The Tricky Art of Measuring Fossil Fuel Subsidies: A Critique of Existing Studies
Bibliographic record
Abstract
Fossil fuel subsidies are of enormous import to policy-makers and public opinion, making it critical to properly define them. However, traditional methodologies tend to place subsidies in the realm of tax expenditure analysis, presenting a flawed picture. A recent report on government subsidies to the Canadian energy sector prepared for the International Institute for Sustainable Development exemplifies this flawed approach along several dimensions: it is not based on a robust underlying economic framework, it fails to account for complex interactions between tax and royalty systems in existing fiscal policy, and it uses a definition of subsidies that was created for a different purpose. The authors of this paper propose an alternative “economic view”, based on economic rents, which provides a neutral benchmark against which subsidies, royalties and other energy-focused fiscal measures can be measured. Using marginal effective tax rate (METR) analysis, the authors show that it is possible to obtain a more accurate picture of energy subsidies and their impact on resource allocation and economic activity. This improved schema will ideally allow governments to better understand subsidies and devise sound policies, leading to less waste and distorted investment choices.
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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 | 0.065 | 0.198 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.017 |
| Science and technology studies | 0.003 | 0.031 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".