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Models and muddles: comment on ‘Calibration of agricultural risk programming models using positive mathematical programming’

Petsakos Athanasios, Rozakis Stylianos

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URIhttp://purl.tuc.gr/dl/dias/541AA35C-9DC4-4F8F-BB20-1C683E7FCEC9-
Identifierhttps://doi.org/10.1111/1467-8489.12407-
Identifierhttps://onlinelibrary.wiley.com/doi/10.1111/1467-8489.12407-
Languageen-
Extent16 pagesen
TitleModels and muddles: comment on ‘Calibration of agricultural risk programming models using positive mathematical programming’en
CreatorPetsakos Athanasiosen
CreatorRozakis Stylianosen
CreatorΡοζακης Στυλιανοςel
PublisherWileyen
Content SummaryThere is an emerging strand in the agricultural economics literature which examines the calibration of risk programming models using the principles of Positive Mathematical Programming (PMP). In a recent contribution to this journal, Liu et al. (2020) compare three different PMP approaches and attempt to find the ‘most practical’ method for calibrating risk programming models to be used in policy analysis. In this article, we argue that the comparison design by Liu et al. (2020) is problematic, as it is based on inappropriate metrics and it ignores recent advancements in PMP. This word of caution intends to provide constructive criticism and aims at contributing to the use of risk programming models in policy analysis.en
Type of ItemΠαρατήρηση/Σχολιασμόςel
Type of ItemNoteen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2024-02-09-
Date of Publication2022-
SubjectAgricultural policyen
SubjectMathematical programmingen
SubjectRisk & uncertaintyen
Bibliographic CitationA. Petsakos and S. Rozakis, “Models and muddles: comment on ‘Calibration of agricultural risk programming models using positive mathematical programming’,” Aust. J. Agric. Resour. Econ., vol. 66, no. 3, pp. 713–728, July 2022, doi: 10.1111/1467-8489.12407.en

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