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Record W4385200373 · doi:10.1016/j.jeem.2023.102853

Economically exhaustible resources in an oligopoly-fringe model with renewables

2023· article· en· W4385200373 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

VenueJournal of Environmental Economics and Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsEconomicsNon-renewable resourceOligopolyRenewable energyMicroeconomicsNash equilibriumImperfect competitionSubsidyNatural resource economicsRenewable resourceFossil fuelCournot competitionEconometricsEcology

Abstract

fetched live from OpenAlex

We consider a game between oligopolistic and fringe suppliers of fossil fuel from an exhaustible resource, and producers of a renewable perfect substitute. Extraction costs are stock-dependent and strictly convex in the rate of extraction. We characterize the open-loop Nash equilibrium analytically and perform numerical simulations with calibrated parameter values. The effects of our cost assumptions are (i) to have asymptotic economical instead of physical exhaustion of the non-renewable resource and (ii) the existence of a limit-pricing phase in which both fossil and renewables suppliers are active. We decompose the welfare loss of imperfect competition in a conservation and a sequence effect, and show that both can be substantial: 3.8 and 4.2 trillion US$ in the calibrated model, respectively. We also examine Green Paradox effects and find that initial carbon emissions depend non-monotonically on the renewables subsidy rate.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.040
GPT teacher head0.208
Teacher spread0.168 · 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