人口普查
小区域估算
估计
人口
保密
地理
美国社区调查
计算机科学
公共用途
统计
计量经济学
人口学
数学
政治学
计算机安全
经济
社会学
管理
法学
标识
DOI:10.1177/23998083231215825
摘要
Small area estimation is critical for a wide range of applications, including urban planning, funding distribution, and policy formulation. Individual-level population data, which typically include each individual’s socio-demographic characteristics and small area location, are a rich source of information for small area estimation. However, individual-level population data are often not made public due to confidentiality concerns. This paper describes the development of a public-use synthetic individual-level population dataset in the United States that can be useful for small area estimation. This dataset contains characteristics of housing type, age, sex, race, and Hispanic or Latino origin for all 308,745,538 individuals in the United States at the census block group level, based on publicly available aggregated data from the 2010 Census. Experimental results suggest the validity of the synthetic data by comparing it to different data sources, and we show examples of how this dataset can be used in small area estimation.
科研通智能强力驱动
Strongly Powered by AbleSci AI