseudo-maximum likelihood (PPML) estimator on a large dataset that requires computing high-dimensional fixed effects. This study develops the concordance between commodities based on harmonized systems (HS) and technologies defined by both international and cooperative patent classifications (IPC/CPC). Using the OECD ENV-TECH classification, covering 169 exporting countries and 179 importing countries worldwide from 1991 to 2019, we determined the relationship between HS commodities and IPC/CPC climate change technologies. The main findings show that, first, the Kyoto Protocol has increased international bilateral trade in the climate change industry, while the Montreal Protocol has led to the opposite effect. In addition, the impact of environmental stringency on international bilateral trade in climate-related industries was negative and significant, refuting the Porter Hypothesis. This result was consistent within the trade between the convention countries. Therefore, national and industrial perspectives are relative, and voluntary climate mitigation methods should be applied, considering the areas where carbon reduction is relatively difficult. In other words, the conventions and policies must shift to a global paradigm in environmental protection and a more inclusive approach, with recognition of diversity in governance types.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".