农业风险的大规模正数学规划模型建模

I. Arribas, K. Louhichi, Ángel Perni, J. Vila, S. Gomez-y-Paloma
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引用次数: 2

摘要

数学规划已被广泛用于考虑农民决策中的风险。最近发展的正数学规划(PMP)重新提出了以更稳健和灵活的方式纳入风险的需要。大多数现有的pmmp风险模型已经在农场类型层面和非常有限的农场样本中进行了测试。本文提出并测试了一种新的方法,在一个大型模型中对个体农场水平的风险进行建模,称为共同农业政策分析的个体农场模型(IFM-CAP)。结果显示在包含和排除风险说明之间存在明显的权衡。尽管这两种选择都提供了非常接近的估计,但模拟结果表明,在模型中明确包含风险可以隔离风险对农民行为的影响。然而,该规范使估算所需的计算时间增加了三倍。
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Modelling agricultural risk in a large scale positive mathematical programming model
Mathematical programming has been extensively used to account for risk in farmers' decision making. The recent development of the positive mathematical programming (PMP) has renewed the need to incorporate risk in a more robust and flexible way. Most of the existing PMP-risk models have been tested at farm-type level and for a very limited sample of farms. This paper presents and tests a novel methodology for modelling risk at individual farm level in a large scale model, called individual farm model for common agricultural policy analysis (IFM-CAP). Results show a clear trade-off between including and excluding the risk specification. Albeit both alternatives provide very close estimates, simulation results shows that the explicit inclusion of risk in the model allows isolating risk effects on farmer behaviour. However, this specification increases three times the computation time required for estimation.
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来源期刊
CiteScore
0.60
自引率
0.00%
发文量
26
期刊介绍: IJCEE explores the intersection of economics, econometrics and computation. It investigates the application of recent computational techniques to all branches of economic modelling, both theoretical and empirical. IJCEE aims at an international and multidisciplinary standing, promoting rigorous quantitative examination of relevant economic issues and policy analyses. The journal''s research areas include computational economic modelling, computational econometrics and statistics and simulation methods. It is an internationally competitive, peer-reviewed journal dedicated to stimulating discussion at the forefront of economic and econometric research. Topics covered include: -Computational Economics: Computational techniques applied to economic problems and policies, Agent-based modelling, Control and game theory, General equilibrium models, Optimisation methods, Economic dynamics, Software development and implementation, -Econometrics: Applied micro and macro econometrics, Monte Carlo simulation, Robustness and sensitivity analysis, Bayesian econometrics, Time series analysis and forecasting techniques, Operational research methods with applications to economics, Software development and implementation.
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