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Record W134331516 · doi:10.15173/esr.v10i1.423

A Forecast of Energy Demand in Japan Considering Asymmetric Price Elasticities

2001· article· en· W134331516 on OpenAlexvenueno aff
Yutaka Nagata

Bibliographic record

VenueEnergy Studies Review · 2001
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsEnergy demandEnergy (signal processing)EconometricsPrice elasticity of demandDemand curveMicroeconomicsNatural resource economicsMathematics

Abstract

fetched live from OpenAlex

Considering asymmetric price elasticities in energy demand functions is an important issue in the field of energy economics. We have estimated past energy demand functions by sector and types of energy in Japan, and confirmed the existence of asymmetric price elasticities in most of the functions. As in the previous studies, when energy prices are falling, price elasticities are insignificant in most of the energy demand functions. Even when energy prices are rising, price elasticities are not significant in many of the functions. We have also constructed a simple energy and economy model to compare future energy demands between the cases with symmetric or asymmetric energy price elasticities. The results show that future energy demand with asymmetric price elasticities is greater than that with symmetric price elasticities. This is because in the asymmetric case, past maximum prices are the most significant factors and price effects will not work unless future energy prices exceed past maximum levels.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.035
GPT teacher head0.274
Teacher spread0.238 · 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 designSimulation or modeling
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

Citations3
Published2001
Admission routes1
Has abstractyes

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