Income and Price Effect on Bilateral Trade and Consumption Through Expenditure Channel: A Case of Chickpea
Bibliographic record
Abstract
Income and price affect chickpea trade expenditure and consumption expenditure share respectively. An empirical model was estimated to examine the trade effect through the expenditure channel using Almost Ideal Demand System and thus considering non-homotheticity in preferences. The results of the analysis indicated that global chickpea trade has increased from 100000 metric tons in 1988 to about 2.5 million metric tons in 2015. Between the same period consumption and production of chickpea had an increasing trend. USA and Canada had become part of the top 10 chickpea producers by 2015 signifying the increasing demand of chickpea in western countries. Factors that affected relative chickpea trade to importers income were relative market size of the exporter, bilateral distance and contiguous borders. Also, a percentage increase in the adjusted mean income of chickpea consuming country will lead to 94% decrease in the consumption of chickpea when country pair effects are considered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".