Reducing Greenhouse Gas Emissions in Transport: All in One Basket?
Bibliographic record
Abstract
Analysis after analysis has shown consistently that if policy-makers aiming to meet climate goals are looking for the most-efficient, least-distortionary way to target emissions growth, there is simply nothing better than abandoning all emissions regulations except for one: A straight, revenue-neutral carbon tax. Nothing works through more channels, at a lower cost. Alas, policy-makers are not always looking for the most-efficient, least-distortionary way to target emissions growth. That’s because many of those same analyses show that in order to reach emissions targets, the price on carbon would have to be so punitive as to be politically unbearable, raising the price of gasoline, for example, by about a dollar a litre. That leads politicians to mix in other policies that are less visible to the consumer but also less efficient, less effective and more expensive in abating carbon dioxide. The recently negotiated Pan-Canadian Framework on Clean Growth and Climate Change intends to follow that model, relying on a blend of different policies to help reach Canada’s Paris climate targets. But while the government seems therefore determined to rule out the possibility of a nothing-but-a-carbon-tax plan, it is possible, through the careful application of just the right sort of emission-reduction approaches, to reduce the costs of abatement in a key policy target — namely, road transportation — to a level that at least approaches the lower cost of a carbon tax. The government will likely consider several options in trying to reduce emissions from road transportation. Typical tools include requiring manufacturers to meet standards for new vehicles that mandate fuel economy and greenhouse gas emissions; gasoline taxes; taxes on emissions-intensive vehicles; subsidies for low-emission or zero-emission vehicles; and subsidies for public transit. Indications are that a low-carbon fuel standard (LCFS) will play a significant role in the Pan-Canadian Framework. Applied carefully, an LCFS combined with a mandate for automakers to sell more electric vehicles would be an appropriate policy for Canada to achieve meaningful emissions reductions at a tolerable cost, given other policy measures already committed to. Subsidies for electric vehicles, however, should be avoided as they turn out to be one of the least cost-effective policies to reduce emissions. Requiring car makers to sell more electric vehicles will lead to higher prices for standard internal-combustion vehicles as automakers are forced to spread the cost of the electric-vehicle mandate across their non-electric models. That in turn will lead to cheaper electric cars and pricier non-electric cars, making it likelier that consumers will gravitate in increasing numbers to electric cars, helping reduce emissions. Meanwhile, as the LFCS standard is raised, drivers of internal-combustion vehicles will face an even higher cost of filling up, again prompting more drivers to consider switching to electric vehicles. The combined effect — achievable at close to the cost of a carbon tax — will make it more expensive to drive a gasoline-powered car, similar to the effect of a carbon tax on drivers, but less visible and so less politically risky.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".