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Record W1608818809

Does it Really Pay to Be Green? An Empirical Study of Firm Environmental and Financial Performance

2001· article· en· W1608818809 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

VenueSSRN Electronic Journal · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsPosition (finance)Valuation (finance)BusinessOutcome (game theory)Porter hypothesisWork (physics)Empirical evidenceEmpirical researchEconomicsIndustrial organizationEnvironmental regulationFinancePublic economicsMicroeconomicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

Previous empirical work suggests that profitable firms tend to have high environmental performance, but questions persist about the nature of the relationship. Does stronger environmental performance really lead to better financial performance or is the observed relationship the outcome of some other underlying firm attribute? Does it pay to have clean running facilities or to have facilities in relatively clean industries? In other words, do the fixed attributes and strategic position of firms cause an apparent but false relationship between financial and environmental performance? To explore this issue, we analyze 606 U.S. manufacturing firms over the time period 1987 to 1996. While we find evidence of an association between lower pollution and higher financial valuation, we find that a firm's fixed characteristics and strategic position might cause or moderate this association. It suggests that When it pay to be green? may be a more important question than does it pay to be green?

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.607

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 science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.232
Teacher spread0.223 · 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