Asymmetric spot‐futures prices adjustments in Quebec grain markets
Bibliographic record
Abstract
Abstract Asymmetric price transmission has been the subject of many studies in agricultural economics, but few has been said on Quebec grain market. This study uses threshold cointegration models to examine the dynamic relationship between Quebec spot and futures prices. Estimation results with daily, weekly, and monthly data from September 1994 to May 2022 are three‐fold. First, the main point to keep from cointegration tests is that futures prices and Quebec local grain prices are integrated but estimations with daily data are consistent to highlight a nonlinear long‐run relationship. Second, results indicate overall positive asymmetric for daily and weekly prices transmissions from futures to spot market. Third, the positive asymmetric prices transmissions shed light on the oligopoly structure of Quebec grain market and inefficiencies in the pricing mechanism which favor local grain sellers. Results with different data frequencies show that aggregated monthly prices data compared to more disaggregated data such as daily and weekly prices may lead to different results. Results imply that policymakers and market stakeholders could facilitate increased grain market competition. Grain users like Quebec hog producers need to better understand additional tools for their management of price risk like futures market and real time prices movement monitoring.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".