The Impact of a Comprehensive Two Child Policy on Population and Economic Structure

DOI

10.2991/meess-18.2018.21How to use a DOI?

Keywords

Universal two-child policy; gray prediction; Coefficient of variation.

Abstract

The population problem involves the quality of population and the structure of population. It is a complex system engineering. The stable population development is directly related to the sustainable development of our society and economy. Based on the grey prediction method, this paper predicts the change of population in China under the full implementation of the two-child policy [1]. We set up a grey prediction model based on grey prediction theory to predict the total population of our country for 2017-2030 years. Economic development is constrained by factors such as capital, energy, labor and technology. According to the analysis of the data, we have determined six factors affecting the economy, such as capital input, energy consumption, labor input, population growth, technical turnover and resident consumption. The coefficient of variation is used to calculate the objective weight of the index. Finally, we conclude that population structure has great influence on the economy, and its performance is in terms of labor force. Through targeted changes in the labor force, the changes in the population of children and the impact on economic growth, we have made targeted recommendations to the policy.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yinhuan Li
PY  - 2018/08
DA  - 2018/08
TI  - The Impact of a Comprehensive Two Child Policy on Population and Economic Structure
BT  - Proceedings of the 2018 International Conference on Management, Economics, Education and Social Sciences (MEESS 2018)
PB  - Atlantis Press
SP  - 108
EP  - 111
SN  - 2352-5398
UR  - https://doi.org/10.2991/meess-18.2018.21
DO  - 10.2991/meess-18.2018.21
ID  - Li2018/08
ER  -