Current Situation of Egyptian Cotton: Econometrics Study Using ARDL Model
Why this work is in the frame
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Bibliographic record
Abstract
The Egyptian cotton crop have experienced challenges in recent years from a drop in the quantity produced and exported, to a decrease in cultivated areas, this have affected the production quantity and value of exports. This study aims to bridge the research gap by exploring the nexus between cultivated area of cotton in Egypt, Relative profitability (cotton-clover/rice-clover), export quantity of cotton, the export prices of Egyptian cotton and the export prices of American cotton (Pima). In order to clarify the relationship between the variables studied and the cultivated area of cotton, the research use time series data from 1980 to 2016, using the Autoregressive Distributed Lag (ARDL) bound test to the find the co-integration between the variables after checking the stationarity in chosen variables with different unit root tests e.g. Augmented Dickey-Fuller (ADF) and the Phillips-Perron (PP). The results show, significant factors that influence the cultivated area of cotton include Relative profitability (cotton-clover/rice-clover), export quantity of cotton in long run term. Which underscores the need for government support in agriculture, in particular, cotton crop support. The increasing trend of cotton cost with declining revenue and decreasing in exports quantity is the main cause of decreased cultivated area of Egyptian cotton. Research recommends that support should be given to cotton farmers, in the form of agricultural equipment or training in good agricultural practices or set a price for cotton guaranteeing a decent profit margin for the farmers. The government (policy makers) should improve the productivity of cotton with the purpose of reducing the total costs and increasing the degree of competitiveness of the Egyptian cotton. Some effective policy measures may include but not limited to, farmer training programs and providing better extension services that will led to the capacity development of farmers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it