A Water-Embedded CGE Approach to Economic and Welfare Effects of Agricultural Water Transfer
Bibliographic record
Abstract
Interbasin water transfer projects which are considered as a solution to the water crisis have different economic and environmental implications for regions. This study investigated the economic and welfare effects of agriculture water transfer to Qazvin Province in Iran using a water-embedded computable general equilibrium (CGE) model. The model was calibrated and solved numerically using a water-embededd social accounting matrix (WSAM). A scenario transferring 290 million m3 of water was simulated. The results indicate that this policy had a positive effect on the region’s welfare and increased the gross production of the agricultural sector by 14.4%, which led to an increase in the production inputs and added value of the agricultural sector. With the increase in gross production, the exports of the agricultural sector increased and the need for imports decreased. With the change of variables in the agricultural sector, other economic sectors were affected directly and indirectly. The economic variables of Qazvin province—gross domestic product (GDP), capital formation, exports of agricultural products, industries, and service efficiency—had a positive response to the policy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".