Essays on the Impacts of Environmental Regulation
Bibliographic record
Abstract
This dissertation investigates the impacts of environmental regulation. The first essay studies the introduction of a carbon tax in British Columbia, and focuses on outcomes in retail gasoline markets. First, I use a theoretical model to describe the short- and long-run effects of the tax in an oligopolistic environment. Second, I use panel data on retail prices, retail margins, and the number of gasoline stations to estimate the causal impact of the tax increase on each of these variables in both the short run and long run. The empirical results are consistent with theory, and suggest that incomplete pass-through of the tax caused exit resulting in even greater long-run price increases. The second essay examines the link between air quality regulation and emissions leakage in Canada. The results show that variation in the stringency of Canadian air quality regulation lead to emissions leakage, which can be explained by policy-induced changes in the distribution of firms' marginal production cost. The last essay studies the affect of air quality regulation on manufacturing plants' productivity. Results form this essay demonstrate that greater stringency reduces productivity by pulling resources away from production, towards regulatory compliance and abatement of emissions. But, the incentive to upgrade productivity is greater for initially-high-productivity plants, leading to productivity gains for these plants.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".