Élasticités et effet rebond des véhicules légers au Canada
Bibliographic record
Abstract
Although reducing greenhouse gas emissions is an imperative, environmental policies can run into two pitfalls: the rebound effect and inelastic demand for gasoline. If a vehicle is more fuel-efficient but is used more often, this reduces the expected energy savings (rebound effect). Similarly, increasing the price of gasoline via carbon pricing has little effect on demand if it is not very sensitive (inelastic) to price. To determine the value of these parameters for light vehicles in Canada, I use data for the ten provinces between 2000 and 2019 to estimate a simultaneous three-equation model of aggregate demand for kilometers traveled, vehicle fleet and fuel efficiency. While the rebound effect is worth 9 % in the short term and 30 % in the long term, gasoline demand is found to be inelastic in both cases. These values are broadly consistent with those found in the literature. A rise in gasoline prices therefore reduces purchasing power rather than consumption. Similarly, in the long term, a 10 % increase in fuel efficiency would increase distance travelled by 3 %.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".