关于在国际期货模型中使预测外源的协议
José Solórzano1, Barry B Hughes1, Mohammod T Irfan1
1University of Denver, Pardee Institute, Denver, CO 80210, USA.
STAR protocols
|December 11, 2024
概括
本研究介绍了将外部数据集成到国际期货 (IFs) 模型中的协议. 这通过结合社会经济途径,提高了对全球发展和环境挑战的预测.
科学领域:
- 综合评估建模 综合评估建模
- 全球变化科学科学 全球变化科学
- 社会经济预测的预测.
背景情况:
- 应对行星和发展挑战的有效政策战略需要了解未来的动态.
- 国际期货 (IFs) 模型是探索长期全球期货的工具.
- 纳入各种数据,如社会经济路径,对于强大的建模至关重要.
研究的目的:
- 介绍一个协议,以添加外源序列的IFs模型数据库.
- 为了实现关键变量的集成,如共享社会经济路径 (SSPs).
- 在投资基金框架内促进更全面的未来场景分析.
主要方法:
- 安装IFs建模软件和SQLiteStudio. 的安装.
- 数据库的探索和对IF数据结构的理解.
- 进口外源数据序列的逐步指南.
- 用新数据运行IF模型并提取结果的程序.
主要成果:
- 用外部数据增强IF模型的记录协议.
- 证明能够在投资基金中引入和利用共享社会经济途径 (SSP).
- 提高了应对复杂全球挑战的场景分析能力.
结论:
- 提出的协议为扩展IF模型分析能力提供了一种实用方法.
- 整合外部数据增强了该模型对政策相关预测的实用性.
- 这种方法支持为可持续发展和环境管理做出更明智的决策.
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