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Record W2176597700 · doi:10.5539/jsd.v8n9p89

Energy Use and GDP in Israel

2015· article· en· W2176597700 on OpenAlexvenueno aff
Cosimo Magazzino

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEnergy (signal processing)EconomicsStatisticsMathematics

Abstract

fetched live from OpenAlex

The paper aims to study the relationship between energy use and GDP in the period 1971-2007 for Israel with a time-series approach. Stationarity and unit root tests reveal that both series are non-stationary, or I(1). Moreover, since both series show the presence of a structural break, the Gregory and Hansen cointegration test has been conducted. The results evidence the presence of a long-run relationship. Causality tests reveal that the “conservation hypothesis” emerges, since the causality flow runs from aggregate income to energy use. The IRFs analysis evidences that a shock to the energy use affects GDP for one period, but dies out very quickly. While shocks to GDP create a smaller but significant response in the energy use, although it falls to zero in few periods. Finally, we calculate with an ECM that the total long-run multiplier is 0.95. The energy use will increase to correct the disequilibrium, with 68% of the (remaining) deviation corrected in each subsequent time period. In addition, a one-unit increase in the GDP immediately produces a 0.18 unit increase in the energy use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.017
GPT teacher head0.203
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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