分数计算在经济增长建模中的应用:基于回归分析的方法
Yi Herng Cheow1, Kok Haur Ng2,3, Chang Phang1
1Department of Mathematics and Statistics, Universiti Tun Hussein Onn Malaysia, Pagoh, Johor, Malaysia.
Heliyon
|August 22, 2024
概括
本研究引入了一种分数级经济增长模型,用于预测国内生产总值 (GDP). 先进的分数模型在匹配经济数据和预测未来GDP趋势方面显著优于传统的整数模型.
科学领域:
- 计量经济学 计量经济学
- 数学经济学数学经济学
- 时间序列分析时间序列分析
背景情况:
- 经济增长建模对于政策制定至关重要.
- 传统模型可能无法捕捉复杂的动态.
- 分数计算为经济现象建模提供了一种新的方法.
研究的目的:
- 开发和验证国内生产总值 (GDP) 的小数级经济增长模型.
- 为了比较分数顺序模型与传统整数顺序模型的性能.
- 用马来西亚GDP数据评估拟议模型的预测准确性.
主要方法:
- 为GDP开发一个分数次序微分方程模型.
- 使用马来西亚GDP数据 (1956-2018) 的实证应用.
- 与整数顺序的多重线性回归模型进行比较,使用AIC,R平方,RMSE和MAE等标准.
主要成果:
- 与所有基准模型相比,减少的分数顺序模型 (6个变量) 显示出优异的样本适应性.
- 分数顺序模型提供了更准确的样本外预测.
- 迪博德-马里亚诺测试证实了分数顺序模型在预测方面具有显著的优势.
结论:
- 分数顺序建模为经济增长分析提供了更强大的框架.
- 拟议的模型提高了GDP预测的准确性.
- 政策决策可以从分数模型中得出的更可靠的经济预测中受益.
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