摘要
本文首次利用Bayesian层次时空模型,以1995—2014年全国省级人口统计数据为基础,分析了近20年来我国老龄化在空间和时间上的变化规律。研究发现:1我国高老龄化地区分布已形成X型地理空间分布结构,东部地区为主,西部地区为辅,总体老龄化率呈上升趋势;2四川、重庆、辽宁、安徽、湖北和湖南等6个地区不仅是老龄化热点区域,而且老龄化增速也快于全国平均水平,特别是四川和重庆,老龄化程度和增速都是全国最高;3中西部地区老龄化程度虽然低于全国平均水平,但增加速度却高于全国平均水平;4北京、天津、上海、江苏、浙江和广东等6个高老龄化地区的老龄化率趋于平稳或增速放缓;5预测"全面二孩"政策情境下我国2030年老龄化率为13.19%(11.10%,20.94%)。
Based on provincial series statistical population data from 1995-2014, this paper investigates the spatio- temporal variation of Chinese aging during last 20 years, by employing Bayesian hierarchy space-time model and linear regression model firstly. There are 5 new findings. The spatial structure of high aging rate has formed as X-shaped, with eastern region playing a main role and western region playing a subsidiary role. Six provinces, such as, Chongqing, Sichuan, Liaoning, Anhui, Hubei, and Hunan, are the old aging hot spots, and increase faster than the national average. Especially, Chongqing and Sichuan＇ s increasing annual augmenters of aging rate are 0.39 and 0. 34 percent point respectively. The aging degree in middle-eastern regions is lower than nation＇ s increase and the rate is faster than nation＇ s. There are six high aging provinces, e.g. Beijing, Shanghai, Jiangsu, and Zhejiang, whose increasing rate are to be stable or lower than nation＇ s, experiencing a slower increasing process. According to our prediction, Chinese aging rate will be 13. 19% （11. 10% -20.94% ） if the universal two-child policy has been implemented.
出处
《统计研究》
CSSCI
北大核心
2016年第8期89-94,共6页
Statistical Research
