城市化与畜产品生产预测：健康与环境风险调整法

集约化农业生产所带来的环境影响和健康危害已经使人们逐渐认识到建立可持续农业发展途径的必要性。随着人们收入的增长,城市化的迅速发展成为消费模式转变的最为显见的驱动力。揭示在考虑到可持续发展的风险和不确定性的情况下对未来农业生产规划的预测,和在决策过程中恰当的风险指标,而这些内容的引入将极可能改变与畜产品设备配置和集约化程度相关的未来政策。以中国为例,研究主要目标为:(1)阐明如何将风险指标引入到决策过程中从而避免健康风险带来的负面结果;(2)阐明如何在农业生产规划中明确风险和不确定性,以达到可持续农业发展。     

城市化与畜产品生产预测:健康与环境风险调整法

集约化农业生产所带来的环境影响和健康危害已经使人们逐渐认识到建立可持续农业发展途径的必要性.随着人们收入的增长,城市化的迅速发展成为消费模式转变的最为显见的驱动力.揭示在考虑到可持续发展的风险和不确定性的情况下对未来农业生产规划的预测,和在决策过程中恰当的风险指标,而这些内容的引入将极可能改变与畜产品设备配置和集约化程度相关的未来政策.以中国为例,研究主要目标为:(1)阐明如何将风险指标引入到决策过程中从而避免健康风险带来的负面结果;(2)阐明如何在农业生产规划中明确风险和不确定性,以达到可持续农业发展.     

Integrated Management of Land Use Systems under Systemic Risks and Security Targets: A Stochastic Global Biosphere Management Model

Interdependencies among land use systems resemble a complex network connected through demand–supply relationships. Disruption of this network may catalyse systemic risks affecting food, energy, water and environmental security (FEWES) worldwide. We describe the conceptual development, expansion and practical application of a stochastic version of the Global Biosphere Management Model (GLOBIOM), used to assess competition for land use between agriculture, bioenergy and forestry at regional and global scales. In the stochastic version of the model, systemic risks of various kinds are explicitly covered and can be analysed and mitigated in all their interactions. While traditional deterministic scenario analysis produces sets of scenario‐dependent outcomes, stochastic GLOBIOM explicitly derives robust outcomes that leave the systems better‐off, independently of which scenario applies. Stochastic GLOBIOM is formulated as a stochastic optimisation model that is critical for evaluating portfolios of robust interdependent decisions: ex‐ante strategic decisions (production allocation, storage capacities) and ex‐post adaptive (demand, trading, storage control) decisions. As an example, the model is applied to the question of optimal storage facilities, as buffers for production shortfalls, to meet regional and global FEWES requirements when extreme events occur. Expected shortfalls and storage capacities have a close relationship with Value‐at‐Risk (VaR) and Conditional Value‐at‐Risk (CVaR) risk measures. A Value of Stochastic Solutions is calculated to illustrate the benefits of the stochastic over the deterministic model approach.     

On Long-term Forecasting of Social Security: A Robustness Analysis

In this paper we present a macro-economic demographic growth modelhaving a special focus on social security. It is designed to study the variability of responses of the system in presence of risks and uncertainties. Here we analyze the robustness of the model towards uncertainties in parameterspecifications, introduced by ARCH-M models with the incorporation ofintervention processes. The parameters varied are labor force participationrates (one of the key sources of uncertainty in the social security policydebate), and the parameters of the production function (the key source ofuncertainty in any long-run economic analysis). The sensitivity analysisfocuses on two variables: assets of the private pension system and thebalance of the public `Pay As You Go' pension system. Special attentionis given to convergence properties of the macro-economic model.