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Record W3028263843 · doi:10.5547/01956574.42.3.mpod

The Price Impact of Energy Vouchers

2020· article· en· W3028263843 on OpenAlexaff
Marion Podesta, Jean‐Christophe Poudou, Michel Roland

Bibliographic record

VenueThe Energy Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversité Laval
FundersAgence Nationale de la Recherche
KeywordsVoucherEconomicsMicroeconomicsRegulator

Abstract

fetched live from OpenAlex

France and South Korea have implemented voucher programs to counter energy poverty. In contrast to goods that traditional voucher programs target, the market structure that dominates energy supply is the oligopoly. In this paper, we study the price impact of vouchers in this market structure. We first state conditions on demand elasticities that make the choice of vouchers consistent with the regulator’s objective of eliminating energy poverty. We then model a game between energy suppliers and the regulator, where suppliers maximize profit while the regulator ensures that no consumer spends more than a given share of income on energy.From a benchmark case without vouchers, we show that vouchers reduce the energy price under simultaneous decision making or when the regulator moves first. However, the price impact of vouchers is ambiguous if firms move first. This scenario’s price is above the price of the simultaneous decision scenario’s price.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.860
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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 teacher head, not a consensus.

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

Citations6
Published2020
Admission routes1
Has abstractyes

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