Measuring market power and the efficiency of Alberta's restructured electricity market: An energy‐only market design
Bibliographic record
Abstract
Abstract We measure the degree of market power execution and inefficiencies in Alberta's restructured electricity market. Using hourly wholesale market data from 2008 to 2014, we find that firms exercise substantial market power in the highest demand hours with limited excess production capacity. The degree of market power execution in all other hours is low. Market inefficiencies are larger in the high demand hours and elevate production costs by 6.7%–19% above the competitive benchmark, with an average of 13%. This reflects 2.1% of the average market price across all hours. A recent regulatory policy clarifies that certain types of unilateral market power execution is permitted in Alberta. We find evidence that suggests that strategic behaviour changed after this announcement. Market power execution increased. We illustrate that the observed earnings are often sufficient to promote investment in natural gas based technologies. The rents from market power execution can exceed the estimated capacity costs for certain generation technologies. However, we demonstrate that the energy market profits in the presence of no market power execution are generally insufficient to promote investment in new generation capacity. This stresses the importance of considering both short‐run and long‐run electricity market performance measures.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".