MétaCan
Menu
Back to cohort
Record W2046375903 · doi:10.1177/0973801012462121

The Dynamics of Electricity Consumption and Growth Nexus: Empirical Evidence from Three Developing Regions

2012· article· en· W2046375903 on OpenAlexaff
Anupam Das, Murshed Chowdhury, Syeed Khan

Bibliographic record

VenueMargin The Journal of Applied Economic Research · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsUniversity of ManitobaMount Royal University
Fundersnot available
KeywordsNexus (standard)ElectricityEconomicsConsumption (sociology)Panel dataGeneralized method of momentsEconometricsLatin AmericansElectricity systemMacroeconomicsElectricity generationPower (physics)

Abstract

fetched live from OpenAlex

In this article, a panel of 45 developing countries for the 1971–2009 period is used to investigate the dynamic relationship between electricity consumption and economic growth. We employ the system generalised method of moments (system GMMs) approach proposed by Blundell and Bond (1998), which is an information-efficient means of obtaining consistent coefficient estimates. Our result suggests a positive relationship between electricity consumption and economic growth when the full panel is estimated. Regional analysis suggests a positive growth–electricity nexus for Asia and the Pacific and the sub-Saharan African region, although the size and significance levels are different. We do not find any statistically significant relationship between electricity consumption and economic growth in Latin America and the Caribbean. JEL Classification: Q43, O13, O44, C23

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)0.001
metaresearch head score (Gemma)0.002
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 score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.168
GPT teacher head0.323
Teacher spread0.155 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueMargin The Journal of Applied Economic ResearchSame topicEnergy, Environment, Economic GrowthFrench-language works237,207