The Contribution of China’s Outward Foreign Direct Investment (OFDI) to the Reduction of Global CO2 Emissions
Bibliographic record
Abstract
Under economic globalization, with the intensification of China’s reform and opening up, China’s outward foreign direct investment (OFDI) has continuously gained momentum, but CO2 emissions caused by the OFDI have not been given due attention. As one China is of the world’s leading CO2 emitters, it is necessary to conduct thorough research into the CO2 emission problem caused by China’s OFDI. Thirty-four host countries were selected as the objects of this study, including some European countries, Australia, India, Indonesia, Brazil, Canada, Japan, Korea, Mexico, Russia, and the USA. Their CO2 emissions as caused by China’s OFDI were calculated using the input-output model with non-competitive imports, the data of China’s OFDI flows, and their own energy consumption and CO2 emissions from 2000 to 2011. Then a comparative analysis was performed taking China as the comparative object. CO2 emission transfer of China’s OFDI was studied quantitatively. Finally, CO2 emissions from China’s OFDI were discussed from the perspective of industry selection and location selection. The results showed that China’s OFDI could achieve the aim of reducing global carbon emissions with reasonable industry and location selection.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".