Does trade openness affects global carbon dioxide emissions
Bibliographic record
Abstract
Purpose The purpose of this paper is to analyze the effect of economic growth, international trade and energy consumption on the global carbon dioxide (CO 2 ) emissions, in the case of top CO 2 emitters, namely, USA, Japan, Canada, Iran, Saudi Arabia, UK, Australia, Italy, France and Spain using the annual data from 1971 to 2013. Design/methodology/approach For this purpose, the time series, data technique is applied. Unit root test with structural break and the bounds testing approach for cointegration in the presence of structural break is tested. Finally, a vector error correction model for the Granger causality test is applied to detect the direction of causality. The authors have used the techniques that will help in examining the structural break in the time series data. Findings The results reveal that their exists a long-run relationship between CO 2 emissions and its determinants in the USA, Canada, Iran, Saudi Arabia, the UK, Australia, Italy, France and Spain, energy consumption is the main determinant of carbon dioxide (CO 2 ) emissions in the long run and for direction of causality, the authors found bidirectional causality in the long run between energy consumption and CO 2 emissions in the USA, Canada, Iran, Saudi Arabia and the UK, and Granger causality running in opposite direction in the case of Australia from CO 2 emissions to energy consumption was analyzed. In terms of growth-trade-pollution nexus (USA, Canada, Iran and France) hold one-way causality running from economic growth and trade openness to CO 2 emissions (IV) the environmental Kuznets curve hypothesis is validated only for the USA. Robust policy implications can be derived from this study. First, without harming the economy, these countries can reduce the use of energy consumption for lower pollution. Second, the amount of trade should be decreased to lower the emissions because the authors find that an increase in trade does Granger cause to CO 2 emissions in the long run. Originality/value There has been no study that investigated the relationship between CO 2 emissions, real income, consumption of energy and international trade in the environmental Kuznets relation for the top CO 2 emitter’s countries over the period of 1971–2013. The authors did a comparative study of the empirical finding among these nations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".