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Record W4213335749 · doi:10.5547/01956574.43.5.sdeb

Reciprocal Dumping under Dichotomous Regulation

2022· article· en· W4213335749 on OpenAlexaff
Sébastien Debia, Georges Zaccour

Bibliographic record

VenueThe Energy Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsInefficiencyEconomicsMicroeconomicsSubgame perfect equilibriumNash equilibriumScarcityOutcome (game theory)Pareto principleSubgameIndustrial organizationBest response

Abstract

fetched live from OpenAlex

An essential ingredient to net-zero-emissions policies is to regionally integrate electricity markets. But electricity cross-border trades are often assessed as inefficient. We explain this inefficiency by the presence of a dichotomous regulation: producers are highly regulated with regard to their local activities, but weakly regulated when it comes to their exports. Such a dichotomy in regulation can be generalized to every economic sector, with varying intensity. We develop a generic 2-player 2-stage game theoretical framework where producers anticipate the impact of their exports on the clearing of regulated local markets. We characterize the subgame-perfect Nash equilibrium of the game as a function of the relative price-elasticity between markets. Overall, dichotomous regulation leads producers to over-export in order to create scarcity in their home market. Hence, despite that local markets clear efficiently, the global equilibrium is inefficient. When the two jurisdictions are relatively symmetric, the equilibrium is Pareto-dominated by the first-best outcome. These results call for better coordination between regulators across different jurisdictions.

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)0.000
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: none
Teacher disagreement score0.962
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.174
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2022
Admission routes1
Has abstractyes

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