Energy Consumption and Economic Growth: A Panel Cointegration Analysis for Developing Countries
Bibliographic record
Abstract
The aim of this paper is to examine the long-run relationship between energy consumption and economic growth for 80 developing countries from 1990 to 2009. For this purpose, methods of panel unit root test, panel cointegration test and panel dynamic ordinary least squares (DOLS) are applied. These 80 countries are divided into three income groups, namely, upper middle income countries, lower middle income countries and low income countries. The empirical results reveal a long-run cointegrated relationship between energy consumption and economic growth for the whole panel of countries as well as for each group of countries. We find the strong relation running from energy consumption to economic growth for upper middle income countries and lower middle income countries, and a strong relation which runs from economic growth to energy consumption for low income countries. These findings clearly indicate that energy consumption had a positive and statistically significant impact on economic growth in the long-run for these countries.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".