CO <sub>2</sub> emissions converge in China and G7 countries? Further evidence from Fourier quantile unit root test
Bibliographic record
Abstract
G7 countries and China are considered not only the biggest energy producers globally but also the largest CO 2 emission groups of countries among the world. In this study, we apply the Fourier quantile unit root test to investigate whether CO 2 emissions converge in China and G7 countries using per capita CO 2 emissions data over 1950–2013. While traditional unit root test results indicate that per capita CO 2 emissions do not converge among these G7 countries and China, empirical results from the Fourier quantile unit root test point out that the CO 2 emissions did converge in Germany, Italy, and the United Kingdom. Although the results of this study do not find strong CO 2 emission convergence in the other five countries (i.e., Canada, France, Japan, the United States, and China), the CO 2 emissions did converge in certain quantiles for these five countries. Our empirical results have important policy implications for the governments of G7 countries and China to implement the effective energy policy to reduce the CO 2 emissions.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".