The Impact of Foreign Direct Investment on CO2 Emission
Bibliographic record
Abstract
In the literature, the impact of Foreign Direct Investment (FDI) on carbon dioxide (CO2) emissions is explained by two different hypotheses: Pollution Halo and Pollution Haven Hypothesis. While Pollution Halo hypothesis states that FDI provides advanced technology to countries and accordingly decreases CO2 emissions, Pollution Haven Hypothesis indicates that there is a positive relationship between FDI and CO2. In this regard, in this study, the impact of FDI on CO2 emissions in the selected 10 of G-20 countries in the period of 1970-2010 is investigated by using panel data analysis. The empirical findings show that panels have cross-section dependence and these two panels are stationary in different levels. Moreover, the existence of long term relationship between panels is found by using Durbin Hausmann panel cointegration test. The results of the study also show that while Pollution Halo Hypothesis is valid for USA, France and Argentina, Pollution Haven Hypothesis is valid for UK, Canada, Australia, South Africa, Italy, Mexico and Saudi Arabia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".