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国家人口增长率,其组成部分和次国家贡献:研究笔记
Vladimir Canudas-Romo1, Tianyu Shen1, Collin F Payne1,2
1School of Demography, Research School of Social Sciences, College of Arts and Social Sciences, Australian National University, Acton, Australian Capital Territory, Australia.
Demography
|May 23, 2024
概括
这项研究适应了变量-r模型,以使用更短的人口统计数据系列分析人口增长. 较短的系列准确地反映了历史的生育率,死亡率和移民趋势,影响了人口动态.
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:
- 人口增长是由生育率,死亡率和移民驱动的.
- 传统分析需要超过100年的人口统计数据,限制范围.
- 了解对增长的历史贡献对政策至关重要.
研究的目的:
- 调整变量-r模型以使用更短的人口数据系列来分析人口增长.
- 评估历史生育率,死亡率和移民对人口增长率的影响.
- 扩展分析国家人口增长的地方贡献的模型.
主要方法:
- 适应变量-r模型用于人口分析.
- 使用较短的历史人口统计数据系列 (例如25年).
- 将特定年龄的增长率分解为变化的组成部分.
主要成果:
- 短历史序列 (25年) 提供年龄特定的增长率,与较长的序列密切匹配.
- 缩短的特定年龄增长率主要取决于出生率,死亡率在年龄较大时显著.
- 亚国家级分析揭示了增长成分的异质性和人口密地区对国家增长的影响不成比例.
结论:
- 经过调整的变量-r模型能够在有限的历史数据下进行可靠的人口增长分析.
- 短期的人口趋势有效地捕捉了人口变化的长期驱动因素.
- 国家以下的人口变化显著影响国家人口动态.
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