Greenhouse gas emissions in Vietnam: an analysis based on a social accounting matrix with firm heterogeneity
Bibliographic record
Abstract
Vietnam is one of the fastest-growing polluters in the world – due to rapid industrialization facilitated by massive foreign investments. This study estimates the sources of greenhouse gas (GHG) emissions arising from activities of firms using a social accounting matrix (SAM) that incorporates firm heterogeneity based on ownership style, namely, state-owned enterprises, private firms, and foreign-invested enterprises. The results show that an increase in exports or investments increases GHG gas emissions to varying degrees depending on whether the increase occurs in state-owned enterprises, private firms, or foreign-invested enterprises (FIEs). The largest increase in emissions results from an increase in exports and investments of FIEs, whereas the increase in emissions due to private firms and SOEs is much smaller. The results imply that it is important to consider the impact of foreign investments and the activities of foreign firms on GHG emissions in Vietnam.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".