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Population forecast of Anhui province based on the GM(1,1) model

Hong Gao (School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing, China)
Tianxiang Yao (School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing, China) (Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China)
Xiaoru Kang (School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 6 February 2017

331

Abstract

Purpose

The purpose of this paper is to predict the population of Anhui province. The authors analyze the trend of the main demographic indicators.

Design/methodology/approach

On the basis of the main methods of statistics, this paper studies the tendency of the population of Anhui province. It mainly analyzes the sex structure and the age structure of the current population. Based on the GM(1,1) model, this paper forecasts the total population, the population sex structure, and the population age structure of Anhui province in the next ten years.

Findings

The results show that the total population was controlled well, but there have been many problems of the population structure, such as the aging population, high sex ratio, heavy social dependency burden, and the declining labor force.

Social implications

This paper forecasts the main indexes of the population of Anhui province and provides policy recommendations for the government and the relevant departments.

Originality/value

This paper utilizes data analysis method and the grey forecasting model to study the tendency of the population problems in Anhui province.

Keywords

Citation

Gao, H., Yao, T. and Kang, X. (2017), "Population forecast of Anhui province based on the GM(1,1) model", Grey Systems: Theory and Application, Vol. 7 No. 1, pp. 19-30. https://doi.org/10.1108/GS-11-2016-0044

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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