Does Agricultural Productivity Actually Matter for Food Security in a Landlocked Sub‐Saharan African Country? The Case of Burkina Faso
Bibliographic record
Abstract
Abstract This paper makes use of a Computable General Equilibrium model to analyze the impact of two agricultural productivity trends on poor households’ food security in Burkina Faso: a negative trend that could arise from many different factors, including land degradation, climate change, and harmful agricultural practices; and a positive trend which may result from enhanced public investment in agriculture, notably in research and development, extension, irrigation, rural roads, rural electrification, and rural education. The results point to a high sensitivity of the poor's consumption to agricultural productivity as well as to stronger impacts on the urban poor than on the rural poor. The current situation is already characterized by severe food insecurity, such that a decline in agricultural productivity is likely to further plunge the urban poor into a deep food crisis. By contrast, positive agricultural productivity trends may help alleviate poverty and food insecurity. Agricultural productivity may indeed affect the poor's food consumption mainly through large changes in agricultural prices and real incomes. Cet article utilise un modèle d’Équilibre Général Calculable pour analyser l'impact des différentes tendances de la productivité agricole sur la sécurité alimentaire des ménages pauvres au Burkina Faso. D'une part, les tendances négatives peuvent résulter de plusieurs facteurs, y compris la dégradation des terres, le changement climatique, et les pratiques agricoles nuisibles. D'autre part, la tendance positive peut résulter de l'investissement public accru dans l'agriculture, notamment dans la recherche et développement, la vulgarisation, l'irrigation, les routes rurales, l′électrification rurale et l′éducation rurale. Les résultats montrent une sensibilité élevée de la consommation des pauvres à la productivité agricole, ainsi que des impacts plus forts sur les populations urbaines pauvres. La situation actuelle est déjà caractérisée par une insécurité alimentaire grave de sorte qu'une baisse de la productivité agricole est susceptible de plonger davantage les pauvres en milieu urbain dans une crise alimentaire profonde. En revanche, la tendance positive sur la productivité agricole peut contribuer à atténuer la pauvreté et l'insécurité alimentaire. La productivité agricole peut en effet affecter la consommation alimentaire des pauvres principalement par le biais de grandes variations des prix agricoles et des revenus réels.
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.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".