首页> 外文期刊>Population Research and Policy Review >New Directions in the Development of Population Estimates in the United States?
【24h】

New Directions in the Development of Population Estimates in the United States?

机译:美国人口估计发展的新方向?

获取原文
获取原文并翻译 | 示例
       

摘要

The advent of a continuously updated Master Area File (MAF) following the 2000 census represents an information resource that can be tapped for purposes of developing timely, cost-effective, and precise population estimates for even the smallest of geographical units (e.g., census blocks). We argue that the MAF can be enhanced (EMAF) for these purposes. In support of our argument we describe a set of activities needed to develop EMAF, each of which is well within the current capabilities of the U.S. Census Bureau and discuss various costs and benefits of each. We also describe how EMAF would provide population estimates containing a wide range of demographic (e.g., age, race, and sex) and socio-economic characteristics (e.g., educational attainment, income, and employment). As such, it could largely negate and eliminate the need for many of the traditional demographic methods of population estimation and possibly reduce the number of sample surveys. We identify important challenges that must be surmounted in order to realize EMAF and make suggestions for doing so. We conclude by noting that the idea of the EMAF could be of interest to other countries with MAF files and strong administrative records systems that, like the United States, are facing the challenge of producing good population information in the face of increasing census costs.
机译:在2000年的人口普查之后,不断更新的主区域文件(MAF)的出现代表了一种信息资源,可以利用该信息资源来为最小的地理单位(例如,人口普查区域)制定及时,具有成本效益的精确人口估计​​值。 )。我们认为可以为这些目的而增强MAF(EMAF)。为支持我们的论点,我们描述了开发EMAF所需的一系列活动,每种活动都在美国人口普查局的当前能力范围内,并讨论了每种活动的各种成本和收益。我们还将描述EMAF如何提供包含各种人口统计信息(例如年龄,种族和性别)和社会经济特征(例如教育程度,收入和就业)的人口估计。因此,它可以在很大程度上消除并消除对许多传统的人口统计学方法的人口估计的需求,并可能减少抽样调查的数量。我们确定了实现EMAF必须克服的重要挑战,并为此提出了建议。我们在总结时指出,EMAF的想法可能会与具有MAF文件和强大的行政记录系统的其他国家(例如美国)面对,而面对日益增长的普查成本,这些国家面临着提供良好的人口信息的挑战。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号