在线咨询
中国工业与应用数学学会会刊
主管：中华人民共和国教育部
主办：西安交通大学
ISSN 1005-3085  CN 61-1269/O1
工程数学学报

工程数学学报 ›› 2020, Vol. 37 ›› Issue (5): 531-549.doi: 10.3969/j.issn.1005-3085.2020.05.002

• • 上一篇    下一篇

人口普查漏报估计研究

胡桂华,   廖金盆,   范署姗,   叶宝红,   吴   婷   

  1. 重庆工商大学数学与统计学院 经济社会应用统计重庆市重点实验室，重庆  400067
  • 收稿日期:2019-06-06 接受日期:2020-04-09 出版日期:2020-10-15 发布日期:2020-12-15
  • 基金资助:
    教育部人文社会科学研究项目 (20YJA910002)；全国统计科学研究重点项目 (2019LZ28)；2020年度重庆市研究生创新型科研项目(CYS20316)；重庆工商大学2020年研究生创新型科研项目(yjscxx2020-094-77).

Research on Census Omission Estimation

HU Gui-hua,   LIAO Jin-pen,   FAN Shu-shan,   YE Bao-hong,   WU Ting   

  1. College of Mathematics and Statistics, Chongqing Key Laboratory of Economic and Social Applied Statistics, Chongqing Technology and Business University, Chongqing 400067
  • Received:2019-06-06 Accepted:2020-04-09 Online:2020-10-15 Published:2020-12-15
  • Supported by:
    The Research Foundation for Humanities and Social Sciences of the Ministry of Education (20YJA910002); the National Key Project of Statistical Science Research (2019LZ28); the Innovative Research Item of Chongqing Graduate Students in 2020 (CYS20316); the Innovative Research Project for Graduate Students of Chongqing Technology and Business University in 2020 (yjscxx2020-094-77).

PDF (PC)

238

摘要： 本文针对目前许多国家在普查漏报估计中使用未匹配估计量，从而低估总体普查漏报人口数的问题，明确提出用普查漏报合成估计量予以替代的研究目标．为实现目标，采取数理模型与抽样估计相结合的方法研究未匹配估计量和普查漏报合成估计量及其抽样方差估计量．理论与实证研究结果表明，相比未匹配估计量，普查漏报合成估计量估计的漏报人口数更多和抽样估计的精度更高；为便于计算，普查漏报合成估计量须在等概率人口层建立；普查漏报合成估计量理论前沿且具有可操作性，将应用于我国2020年人口普查漏报估计，提高其估计精度．

关键词: 抽样调查, 人口普查质量评估, 普查漏报, 分层刀切法

Abstract: In view of many countries using unmatched estimator in census omission estimation, which leads to underestimate omissions, the objective of this work is to replace it with the census omission synthetic estimator. In order to achieve the goal, a combination of mathematical model and sampling estimation is used to study the unmatched estimator, census omission synthetic estimator, and their sampling variance estimators. Theoretical and empirical research results show that compared with the unmatched estimator, the census omission synthetic estimator provides more omissions and higher estimation accuracy. For simplicity of calculation, the census omission synthetic estimator must be established in population strata of equal probability. The census omission synthetic estimator will be applied to China's 2020 census omission estimation to improve its estimation accuracy.

Key words: sample survey, census quality evaluation, census omissions, stratified jackknife

中图分类号: