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Record W3125431043

Residential Electricity Pricing in Texas’s Competitive Retail Market

2020· preprint· en· W3125431043 on OpenAlexaff
David P. Brown, Chen-Hao Tsai, C.K. Woo, Jay Zarnikau, Shuangshuang Zhu

Bibliographic record

VenueRePEc: Research Papers in Economics · 2020
Typepreprint
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPrepayment of loanVolatility (finance)Electricity retailingBusinessMarket powerSample (material)ElectricityEconomicsElectricity marketCommissionLimit pricePrice levelCommerceMonetary economicsMicroeconomicsFinancial economicsFinance
DOInot available

Abstract

fetched live from OpenAlex

Using a large sample of residential retail electricity plans advertised on the Public Utility Commission of Texas’s Power-to-Choose website between during January 2014 to December 2018, our panel regression analysis finds changes in the projected wholesale price of electricity are not fully reflected as changes in these plans’ price quotes. The estimated rates of wholesale price pass-through range from 43% to 45%. Retailers tend to charge risk premia that increase with wholesale price volatility. Prepayment and time-of-use plans likely contain price premia. The price premia associated with higher-than-average renewable energy contents in the early years of our sample have largely vanished by 2018. Longer contract terms come at a higher price. Finally, increased customer switching tends to reduce retail price quotes, implying that Texas’s residential retail market can be made more price competitive through consumer education on plan choices and dissemination of credible price information.

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 score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.027
GPT teacher head0.284
Teacher spread0.257 · 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
Published2020
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicEnergy Efficiency and ManagementFrench-language works237,207