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按年龄、性别和种族对美国各县的人口预测进行控制,以实现共享社会经济途径。

Population projections for U.S. counties by age, sex, and race controlled to shared socioeconomic pathway.

机构信息

Department of Sociology, Florida State University, 600 W. College Avenue, Tallahassee, USA.

The Center for Demography and Population Health, Florida State University, Tallahassee, USA.

出版信息

Sci Data. 2019 Feb 5;6:190005. doi: 10.1038/sdata.2019.5.

Abstract

Small area and subnational population projections are important for understanding long-term demographic changes. I provide county-level population projections by age, sex, and race in five-year intervals for the period 2020-2100 for all U.S. counties. Using historic U.S. census data in temporally rectified county boundaries and race groups for the period 1990-2015, I calculate cohort-change ratios (CCRs) and cohort-change differences (CCDs) for eighteen five-year age groups (0-85+ ), two sex groups (Male and Female), and four race groups (White NH, Black NH, Other NH, Hispanic) for all U.S counties. I then project these CCRs/CCDs using ARIMA models as inputs into Leslie matrix population projection models and control the projections to the Shared Socioeconomic Pathways. I validate the methods using ex-post facto evaluations using data from 1969-2000 to project 2000-2015. My results are reasonably accurate for this period. These data have numerous potential uses and can serve as inputs for addressing questions involving sub-national demographic change in the United States.

摘要

小区域和次国家人口预测对于理解长期人口变化非常重要。我提供了美国所有县 2020-2100 年期间按年龄、性别和种族划分的每五年一次的人口预测。使用历史上美国人口普查数据,按照时间修正的县边界和 1990-2015 年期间的种族群体,我为所有美国县计算了 18 个五年年龄组(0-85+)、两个性别组(男性和女性)和四个种族组(白种非西班牙裔、黑种非西班牙裔、其他非西班牙裔、西班牙裔)的队列变化比(CCR)和队列变化差异(CCD)。然后,我将这些 CCR/CCD 使用 ARIMA 模型作为输入,输入到 Leslie 矩阵人口预测模型中,并将预测结果控制到共享社会经济途径中。我使用 1969-2000 年的数据进行事后评估来验证这些方法,以预测 2000-2015 年的数据。在这段时间内,我的结果相当准确。这些数据有许多潜在的用途,可以作为解决美国次国家人口变化问题的输入。

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