The Impact of Globalization and Financial Development on Climate Change: Fresh Evidence from 60 Developing Countries
Bibliographic record
Abstract
The scope of this chapter is to investigate the causal effects of globalization and financial development on environmental degradation, proxied by the level of carbon dioxide emissions for 60 developing countries over the period 1970–2014. The econometric methodology accounts for the presence of cross-sectional dependence, while it employs proper cross-sectional augmented panel unit root tests to ascertain unit root properties and cointegration relationships. To secure the robustness of our findings, we employ both parametric and semi-parametric techniques. The empirical findings postulate, for the first time in the empirical literature, a non-monotonic inverted-U-shaped curve between globalization and environmental degradation, similar to the environmental Kuznets curve (EKC) hypothesis. This empirical analysis suggests insightful policy implications for managers and policymakers, as the reduction in CO2 emissions can be achieved without a slowdown in economic activity and financial development.
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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 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".