Imported carbon emissions: Evidence from French manufacturing companies
Bibliographic record
Abstract
Abstract This paper analyzes imported carbon emission at the firm level. To do so, we combine information on emissions, imports, imported emissions and energy prices for French manufacturing firms between 1997 and 2014. We document a significant increase of the carbon emissions embedded in imports of French manufacturing companies over the period 1997 to 2014 that is attributable mainly to a shift towards more carbon‐intensive products and countries. We then estimate the impact of imported emissions on domestic emissions and emission intensity using a shift‐share instrumental variable strategy based on third countries supply shocks. We do not find compelling evidence of an impact of carbon imports on total emissions, but emission efficiency improves significantly in companies offshoring emissions abroad. A 10% increase in carbon offshoring causes a 4% decline in emission intensity. In addition, we find that the elasticity of domestic emission intensity to imported emissions is stronger in energy‐intensive sectors, on high‐productivity companies and among exporters. Reassuringly, the relationship between imported emissions and emission intensity does not seem to be driven by a pollution haven motive.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".