The Evaluation of Asymmetry in Price Transmission and Market Power in Iran Sugar Production Industry
Bibliographic record
Abstract
Asymmetric price transmission in production institutes can be a reason for the existence of market power. In this regard, by the help of an integrative sample, this study simultaneously analyzes the price transmission between production markets and retails markets of sugar in the presence of the parameter of market power. For this purpose, the seasonal data of the required variables during the years 1995-2013 was used. In order to meet the study objectives, the behavior of the retails price of sugar was evaluated in the framework of two regimes of different changes which were compatible with nature of presenting agricultural products that are widely supplied in the harvest seasons. Also, the inverse elasticity of product supply was used as the parameter of market power. Considering the more probable regime (second regime), it was realized that the marketing elements at the wholesale level intend to price transmission increase more intensively than price decrease to the retail trades level. In this regime, asymmetric price transmission and existence of market power were approved. In the first regime, market power was much more and considering the fact that it has the 30% probability of happening, it has more compatibility with the seasons when supply is abundant. In these seasons, sugar production and refining units increase the market power and create a monopsony market in buying the inputs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".