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Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling

机译:积极的数学编程方法–文学和应用建模的最新进展

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This paper reviews and discusses the more recent literature and application of Positive Mathematical Programming in the context of agricultural supply models. Specifically, advances in the empirical foundation of parameter specifications as well as the economic rationalisation of PMP models – both criticized in earlier reviews – are investigated. Moreover, the paper provides an overview on a larger set of models with regular/repeated policy application that apply variants of PMP. Results show that most applications today avoid arbitrary parameter specifications and rely on exogenous information on supply responses to calibrate model parameters. However, only few approaches use multiple observations to estimate parameters, which is likely due to the still considerable technical challenges associated with it. Equally, we found only limited reflection on the behavioral or technological assumptions that could rationalise the PMP model structure while still keeping the model’s advantages.
机译:本文回顾并讨论了在农业供给模型中正数学规划的最新文献和应用。具体而言,研究了参数规范的经验基础以及PMP模型的经济合理性方面的进展-两者均在先前的评论中受到了批评。此外,本文还概述了使用PMP变体的,具有常规/重复策略应用程序的较大模型集。结果表明,当今的大多数应用都避免使用任意参数规格,而是依赖于供应响应上的外来信息来校准模型参数。但是,只有极少数的方法使用多个观测值来估计参数,这可能是由于与之相关的巨大技术挑战。同样,我们发现对行为或技术假设的反思有限,这些假设可以合理化PMP模型结构,同时仍保持模型的优势。

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