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Record W2186615853

Availability and Pricing of ENERGY STAR Room Air Conditioners

2005· article· en· W2186615853 on OpenAlexaboutno aff
Thomas Mauldin, Angela Li, Lynn Hoefgen, Thomas Ledyard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Star (game theory)IncentiveEnergy (signal processing)Order (exchange)EconomicsBusinessMicroeconomicsGeographyFinanceMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

Many appliance market transformation programs offer customer incentives in order to promote the purchase of ENERGY STAR ® room air conditioners (RACs). Because sales of RAC units are highly seasonal, it is important to understand seasonal availability and its potential effects on pricing. This research stemmed from the observation that the market share of ENERGY STAR-labeled RACs is typically higher in the third quarter of the year than in the second quarter. One hypothesis was that this trend may be due to consumers selecting cheaper non-ENERGY STAR models when they are available at the beginning of the summer season, and more expensive ENERGY STAR models toward the end of the season when the alternative non-ENERGY STAR models are sold out. Hence the research team collected price and feature information on models available at Massachusetts retailers in May and August of 2004. A regression analysis performed on these data found that the ENERGY STAR label adds about $39 to the price of a RAC unit, and that, overall, units sold in the third quarter have a price discount of about $16. However, the price difference between ENERGY STAR and non-ENERGY STAR models does not substantially differ from one quarter to another. Hence retailers do not appear to be “gaming” the incentives offered by program sponsors, which are only available during the second quarter. In addition, program incentive levels ($25 in 2004) appear to be reasonable, representing about two-thirds of the incremental cost of an ENERGY STAR model.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.722

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 science0.0000.000
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 head0.007
GPT teacher head0.213
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2005
Admission routes1
Has abstractyes

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