预测洛伦茨曲线的时间序列:对方差异的单向功能分析
1Department of Actuarial Studies and Business Analytics, Macquarie University, Sydney, NSW, Australia.
Journal of applied statistics
|December 4, 2025
概括
本研究引入了使用函数式方差分析对洛伦茨曲线的新预测方法. 这种方法增强了对收入和财富分配和不平等的分析.
科学领域:
- 经济学 经济学 经济学
- 统计 统计 统计 统计
- 计量经济学 计量经济学
背景情况:
- 洛伦茨曲线对于分析收入和财富分配以及不平等至关重要.
- 预测洛伦茨曲线的现有方法可能缺乏解释性或准确性.
研究的目的:
- 开发和评估一种用于洛伦兹曲线时间序列的新预测方法.
- 通过统计建模,加强对收入和财富不平等的分析.
主要方法:
- 使用单向函数式方差分析 (fANOVA) 来分解洛伦兹曲线的时间序列.
- 开发了一种基于fANOVA的方法来生成一步前的点和间隔预测.
- 将洛伦茨曲线数据分解为功能大效应,功能行效应和余函数,以实现可解释性.
主要成果:
- 方差方法的功能分析提供了可解释的洛伦兹曲线变化的分解.
- 预测准确性被评估并与三种非功能预测方法进行比较.
- 该研究使用意大利家庭收入和财富数据进行实证评估.
结论:
- 方差的功能分析为预测洛伦茨曲线提供了一个有前途的方法.
- 拟议的方法增强了对收入和财富分配动态的理解和预测.
- 这种技术可以应用于国家和区域一级进行不平等分析.
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