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Record W3033497119 · doi:10.1111/jpet.12450

Environmental certification programs: How does information provision compare with taxation?

2020· article· en· W3033497119 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

VenueJournal of Public Economic Theory · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsYork University
Fundersnot available
KeywordsCertificationCompetition (biology)Monopolistic competitionQuality (philosophy)Environmental qualityEconomicsFree entryPublic economicsBusinessMicroeconomicsIndustrial organizationMonopoly

Abstract

fetched live from OpenAlex

Abstract This paper develops a monopolistic competition framework to assess whether environmental certification programs can serve as effective substitutes for more traditional policy instruments such as environmental taxation or a minimum quality standard (MQS). I show that if firms can organize themselves and choose the certification standard collectively, then there is a beneficial role for a regulator to intervene. Also, the degree of substitution between differentiated goods that impose environmental damage and a “clean” outside good, the degree of competition in the industry and the extent of environmental damage caused by minimal quality goods are important considerations in the choice between a certification program and a tax or a MQS. While the comparison between a certification program and a tax depends on numerous factors, I find unequivocally that certification is a poor substitute for taxation whenever the outside good is a close substitute for differentiated goods, there is a high degree of competition in the industry or if minimal quality goods impose considerable environmental damage.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.357

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 communication0.0000.002
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 head0.039
GPT teacher head0.200
Teacher spread0.160 · 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