Transparency and Bidding Competition in International Wheat Trade
Bibliographic record
Abstract
One of the trade policy issues identified by U.S. interests, including grower groups, traders and policy makers, is price transparency. This has been a point of contention between the United States and Canada as well as other exporting countries with state trading enterprises (STEs). The transparency problem generally refers to the inability to observe terms of trade (including price, quality, credit, etc.)offered by STEs, and the potential strategic advantage this provides in bidding competition. A game theory model of import tendering is developed in this paper to examine the effects of information asymmetry among rivals. Several stylized examples are used to illustrate aspects of competition and to analyze effects on bidding strategies. Results indicate that: Less uncertainty among rivals reduces equilibrium bids and prices. Tenders with less transparency have the effect of increasing prices to buyers and payoffs to sellers. Increases in the number of rivals have the effect of reducing bids and mitigating the informational advantages of STEs. In all cases, less transparent sellers have an advantage in bidding relative to more transparent sellers. That advantage in our stylized case is in the area of $1–2/t. However, the advantage is reduced when there are many transparent rivals and in the case where transparent players act as agents for an STE.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".