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Record W2971134310 · doi:10.1007/s11146-019-09720-0

Energy Efficiency Information and Valuation Practices in Rental Housing

2019· article· en· W2971134310 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.

Bibliographic record

VenueThe Journal of Real Estate Finance and Economics · 2019
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsUniversity of Guelph
FundersHorizon 2020Nederlandse Organisatie voor Wetenschappelijk OnderzoekEuropean Commission
KeywordsValuation (finance)RentingProperty valueEfficient energy useDatabase transactionResidential propertyTransaction costActuarial scienceBusinessEnergy (signal processing)EconomicsEconometricsFinanceStatisticsReal estateMathematicsEconomic geographyDatabasePolitical scienceLawComputer scienceEngineering

Abstract

fetched live from OpenAlex

The consensus in the academic literature is that energy efficiency is associated with transaction value premiums, but it is not clear to what extent property appraisers take account of this. We decompose external appraisals of rental housing by international valuation firms in England and the Netherlands in two waves, keeping the samples of valued homes constant between these years. We find a notable change in the behavior of external property appraisers. In England, energy performance does not impact assessed values in 2012, while estimation results for 2015 show a significant discount in assessed values for D-, E- and F- relative to C-labeled dwellings. For the Netherlands, we do not observe a significant relationship between energy efficiency and assessed values in 2010, but in 2015 we find that more energy efficiency leads to higher external valuations.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.134

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 communication0.0000.001
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 head0.011
GPT teacher head0.226
Teacher spread0.216 · 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