Factors Influencing Export of Soya Bean Oil from India: A Panel Gravity Model Analysis
Bibliographic record
Abstract
Soya bean, the ‘miracle bean’, belongs to the family Leguminoceae, subfamily Papilionoidea. Soya bean oil is one of the most widely consumed cooking oils and is rich in linolenic acid. In the past 20 years the export of soya bean oil from India was mainly focused on Bhutan, Jordan, Canada, Singapore and Myanmar. The data was collected from 2002-03 to2021-22. The sources of data were Food and Agriculture Organization Statistics (FAOSTAT), Directorate General of Commercial Intelligence and Statistics (DGCIS), International Monetary Fund (IMF), Statista and Trade map. The panel data was estimated by the Feasible Generalized Least Squares (FGLS) method. For soya bean oil the per capita GDP of India's trading partners, distance, trade openness, and exchange rates are the most significant factors affecting bilateral trade. While partner countries' prosperity and liberal trade policies boost trade, greater distances and unfavorable exchange rates hinder it. India's GDP and domestic inflation show minimal impact on trade flows. Wooldridge test indicated no first-order auto-correlation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".