This study proposes an approach for predicting the impacts of scenarios on food security and demonstrates its application in a case study. The approach involves two main steps: (1) scenario definition, in which the end user specifies the assumptions and impacts of the scenario using a scenario template, and (2) scenario evaluation, in which a Vector Autoregression (VAR) model is used in combination with Monte Carlo simulation to generate predictions for the impacts of the scenario based on the defined assumptions and impacts. The case study is based on a proprietary time series food security database created using data from the Food and Agriculture Organization of the United Nations (FAOSTAT), the World Bank, and the United States Department of Agriculture (USDA). The database contains a wide range of data on various indicators of food security, such as production, trade, consumption, prices, availability, access, and nutritional value. The results show that the proposed approach can be used to predict the potential impacts of scenarios on food security and that the proprietary time series food security database can be used to support this approach. The study provides specific insights on how this approach can inform decision-making processes related to food security such as food prices and availability in the case study region.

翻译：这项研究提出一种预测粮食安全设想方案影响的办法,并在案例研究中展示其应用情况。该办法涉及两个主要步骤:(1) 设想方案定义,其中最终用户使用设想方案模板具体说明设想方案的假设和影响;(2) 设想评价,其中与蒙特卡洛模拟结合使用矢量自动递减模型,以预测基于既定假设和影响的设想方案影响;该案例研究以利用联合国粮食及农业组织(粮农组织统计处)、世界银行和美国农业部(美国农业部)的数据建立的专有时间序列粮食安全数据库为基础。该数据库载有一系列关于各种粮食安全指标的数据,如生产、贸易、消费、价格、供应、获取机会和营养价值。结果显示,拟议办法可用于预测粮食安全设想方案的潜在影响,并可利用专有时间序列粮食安全数据库支持这一办法。该研究具体了解了这一办法如何为区域粮食价格和供应情况等与粮食安全有关的决策进程提供信息。