Palm Oil Import Demand in North America Countries
Bibliographic record
Abstract
Palm oil is one of the agricultural commodities grown in world trade. North America is one of the regions with high import demand, so that the region can be observed as an export destination. This study aimed to examine the palm import demand in three selected North American Countries (United States of America (USA), Canada and Mexico) and its determinants. Autoregressive Distributive Lags (ARDL) was applied in this study between 1990 and 2017. The results indicate that the demand for palm oil in North American countries has increased. However, the import growth and shares have fluctuated relatively. GDP, GDP Indonesia, GDP Malaysia world palm oil prices, soybean oil prices, and biodiesel production significantly affect palm oil imports in the USA in the long and short-run. The GDP and GDP of Indonesia are the factors that influence palm oil import in Canada and Mexico in the long run. However, we found the impact of GDP Malaysia and GDP Indonesia in Canada in the short-run. Moreover, Indonesia's GDP and GDP significantly influenced palm oil import in Mexico. This research implies that oil palm exporting countries need to consider these factors, especially GDP, before expanding their market to North American countries as one of the biggest palm oil markets in the global world. Keywords: business analytics, biofuel, gdp, import, palm oil, price, north america
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".