Welfare Effects of Water Variability in Agriculture. Insights from a Multimarket Model
Bibliographic record
Abstract
The purpose of this research is to assess the welfare effects of climate change on the Chilean agricultural sector, with special focus on changes in water availability. The productive impacts of climate change on the agricultural sector are well analyzed at both a global and national level. There is, however, a lack of evidence about the aggregated impacts, considering both demand and supply. This study tries to fill this gap by using a multimarket model, specifically designed for the Chilean agricultural sector. According to our results, changes in water availability will have modest welfare impacts, with an average decrease of total surplus of 4.3%, minor price changes (around −1%), and no significant impacts on total agricultural land. Despite the small aggregated effects, it is expected that climate change will have uneven consequences across regions and activities. For instance, even though the southern zone (zone 3) shows the smallest income changes −14% (average), the impacts within the zone range from 1% to 52% decrease in agricultural net income. This situation suggests large distributional consequences of climate change for the Chilean agricultural sector.
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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 | 0.002 | 0.004 |
| 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".