Population Research ›› 2022, Vol. 46 ›› Issue (4): 3-13.

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Reassessment of China's Fertility Level:An Analysis of the 7th Population Census Data

Zhai Zhenwu1,Jin Guangzhao2,Zhang Yiyang3   

  1. Zhai Zhenwu 1, Center for Population and Development Studies, Renmin University of China; Jin Guangzhao2 and Zhang Yiyang3, Center for Population and Development Studies, Renmin University of China.
  • Online:2022-07-29 Published:2022-08-03

中国生育水平再探索——基于第七次全国人口普查数据的分析

翟振武1,金光照2,张逸杨3   

  1. 翟振武1,中国人民大学人口与发展研究中心教授;金光照2、张逸杨3,中国人民大学人口与发展研究中心博士研究生。
  • 基金资助:
    本研究得到国家社会科学基金专项项目“新时代中国特色人口学基本理论问题研究”(19VXK07)的支持。

Abstract: The key to accurately assessing China's fertility level lies in high-quality data. The 7th population census has obtained data of very high quality mainly due to the newly added ID number registration and application of information technology, providing a good opportunity for reassessing China's fertility level. This study shows that the total fertility rate (TFR) of China maintained above 1.6 from 2006 to 2017, exceeded 1.7 in most of the years, but dropped sharply from 2017 to 2020. The TFR was fluctuating considerably, ranging from a low of just 1.3 in 2020 to a high of 1.89 in 2012 and 1.88 in 2017, with a 15-year average of 1.7. Fertility preferences, fertility policy adjustments, and COVID-19 had marked influence on fertility level. The average number of children ever born suggests that there is still potential for improvements in China's fertility level, and the key measure is to fully eliminate the emerging fertility inhibiting factors and build a fertility/family-friendly society to tap this potential.

摘要: 解开中国生育水平之“谜”的关键在于获得一套高质量的数据。第七次全国人口普查通过增设公民身份号码登记项目、全面运用信息化技术手段,获得了高质量年龄结构数据,为准确估计中国过去一段时间的生育水平提供了可靠数据基础。基于第七次全国人口普查数据分析发现,中国总和生育率在2006~2017年始终维持在1.6以上的水平,许多年份超过了1.7,在2017~2020年则持续下降;生育率存在较大波动,2020年达到最低值1.3,2012年和2017年出现明显高峰,分别约为1.89和1.88,15年间平均约为1.7。生育属相偏好、生育政策调整、新冠肺炎疫情造成了总和生育率的波动。妇女平均活产子女数显示中国目前生育水平仍有提升空间和发展潜力。充分消解新近出现的生育水平抑制性因素、构建家庭友好和生育友好型社会,是挖掘和发挥这种潜力的关键举措。

关键词: 生育水平, 总和生育率, 第七次全国人口普查, 数据质量