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Record W4294292687 · doi:10.1111/1467-8551.12652

Firm‐Level Climate Change Risk and CEO Equity Incentives

2022· article· en· W4294292687 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

VenueBritish Journal of Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of OttawaMemorial University of Newfoundland
FundersSocial Sciences and Humanities Research Council of CanadaMemorial University of Newfoundland
KeywordsEndogeneityIncentiveEquity (law)Equity riskValuation (finance)EconomicsSystematic riskBusinessClimate changeExecutive compensationMonetary economicsPublic economicsMicroeconomicsFinanceEconometrics

Abstract

fetched live from OpenAlex

Abstract We document evidence that CEOs who lead firms that face higher climate change risk (CCR) receive higher equity‐based compensation. Our finding is consistent with the compensating wedge differential theory and survives numerous robustness and endogeneity tests. The result is more prominent for firms that are socially responsible, susceptible to higher environmental litigation and part of the non‐high‐tech industries. Furthermore, we find supportive evidence that firms offering higher equity incentives to their CEOs for managing higher CCR are usually better off in the long run via a lower cost of equity capital and higher firm valuation.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.577

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 communication0.0000.001
Open science0.0000.001
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 head0.042
GPT teacher head0.238
Teacher spread0.196 · 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