Is energy consumption neutral to economic growth? An empirical analysis on energy conservation and decoupling
Bibliographic record
Abstract
Climate change is a global-scale phenomenon, but is not impacting everyone equally. The heterogeneous socio-economic manifestations at the regional level of climate change require plenty of different adaptation strategies. However, its causes are few, with human activity and the related emission of Greenhouse gases (GHG) being the single most important cause. Here we explore the economic consequences of a specific climate change mitigation strategy: the reduction of total energy consumption by the eleven most industrialised countries. We estimate a Structural Vector Autoregressive Model (SVAR) by means of short-run restrictions and long-run restrictions that are entirely implied by the properties of the data (cointegra- tion and non-Gaussianity). We also outline the poor real-world applicability of the Granger causality definition in this context. Our evidence suggests that energy con- servation policies negatively affect Gross Domestic Product (GDP) in Belgium and France, and also in Canada and Great Britain after 3-4 years. Such policies are neutral to economic growth in the Italy, Japan and in the US. This implies that for most countries, reducing energy consumption may not affect GDP growth; such result supports climate change mitigation policies based on the reduction of energy consumption. Cointegration analysis further suggests that for 9 out of the 11 countries examined, GDP and energy consumption are not bound by the same long-run relationship: while both GDP per-capita and energy consumption are growing, GDP is growing at a much faster pace. This dramatic decrease in energy intensity (energy consumption over GDP) is often termed energy-use decoupling. By considering U.S. quarterly data, we find that positive shocks in the share of renewable energy consumption and in Total Factor Productivity (or TFP) reduce the amount of energy required to produce one unit of GDP. The share of renewable energy consumption variable can explain a larger decrease in energy intensity, and its effect is more per- sistent than the effect of positive productivity shocks. This implies that in the US, increasing the share of renewable energy is more effective than focusing on the total factor productivity to produce more by consuming less energy per unit of product.
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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".