Prediction of Population Aging Based on an Improved Markov Matrix

DOI

10.2991/978-94-6463-056-5_42How to use a DOI?

Keywords

Population Prediction; Improved Markov Matrix; Population Aging; Leslie Matrix; Turning Point

Abstract

Grasping the population aging from the perspective of long-term development has certain guiding significance of formulating national economic development plan and social strategic goals in China. Based on the Markov matrix and the population process reflected by Leslie matrix, an improved Markov matrix is constructed in this paper to predict the aging tendency of China’s population. The prediction process takes full account of age-specific fertility rate, age-specific survival rate, male-to-female birth ratio and age-specific male-to-female ratio, which makes it have strong fault tolerance. It turns out that China's population will reach a peak of 1.42337 billion in 2027, and the proportion of the aging population will reach a maximum of 34.35% in 2060 and then begin to decline slightly, which can be traced to the second baby boom in Chinese history. But the proportion will remain above 25% until 2220. China's population aging is a long-term and non-cyclical process, and its deepening is mainly caused by the population structure not adapting to the population fertility pattern and life style under the background of the new era. Therefore, improving the population aging in China needs time to push forward the evolution of population structure. At the same time, China should develop a long-term sustainable aging economy to prepare for confronting the aging war and the "turning point".

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Lelin Zeng
AU  - Jinghao Duan
AU  - Junfang Zhao
PY  - 2022
DA  - 2022/12/29
TI  - Prediction of Population Aging Based on an Improved Markov Matrix
BT  - Proceedings of the 2022 2nd International Conference on Management Science and Software Engineering (ICMSSE 2022)
PB  - Atlantis Press
SP  - 292
EP  - 301
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-056-5_42
DO  - 10.2991/978-94-6463-056-5_42
ID  - Zeng2022
ER  -