Market structure and technology adoption in renewable energy
Bibliographic record
Abstract
We study the effect of market structure on technology adoption in the U.S. solar and wind power industries. We compare adoption across two market types: restructured markets, which are designed to promote competition, and regulated markets, which are dominated by regulated monopolists. Solar projects in restructured markets are 32 percent less likely to adopt frontier technology. We also find negative effects of restructuring on adoption for wind projects. We provide evidence that this negative relationship between competition and technology adoption is explained by differences in financing costs across the two market types. • We find that solar and wind projects located in restructured markets, which are designed to promote competition, are less likely to adopt frontier technology than comparable projects in regulated markets. • Solar projects in restructured markets are 32 percent less likely to adopt axis-tracking panels and wind projects use 2.4 meters smaller turbines than comparable projects in regulated markets. • We find evidence that higher financing costs in restructured markets explain lower technology adoption in these markets. • Our results suggest that reducing financing costs in restructured markets can help promote technology adoption by renewable projects.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".