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Record W3092062964 · doi:10.5547/01956574.41.5.kjes

Utilities Included: Split Incentives in Commercial Electricity Contracts

2020· article· en· W3092062964 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Energy Journal · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of CanadaMcGill University
KeywordsElectricityIncentiveEconomicsMicroeconomicsLeaseBusinessIndustrial organizationFinance

Abstract

fetched live from OpenAlex

This paper quantifies a tenant-side “split incentives” problem that exists when the largest commercial sector customers are on electricity-included property lease contracts, causing them to face a marginal electricity price of zero. We use exogenous variation in weather shocks to show that the largest firms on tenant-paid contracts use up to 14 percent less electricity in response to summer temperature fluctuations. The result is retrieved under weaker identifying assumptions than previous split incentives papers, and is robust when exposed to several opportunities to fail. The electricity reduction in response to temperature increases is likely to be a lower bound when generalized nationwide and suggests that policymakers should consider a sub-metering policy to expose the largest commercial tenants to the prevailing retail electricity 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.

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)0.001
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 score0.540
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.115
GPT teacher head0.241
Teacher spread0.126 · 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