Macroeconomic and Distributional Impacts of Jatropha Based Biodiesel in Mali
Bibliographic record
Abstract
Mali has introduced a program to produce biodiesel using jatropha, a shrub widely available throughout the country. The aim of the program is to partially substitute diesel, which is entirely supplied through imports, with domestically produced biodiesel. In this paper, we use a computable general equilibrium (CGE) model and a microsimulation model to analyze macroeconomic and distributional impact of a hypothetical expansion of jatropha based biodiesel industry in Mali. We find that the expansion of biodiesel industry (i.e., both jatropha farming and oil conversion), would increase GDP, though slightly, if idle lands are utilized for jatropha cultivation. However, the expansion of jatropha would cause slight loss in GDP if the existing agriculture land is used for jatropha cultivation. The distributional results are slightly different. We find that rural poverty would decrease no matter whether idle lands or existing agricultural lands are used for jatropha plantation, although the percentage reductions in rural poverty are higher in the former compared to the latter case. Our results indicate that if governments plan to promote jatropha biodiesel they should not allow jatropha to compete with food staples on the existing land. Policies should be targeted to utilize the idle lands which have not been used for any productive use.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".