Working Paper Series FSWP2005-01 STATE TRADING ENTERPRISES IN A DIFFERENTIATED PRODUCT ENVIRONMENT: THE CASE OF GLOBAL MALTING BARLEY MARKETS
Bibliographic record
Abstract
The lack of transparency in the pricing and operational activities of state trading enterprises (STEs) has caused WTO members to express concern that certain countries ’ STEs might circumvent Uruguay Round commitments on export subsidies, domestic support, or market access. The purpose of this study is to examine the market structure of the differentiated world malting barley market in which two STEs (the Canadian Wheat Board and Australian Barley Board) maintain jointly a very large share of the export market. In particular, this study focuses on the exclusive procuring and pricing policies used by both STEs to test if these intra-country mechanisms can generate leadership and shift rent from other exporting countries. A conceptual and empirical framework is also provided to test if STEs set their initial payments at optimal levels. Four key results are forthcoming from this research. First, we found strong support that the global malting barley market operates in a quantity setting oligopolistic structure. Second, both STEs and other exporting countries were in Cournot competition, and thus held the potential to exercise rentshifting behavior using their initial payment structures. Third, while some distortionary impacts from the STE prepayment systems were possible, we did not find evidence that it was a tool either STE employed. Empirical results from the precommitment stage show that both STEs did not set their initial payments low enough to maximize their profits. Fourth, It appears that the strong anecdotal and statistical evidence of
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.005 |
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".