地理研究 ›› 2019, Vol. 38 ›› Issue (3): 667-683.doi: 10.11821/dlyj020180967
郭远智1,2,3(), 周扬1,2,3(
), 韩越1,2,3
收稿日期:
2018-09-26
修回日期:
2019-01-30
出版日期:
2019-03-20
发布日期:
2019-03-20
作者简介:
作者简介:郭远智(1990-),男,江西南康人,博士研究生,研究方向为城乡发展与贫困地理学研究。E-mail:
基金资助:
Yuanzhi GUO1,2,3(), Yang ZHOU1,2,3(
), Yue HAN1,2,3
Received:
2018-09-26
Revised:
2019-01-30
Online:
2019-03-20
Published:
2019-03-20
摘要:
社会经济发展过程中农村青壮年劳动力外流、预期寿命延长以及生育率下降使得乡村人口老龄化形势愈发严峻,因此科学认知农村人口老龄化的发展演化及其机理对于推进乡村振兴战略的实施具有重要意义。基于2000年和2010年人口普查数据,采用标准差椭圆、空间自相关、多元线性回归等分析方法,本文揭示了中国县域农村人口老龄化的时空格局及其形成机制,探讨人口老龄化背景下的乡村振兴对策。结果显示:① 2000—2010年,中国农村老龄人口主要分布在胡焕庸线东南一侧,在空间分布上保持“东北-西南”格局。② 2000年全国有48.26%的区县农村尚未步入老龄化,主要分布在西部、东北地区和中部的江西和湖北东部;到2010年,仅有17.54%的区县农村未进入老龄化,主要分布在胡焕庸线西北一侧及大兴安岭地区。③ 植被覆盖指数、死亡率、每千人卫生机构床位数、受教育水平、农民人均可支配收入与农村人口老龄化水平呈现正相关关系,人口净流出率、出生率、城镇化率、少数民族人口占比、海拔、人均GDP则呈现负相关关系。老龄化背景下,应积极推动新型城镇化和县域经济发展,构建城乡融合发展的体制机制和可持续发展的内生机制,同时逐步放开生育限制,降低人口的风险暴露,进而减缓人口老龄化发展,推动乡村振兴战略的实施。
郭远智, 周扬, 韩越. 中国农村人口老龄化的时空演化及乡村振兴对策[J]. 地理研究, 2019, 38(3): 667-683.
Yuanzhi GUO, Yang ZHOU, Yue HAN. Population aging in rural China: Spatial-temporal pattern and countermeasures for rural revitalization[J]. GEOGRAPHICAL RESEARCH, 2019, 38(3): 667-683.
表1
中国农村老龄人口特征椭圆参数"
特征椭圆 | 平均中心坐标 | x标准差(km) | y标准差(km) | 方位角θ(°) | |
---|---|---|---|---|---|
2000年 | 农村老龄人口 | 113.08°E, 32.19°N | 717.07 | 990.39 | 35.68 |
农村人口 | 112.59°E, 32.41°N | 783.34 | 1039.71 | 35.76 | |
老龄人口 | 113.87°E, 32.52°N | 726.43 | 1056.27 | 32.10 | |
2010年 | 农村老龄人口 | 113.01°E, 32.19°N | 738.89 | 1020.84 | 35.96 |
农村人口 | 112.62°E, 32.51°N | 833.58 | 1080.36 | 36.89 | |
老龄人口 | 113.79°E, 32.66°N | 758.19 | 1066.73 | 32.01 |
表3
中国农村人口老龄化模型的回归分析"
非标准化系数 | 标准化 系数 | t | Sig. | 共线性统计 | |||||
---|---|---|---|---|---|---|---|---|---|
B | Std. Error | 容忍度 | VIF | ||||||
NDVI | 2.008 | 0.292 | 0.107 | 6.872 | 0.000 | 0.699 | 1.432 | ||
Elevation | -2.63E-04 | 0.000 | -0.082 | -4.336 | 0.000 | 0.471 | 2.122 | ||
Natality | -0.115 | 0.012 | -0.155 | -9.384 | 0.000 | 0.617 | 1.620 | ||
Mortality | 0.953 | 0.033 | 0.439 | 28.755 | 0.000 | 0.725 | 1.379 | ||
NOR | -2.847 | 0.161 | -0.253 | -17.693 | 0.000 | 0.830 | 1.205 | ||
Per capita GDP | -0.08E-08 | 0.000 | -0.052 | -2.501 | 0.012 | 0.387 | 2.586 | ||
Per capita DIR | 4.43E-04 | 0.000 | 0.421 | 18.467 | 0.000 | 0.326 | 3.071 | ||
ROM | -0.006 | 0.002 | -0.058 | -3.497 | 0.000 | 0.620 | 1.613 | ||
UR | -0.009 | 0.003 | -0.054 | -2.581 | 0.010 | 0.384 | 2.606 | ||
NBHI | 0.125 | 0.038 | 0.056 | 3.277 | 0.001 | 0.582 | 1.719 | ||
EA | 0.112 | 0.054 | 0.048 | 2.075 | 0.038 | 0.314 | 3.183 | ||
Constant | 2.549 | 0.561 | 4.540 | 0.000 | |||||
R=0.739 | R2=0.546 | 调整R2=0.544 | |||||||
F=292.950 | Sig.=0.000 | df=11 |
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