An Economic Analysis of Western Canadian Grain Export Capacity
Bibliographic record
Abstract
Abstract Record grain supplies combined with insufficient grain export capacity in the 2013–14 and 2014–15 crop years resulted in depressed Western Canadian grain prices costing producers several billion dollars. The exceptional size of the crop and the harsh winter weather contributing to this costly event raise an important question as to whether additional investment in export capacity is warranted. This study systematically assesses the need for additional grain export capacity in Western Canada. Somewhat conservative grain production forecasts and rational expectations storage are used within a spatial mathematical programming model to simulate a competitive market, moving grain to export positions. We find in the absence of additional export capacity there will be increasingly frequent periods of costly congestion. A 10 million tonnes (Mt) (5 Mt) improvement in both rail and West Coast capacity implies $9.2 billion ($6.0 billion) of cost‐saving benefits for the producers over the 2016–25 period. While these estimates are sensitive to future realized production levels, their magnitude suggests that innovation to increase export capacity is economically important for grain producers in Western Canada. Des approvisionnements records de grains combinés à une capacité exportatrice insuffisante de ces derniers en 2013–14 et en 2014–15 ont engendré le bas prix du grain de l'Ouest canadien représentant une perte de milliards de dollars pour les producteurs. La production exceptionnelle et l'hiver particulièrement rude ont contribué à cet événement coûteux et soulèvent une question importante concernant le besoin pour des investissements additionnels en capacité exportatrice. Cette étude évalue systématiquement le besoin pour une capacité exportatrice accrue des céréales provenant de l'Ouest canadien. Les prévisions relativement prudentes de production de grains et l'anticipation rationnelle de stockage servent dans le cadre d'un modèle de programmation mathématique spatiale pour simuler un marché compétitif, transportant le grain vers les points d'exportation. Les trouvailles indiquent qu'en l'absence de capacité supplémentaire exportatrice, surviendront des périodes de plus en plus fréquentes de congestion coûteuse. Une amélioration de 10 Mt (5 Mt) à la capacité ferroviaire et de la Côte Ouest suppose des réductions de coûts à la hauteur de 9,2 milliards de dollars (6 milliards de dollars) pour les producteurs pour la période entre 2016 et 2025. Ces estimations étant liées à l'atteinte de futurs niveaux de production, leur importance suggère que l'innovation en vue d'accroître la capacité exportatrice s'avère économiquement essentielle pour les producteurs céréaliers de l'ouest du Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".