European Union non-tariff barriers to imports of African biofuels
Bibliographic record
Abstract
The introduction of EU mandates for biofuel use in the transport sector initially led to high expectations that African countries would benefit from biofuel exports to the EU. This market opportunity has not been realised, however, due to regulatory requirements for the production of biofuels that act as non-tariff barriers to the acceptance of African biofuels in the EU. This benefits producers of biofuel crops and processors in the EU by providing economic protection. In particular, the EU import regime fails to acknowledge the challenges faced by African (or other) developing countries in satisfying the requirements.Using a computable general equilibrium model for Malawi, we quantify the foregone potential benefits from biofuel production for exports to the EU arising from non-tariff barriers (NTBs) embedded in the sustainability criteria. Our results show that sugarcane-ethanol production under smallholder outgrower regimes would lead to both economic growth outcomes and rural development, whereas jatropha-biodiesel fails to increase rural incomes due to low profitability. While there is widespread agreement on the latter today, our study is the first to explore the failure of jatropha in Malawi in an economy-wide framework. The ethanol results, however, also hold if land clearing is forbidden, thereby preserving biodiversity as stipulated under the sustainability criteria in the EU Renewable Energy Directive. The EU NTBs embedded in the Renewable Energy Directive thus play a much larger role for countries in Sub-Sahara Africa than simply inhibiting investment opportunities and should be refashioned to lower the entry costs for developing countries.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".