How do climate policy uncertainty and renewable energy and clean technology stock prices co-move? evidence from Canada
Bibliographic record
Abstract
Abstract This work probes the dynamic co-movement between the Climate Policy Uncertainty Index (CPU) and the Renewable Energy and Clean Technology Index (RECT) employing the novel wavelet power spectrum (WPS) and wavelet coherence (WC) approaches for monthly data between 2013 and 2022. Using the wavelet approach enables us to observe the causality direction from both time and frequency dimensions and also to help detect the causal linkage in the short-medium and long-term horizons. This is the first study aiming to perform this relationship from both time and frequency dimensions. Remarkably, findings reveal that: i) CPU seems only volatile in 2019 and 2021 in the short run; (ii) there was significant volatility in the RECT in the short and long terms (SLT) between 2018 and 2022; (iii) RECT significantly caused the CPU between 2014 and 2018; iv) after 2019, CPU started to cause RECT in the short and medium terms (SMT).
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".