Co-integration Test: An Application to Selected Sorghum Markets in Sudan
Bibliographic record
Abstract
An attempt was made in the study to understand the nature of the market integration. The study was based mainly on monthly wholesale price of sorghum in four market locations; namely Khartoum, Elobied, Gdarif and Damazin. Sorghum wholesale price series was used for the period from January 2012 to December 2016. Unit root test, Johnson co-integration test and Error Correction model were used to disclose stationary series, the long run relationship and short run relationship between these markets, respectively. The result showed that, long run relationship was indicated between all pairs of markets, except between Khartoum and Elobied market (consumption or deficit market). Long run equilibrium indicated adjustment to surplus markets (Gadarief and Damazin). This result may be interpreted by the fact that these markets are connected by good communication and transportation. From ECM model, Wholesale sorghum prices in all markets (higher price) quickly fall back towards Gadarif market whereas Gadarif adjusts back to Khartoum. Also, higher wholesale prices in Damazin quickly fall back towards all markets. There is short run causality running from: Gadarif and Damazin to Khartoum, Gadarif to Elobied and Khartoum to Damazin market. Long run equilibrium indicated adjustment to surplus markets (Gadarief and Damazin).This result may be reflected to good communication and transportation between the markets.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".