Evidence map›Paper›PMID 41096401›Full record

ArticleAnimals : an open access journal from MDPI2025

The Efficiency of Poultry Farms: A Dynamic Analysis Based on a Stochastic Frontier Approach and Panel Data.

Maria Bonaventura Forleo, Paola Di Renzo, Luca Romagnoli, Vincenzo Giaccio, Alfonso Scardera

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Maria Bonaventura ForleoDepartment of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy.ORCID 0000-0003-0344-5147
Paola Di RenzoDepartment of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy.
Luca RomagnoliDepartment of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy.ORCID 0000-0003-3243-1561
Vincenzo GiaccioDepartment of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy.ORCID 0000-0003-3826-8144
Alfonso ScarderaCouncil for Agricultural Research and Economics (CREA), Via G. Vico, 4, 86100 Campobasso, Italy.ORCID 0009-0000-4127-097X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

EU production is important for global poultry markets and is concentrated in a few countries, including Italy. The aim of this study is to investigate the technical efficiency of Italian poultry farms in 2019-2022, characterized by the COVID-19 pandemic and avian influenza, which occurred almost simultaneously and presented poultry farms with important economic challenges. In particular, this study aims to observe how efficiently poultry farms utilized their inputs with regards to controllable or managerial factors and exogenous shocks and factors beyond the firm's control. Data was retrieved from the RICA database, the Italian section of the EU Farm Accountancy Data Network. After a descriptive analysis, a stochastic frontier model was applied to the panel data to estimate production frontier and firm-specific inefficiency factors. Results reveal the relevance of certain cost categories (feed, water, fuel, and electricity) and their increase over the observed period. Current and capital costs have positive and significant impacts on the value of production. As regards the determinants of technical efficiency, a greater endowment of some inputs (labor and farm area) and the sizes of farms in terms of livestock units are correlated with an improvement in the technical efficiency of farms.

Indexed as

COVID-19FADNfinancial itemsfixed effectsItalypanel datapoultry sectorSFAtechnical inefficiency

Identifiers

PMID41096401
PMCPMC12523659

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.