从分组数据中估计完整的迁移概率:开发全球人类内部迁移数据库的方法协议
Sigurd Dyrting1, Andrew Taylor1
1Northern Institute, Charles Darwin University, Darwin, Northern Territory, Australia.
PloS one
|December 10, 2024
概括
研究人员开发了一种新方法来估计内部移民的概率,创造了一个重要的数据库,以了解全球人口变化. 这推动了人口统计分析和未来人口预测.
科学领域:
- 人口统计学 人口统计学
- 人口研究 人口研究
- 量化社会科学 量化社会科学
背景情况:
- 内部移民是全球人口变化的主要驱动因素.
- 现有的人口统计框架缺乏全面的,标准化的历史移民数据.
- 估计迁移概率是具有挑战性的,因为数据限制,如年龄聚合和小样本大小.
研究的目的:
- 开发一种可靠的方法来推断年龄-原产地-目的地特定的迁移概率.
- 创建一个协调的,跨国的人类内部迁移数据库.
- 为研究和政策解决对可访问,高质量的内部移民数据的需求.
主要方法:
- 扩展P-TOPALS和P-spline方法,以平滑迁移概率.
- 对于分组年龄数据的应用,以处理不确定性和聚合.
- 使用IPUMS国际的微数据样本进行多国分析.
主要成果:
- 开发了一种用于估计完整年龄-原产地-目的地迁移概率的新方案.
- 与混合螺纹参数方法相比,拟议的方法显示出更高的准确性和可信性.
- 对于50多个国家,估计了完整的移民概率,形成了一个基础数据库.
结论:
- 开发的方法有效地从具有挑战性的数据集中推断出迁移概率.
- 人类内部迁移数据库为人口统计研究提供了至关重要的资源.
- 这项工作显著提高了分析和预测受内部移民影响的人口动态的能力.
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