Energy Productivity Convergence in Asian Countries: A Spatial Panel Data Approach
Bibliographic record
Abstract
The main purpose of this paper is to examine the convergence of energy productivity for 35 Asian countries over the period 1993–2010. These 35 countries are divided into five different geographical regions, namely, South East Asia, South Asia, North East Asia, North Asia and West Asia. We first use the sigma-convergence approach to investigate the disparity of energy productivity over time and find weak evidence of sigma-convergence process in energy productivity for all sample countries and mixed evidence for sub-sample countries. We then estimate the beta-convergence model by using the spatial panel data approach and find an existence of beta-convergence process in energy productivity for the whole set of sample countries and North East Asia. Moreover, we find mixed evidence of beta-convergence process in energy productivity for South East Asia, North Asia and West Asia. In South Asia, we find strong evidence of divergence process in energy productivity over the study period.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".