Carbon Pricing with an Output Subsidy under Imperfect Competition: The Case of Alberta's Restructured Electricity Market
Bibliographic record
Abstract
In this paper, we examine the use of carbon pricing and an output-based subsidy in a market with imperfect competition. We consider a carbon pricing policy in Alberta's electricity market as a case study. This policy consists of two phases. In the first phase, the carbon price is doubled with the output subsidy being based on a fraction of facility-level emission intensity. In the second phase, the carbon price will remain constant, while the output subsidy is altered to be uniform across assets and based on the emissions intensity of an efficient natural gas asset. Using a model of oligopoly competition, we simulate the short-run impacts of the two phases on electricity prices, emissions, and unit and firm-level profitability. We find that the mechanisms by which electricity prices and emissions change in response to carbon pricing differ depending on whether the market is perfectly competitive or oligopolistic. We demonstrate that regardless of market structure, changing the basis of the output subsidy has substantially larger effects than a doubling of the carbon price. The estimated effects of carbon pricing vary as the firms' generation portfolios change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".