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Record W2198099674

Market Power Indices and Wholesale Price Elasticity of Electricity Demand

2014· preprint· en· W2198099674 on OpenAlexaffabout
Talat S. Genc

Bibliographic record

VenueRePEc: Research Papers in Economics · 2014
Typepreprint
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPrice elasticity of demandLerner indexEconomicsMarket powerElectricity marketWholesale marketElectricityElasticity (physics)EconometricsIndex (typography)Agricultural economicsMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

We investigate price responsiveness of wholesale electricity customers in the hourly Ontario wholesale electricity market. We use detailed generator and market level data to calculate market power measures such as the Lerner Index, Residual Supplier Index, and Pivotal Supplier Index which are combined with the competition model to structurally estimate price elasticity of demand in peak hours of summer and winter seasons. We find that the hourly price elasticities are small and change over the peak hours of seasons and years. For instance, in 2008 the elasticity estimates are in the interval of (0.019, 0.083). Comparing high demand winter hours to summer hours indicates that consumers’ price responsiveness is lower in summer than in winter. We also employ these indices along with the estimated price elasticities to project the likely impacts of interconnection capacity expansions on market prices. Our calibrations show that even small amount of transmission investments (and hence trade activities) can result in substantial market price reductions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations3
Published2014
Admission routes2
Has abstractyes

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