通过结合本地线性和标准方法预测经济增长
Marlon Fritz1, Sarah Forstinger2, Yuanhua Feng1
1Department of Economics, Paderborn University, Paderborn, Germany.
Journal of applied statistics
|May 30, 2025
概括
准确的宏观经济预测对于发展中经济体来说是具有挑战性的. 本研究引入了一种改进的局部线性趋势估计方法,增强GDP增长预测并减少预测差异.
科学领域:
- 经济学 经济学 经济学
- 计量经济学 计量经济学 计量经济学
- 时间序列分析时间序列分析
背景情况:
- 发展中国家的经济对全球增长至关重要.
- 宏观经济时间序列预测受到数据限制,波动性和非线性趋势的阻碍.
- 现有的方法往往难以应对发展中国家经济数据的复杂性.
研究的目的:
- 为宏观经济增长数据提出一个改进的预测方法.
- 为应对发展中国家经济预测时间序列的挑战.
- 提高GDP增长预测的准确性和可靠性.
主要方法:
- 数据驱动的局部线性趋势估计,使用扩展的代插件算法来进行内源带宽选择.
- 随机步行模型的扩展,以纳入局部线性,时间变化的漂移.
- 对六个发展中国家和两个发达经济体的GDP数据的应用,比较预测组合.
主要成果:
- 拟议的局部线性趋势估计方法提供了流的趋势估计,适应临时变化.
- 扩展随机步行模型与局部线性漂移改善了预测.
- 与传统方法相比,包括局部线性方法在内的预测组合显示出更高的准确性和更小的差异.
结论:
- 开发的预测方法为宏观经济时间序列分析提供了更复杂的方法,特别是对于发展中国家的经济体.
- 改进的趋势估计和模型扩展有助于更可靠的GDP增长预测.
- 研究结果表明,先进的预测技术对于应对发展中国家经济形势的复杂性至关重要.
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