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Record W2018933200 · doi:10.1111/0008-4085.00101

Price, scarcity rent, and a modified <i>r</i> per cent rule for non‐renewable resources

2001· article· en· W2018933200 on OpenAlexaffvenue
John Livernois, Patrick Martin

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsScarcityEconomicsConfusionWelfare economicsMicroeconomics

Abstract

fetched live from OpenAlex

Since Hotelling's seminal paper on the optimal depletion of exhaustible resources, much has been published; yet confusion remains about whether scarcity rent and price increase or decrease as a resource is depleted when costs tend to rise with depletion. We show that Hotelling's fundamental results of rising scarcity rent and price paths are sustained and that the path of scarcity rent converges on the r per cent rule, provided the objective function is concave. Predictions of non‐monotonic or declining scarcity rent paths are due to implicit assumptions that lead to a non‐concave objective function. We identify the sources of these non‐concavities. JEL Classification: Q30, D90, C60 Prix, rente de rareté et une règle modifiée du r‐pourcent pour les ressources non renouvelables. Malgré la volumineuse littérature spécialisée qui a fleuri depuis qu'Hotelling a écrit son mémoire fondateur sur l'épuisement optimal des ressources renouvelables, une grande confusion règne toujours quand il faut établir si la rente de rareté et le prix augmentent ou chutent à proportion que la ressource s'épuise quand les coûts tendent à croître avec l'épuisement. Ce mémoire montre que les résultats fondamentaux obtenus par Hotelling quant aux sentiers de croissance de la rente de rareté et du prix tiennent toujours, et que le sentier de croissance de la rente de rareté converge vers la règle du r‐pourcent pourvu que la fonction objective soit concave. Les prédictions de sentiers de croissance non monotone ou de déclin de la rente de rareté présentées dans la littérature spécialisée sont attribuables à des postulats implicites qui engendrent une fonction objective non concave. Les auteurs identifient les sources de ces non‐concavités.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.205
GPT teacher head0.199
Teacher spread0.005 · 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.

Study designTheoretical or conceptual
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

Citations26
Published2001
Admission routes2
Has abstractyes

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