SPATIAL PRICE TRANSMISSION AND ASYMMETRIC ADJUSTMENT: THE CASE OF LOCAL AND IMPORTED RICE IN TOGO
Bibliographic record
Abstract
In this paper, we have investigated the extent and the speed of adjustment of six domestic markets of imported rice and the local market of processed rice in Togo to rice prices change on the global market and how the local market of paddy and the imported rice markets respond respectively to prices change in the processed rice and on the central market of imported rice Lomé and test for asymmetry in the adjustment process using both standard and threshold cointegration tests. Symmetric and asymmetric error correction models with respect to the linear and threshold cointegration relationships between markets pairings are estimated to investigate short-run prices dynamics. Results indicate that prices for the global to local markets pairings are cointegrated with relatively low price transmission elasticities. Prices on the imported rice markets in Togo are also cointegrated (when Lomé is considered as the central market). Threshold cointegration tests reveal that in the long-run, the local market of paddy adjusts asymmetrically to prices change in the processed rice and there is asymmetric adjustment of domestic markets of Cinkassé and Lomé to prices change on the global market. Except for Amégnran market, the four other domestic markets of imported rice adjust also asymmetrically to rice prices change on the central market of Lomé. In the short-run, there is asymmetric adjustment only between the global market and the imported rice markets of Lomé and Cinkassé. Among imported rice prices dynamics in Togo, only Cinkassé market adjust asymmetrically to prices change on the central market of Lomé. The results imply that oligopolistic middlemen in rice marketing in Togo are more sensitive and react quickly when rice prices change on the global market tends to squeeze their margins than changes that stretch them.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".