Investigating the Interactive Role of Demand Side Factors Potentially Responsible for Energy Crisis in Pakistan
Bibliographic record
Abstract
This paper attempts to investigate the dynamic relationship among Energy Consumption (E), Financial System Development (F), Industrailization (I), Agriculture Development (A) and Economic Growth (Y) in case of Pakistan for the period 1971-2018 by using cointegration approach. After confirming the level of stationarity, the presence of long run relationship among the series was tested through newly developed combined cointegration approach in addition to ARDL bound testing with structural break dummy. The short run and long run parameter coefficients were estimated by unrestricted error correction model (UECM) because all the series are found stationary at 1st difference I(1) and sufficient evidence of cointegration. Finally, the direction of causality among the considered variables was achieved through Granger causality test within the framework of VECM. The long run parameter coefficient estimates by UECM indicate that financial development, industrialization, economic growth and decrease in agricultural contribution to GDP induce electricity consumption in Pakistan. We also found that a long-run unidirectional causality is running from the economic growth to electricity consumption which favors the electricity conservation hypothesis in case of Pakistan. The causality running from the electricity consumption to agriculture output coupled with negative parameter coefficient value suggests that electric power deficit is responsible for hampering the agricultural growth in Pakistan. The study suggests that electricity conservation policy in addition to prudent rationing of electric power among the various sectors may greatly contribute to minimize the adverse effects of energy crisis in Pakistan.
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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) | 0.000 | 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".