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Record W4400354823 · doi:10.58886/jfi.v22i1.6774

Intersection of Climate Beliefs and Sustainability: An Empirical Study of Energy Efficiency Premiums in the Residential Real Estate Market

2024· article· en· W4400354823 on OpenAlexaff
Yuchen Lin

Bibliographic record

VenueJournal of Finance Issues · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsQueen's University
Fundersnot available
KeywordsSustainabilityIntersection (aeronautics)Real estateEstateBusinessEfficient energy useEmpirical researchFinancial economicsEnvironmental economicsEconomicsNatural resource economicsFinanceEngineeringTransport engineeringMathematics

Abstract

fetched live from OpenAlex

Building on both the certification literature and previous work on the impact of climate change on real estate prices, this paper investigates how the prices of more sustainable homes differ from conventional homes. This paper utilizes data from the Green Building Registry and the Yale Climate Opinion Maps, along with Zillow housing price datasets and uses the hedonic pricing model to estimate the economic impact of energy efficiency on housing prices. Using comprehensive sales transaction data merged with energy rating data of U.S. real estate properties, this paper finds that properties with better energy ratings are sold at a premium compared to those with poor energy performance. The results also suggest that the premium is more profound among neighbourhoods that are more concerned about sustainability and environmental issues. The paper contributes meaningfully to the sustainable finance literature and the energy ratings literature. It has the potential to further our understanding of the role of energy ratings on real estate pricing and how climate beliefs may impact this role.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.062
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.017
GPT teacher head0.290
Teacher spread0.273 · 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 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
Published2024
Admission routes1
Has abstractyes

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