Impacts of the Clean Air Act on the Power Sector from 1938-1994: Anticipation and Adaptation
Bibliographic record
Abstract
This study leverages newly digitized data on virtually every fossil-fuel power plant in the United States from 1938-1994 to provide the first assessment of the impacts of the 1970 Clean Air Act (CAA) that accounts for anticipation. The extended pre-regulation benchmark allows us to account for anticipatory behavior by electric utilities in the years leading up to the Act's passage. Guided by predictions from a simple theoretical framework, we use a difference-in-differences approach to examine the impacts of the Act's nonattainment designations on coal-fired power plants of different vintages. We find that nonattainment designation led to large and persistent decreases in plant productivity, which would be substantially underestimated without data from well before the passage of the 1970 CAA. The productivity losses were concentrated only among plants built before 1963. This timing aligns with the passage of the original 1963 CAA, which served as a signal of impending federal regulation. We provide empirical and historical evidence of anticipatory responses by utilities in the design and siting of plants that opened after 1963. Finally, we find that the aggregate productivity losses of the CAA borne by the power sector were substantially mitigated by the reallocation of output away from older less productive power plants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".