Customs Revenue in the Renewable Energy Sector: Evidence from South Africa
Bibliographic record
Abstract
This report assesses the effects of customs revenues in the renewable energy industry in South Africa. After ESKOM (State-owned enterprise) presented the firm’s biggest loss of R9.7 ($0.6) billion in August 2009, several applications for higher tariffs were performed over the years. South Africa has been going through an energy crisis, with more loadshedding expected in 2024, which is predicted to hamper GDP development. Indeed, the country’s economy has been adversely disturbed by the COVID-19 pandemic, and its improvement path is at this instant stifled by incessant power cuts. There is no doubt that this energy crisis will continue for a while in the future, and it is unlikely to get better soon. This policy report provides a customs revenue analysis of the market participants or entities in the renewable energy industry. This study adopted a pragmatic research methodology and found that the government could propose to the National Treasury the scrapping of value-added tax (VAT) and Customs Duties on the importation of solar panels and parts in order to help reduce the cost of purchasing for both businesses and households.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".