An economic analysis of production efficiency: Evidence from Irish farms
Bibliographic record
Abstract
Abstract The objective of this paper is to investigate the economics of production efficiency of dairy farms, with a specific focus on the role of agricultural policy. Our analysis is based on a representative sample of Irish dairy farms, ranging from 2000 to 2018, which includes a period of major change in EU dairy policy. Based on a multi‐input multi‐output production system, we first estimate technical, allocative, scale and scope efficiencies. We find significant heterogeneity in technical and allocative efficiencies, which change over time. We also calculate shadow prices of milk quota, which suggest that milk quotas restricted many farmers and limited their ability to produce milk. Finally, we explore determinants of technical, allocative, scale and overall inefficiencies using random panel‐data censored regression. We find that subsidies are positively associated with farm efficiency, but the effects vary over distinct quota abolition periods. Overall, our empirical findings indicate that agricultural policy had important effects on the managerial effectiveness of farmers.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".