A note on the induced effects of carbon prices and R&D subsidies in carbon-free technologies
Bibliographic record
Abstract
This note focuses on two types of distortions that can prevent the market from functioning optimally. The first results from CO2 emissions generated by the consumption of fossil fuels. The second is related to R&D activities, since innovators are generally incapable of securing the totality of the benefits created by their innovations. Two types of instruments can be used in order to correct for these externalities: a carbon price on the one hand, and research subsidies on the other hand. These instruments tend to interact in a complex manner when the economy is in equilibrium. The paper first recalls the basic economic principles which govern the correction of environmental and research externalities and describes four endogenous growth models that provide information about the interaction between related public policies. Although they differ in the ways how innovation, production, the climate and damages have been taken into account, all of them reach the following consensual result: the beneficial effect of the carbon price is reinforced by the simultaneous implementation of R&D subsidies in favour of carbon-free energies and vice-versa. Furthermore, early action is necessary in order to reduce the social costs of climate change mitigation.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".