A note on the induced effects of carbon prices and R&D subsidies in carbon-free technologies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it