Subsidies, Land Size and Agricultural Output
Bibliographic record
Abstract
In this paper we make a two-fold contribution. We first examine the impact of agricultural subsidies on Greece, using a detailed, micro-panel dataset for four years, 2008, 2010, 2012, and 2014. Our analysis is illuminating at least two aspects of subsidies: first, it suggests that an incentive scheme for promoting a larger farm size would have a probable positive effect on agricultural value-added; second, that subsidies today produce the larger impact on future value-added for the top two percentiles of the subsidy distribution. The adjacent contribution is the presentation of a new theoretical model on subsidies where we examine the impact of land size and taxes on them. We estimate the model’s hyperparameters, using Greek data from the FADN database. Our new theoretical results, combined with the empirical analysis on the first part, suggest that agricultural subsidies are of dubious economic value, in magnitude and effect, and distort the incentives for returns-to-scale and increased working hours in Greek agriculture
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".