Price Incentives and Supply Response in Cocoa -A Case of Border Regions of Ghana
Bibliographic record
Abstract
Smuggling of cocoa between Ghana and its neighbouring producing countries such as Cote d’Ivoire and Togo is a frequent occurrence often to the advantage of the country posting higher producer price. Ghana is a net loser with regards to the smuggling of cocoa given relatively lower real producer price compared to its counterparts in production. Additionally, the close geographical location of key producing regions to the border lends support to such activities. This study investigates the supply response of cocoa in producing region such as Western North, Western South and Brong-Ahafo with proximity to Cote d’Ivoire and Volta which shares borders with Togo using data from 1981 to 2017. The study further estimates the volume of cocoa crop lost from these regions to the country’s neighbours from 2000 to 2017. In the findings, relative price differences significantly impact the volumes of reported crop for the country with 1% higher price abroad driving down production volumes in Western North, South and Brong-Ahafo by 0.53%, 0.48%, and 0.11% respectively. In 2013/14 crop year the country lost averagely 25,494 MT and 21,883 MT due to smuggling out of Western North and South, moderating to 1,559 and 1,358 in 2016/17. The Volta region consistently records outflow in each crop year except for 1999/2000, with peak losses in 2010/11 of 2,160 MT moderating to 1,197 in 2016/17. Net gains into the country from cocoa smuggling spanning from 1999/2000 to 2016/17 is averagely 23,534 MT and 15,336MT into Western North and South. However cocoa smuggling for both Ghana and its neighbours is on the descent in recent years as price disparities reduce. Intensifying the collaboration between Ghana and its close counterparts to minimize real crop price differences will effectively curtail the menace and the negative fallout of this to each country.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".