Dynamic Economic Analysis between Renewable Energy, Carbon Dioxide Emissions, Trade and GDP based on VECM Granger test and Wavelet Analysis
Bibliographic record
Abstract
In this study, we explored the dynamic economic relationship between Taiwan’s GDP growth, renewable energy consumption, foreign trade openness, and CO2 emissions from 1965 to 2016. Our analysis is based on using updated data to test the existence of Taiwan's EKC model and discuss the causal relationship between CO2 emissions and variables such as GDP growth, renewable energy consumption, and foreign trade opening. We used multicollinearity analysis to test the stationarity of the quadratic form of the EKC model, ADF and KPSS techniques, and Johansen and Juselius cointegration tests and found that there is a long-term equilibrium. By using VECM Granger causality test and wavelet coherence analysis, we further explored the causal relationship between CO2 emissions and other related variables, and found that there is a two-way causal relationship between carbon dioxide emissions and renewable energy consumption in the short term. In addition, from the wavelet correlation analysis of GDP growth and CO2 emissions, it can be seen that 1992 was a turning point in Taiwan’s economic development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".