The Future Process of Japan’s Population Aging: A Cluster Analysis Using Small Area Population Projection Data

Author:

Inoue TakashiORCID,Inoue NozomuORCID

Abstract

AbstractJapan’s population aging is the most advanced in the world today. No nationwide study has been conducted using small area population projection data on Japan’s aging population. This is because such projection data was unavailable for Japan before the 2016 launch of the website ‘The Web System of Small Area Population Projections for the Whole Japan’ (SAPP for Japan). SAPP for Japan opened the small-area and long-term projected population of Japan for the first time on the World Wide Web. The purpose of this study is to quantitatively analyze the future aging process using data from the SAPP for Japan and, based on this analysis, to attempt to present the standard aging process that developed countries will experience after the demographic transition, taking advantage of the fact that Japan has the most aged population in the world. Subsequently, a non-hierarchical cluster analysis was performed using two statistics on aging: the elderly population proportion and the elderly population change index, and the small areas were classified into seven clusters. Furthermore, this study examined the demographic and geographical features of the clusters, introduced a new concept of the stage in the population aging process, and analyzed the relationship between the features and the stages. To conclude, the following findings were obtained regarding the future process of Japan’s population aging. In each area of Japan, first, the total population begins to decline, second, the elderly population begins to decrease, and finally, its proportion begins to decrease. These stage shifts generally proceed earlier in areas with a higher elderly population proportion and are attributed to the reduced size of younger cohorts owing to long-term fertility decline. This process would be the norm in many developed countries after the demographic transition.

Funder

Japan Society for the Promotion of Science

Publisher

Springer Science and Business Media LLC

Reference84 articles.

1. Anderson, M. A. (2007). Location quotients, ambient populations, and the spatial analysis of crime in Vancouver, Canada. Environment and Planning a: Economy and Space, 39, 2423–2444. https://doi.org/10.1068/a38187

2. Anselin, L., Lozano, N., & Koschinsky, J. (2006). Rate transformations and smoothing. Spatial Analysis Laboratory, Department of Geography, University of Illinois, Urbana-Champaign. https://www.researchgate.net/publication/249913160_Rate_Transformations_and_Smoothing

3. Arthur, D., & Vassilvitskii, S. (2007). K-means++: The advantages of careful seeding. In Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 1027–1035). Society for Industrial and Applied Mathematics.

4. Baker, J., Alcántara, A., Ruan, X., Watkins, K., & Vasan, S. (2014). Spatial weighting improves accuracy in small-area demographic forecasts of urban census tract populations. Journal of Population Research, 31(4), 345–359. https://doi.org/10.1007/s12546-014-9137-1

5. Baker, J., Swanson, D. A., & Tayman, J. (2021). The accuracy of Hamilton-Perry population projections for census tracts in the United States. Population Research and Policy Review, 40, 1341–1354. https://doi.org/10.1007/s11113-020-09601-y

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3