Welcome to Francis Academic Press

Academic Journal of Business & Management, 2020, 2(3); doi: 10.25236/AJBM.2020.020302.

Grey Correlation Analysis and Forecast of Residents' Income and Consumption Structure

Author(s)

Haifei Xiang

Corresponding Author:
Haifei Xiang
Affiliation(s)

Department of public education , Wenzhou Polytechnic , Wenzhou ,325000, China
[email protected]

Abstract

At present, China's economy is facing the problem of declining investment and export growth. To ensure the sound development of China's economy, it is necessary to maintain the effective pull of consumption on economic development. Correctly evaluating the basic situation and changing trend of Chinese residents' consumption structure is helpful to provide theoretical basis for relevant macro-economic policies to improve consumption structure, thus comprehensively improving the consumption level and quality of life of Chinese urban residents. This paper selects 8 indicators related to the consumption structure of rural residents, and based on statistical data, uses grey correlation analysis method to quantitatively analyze the relationship between the consumption structure and income level of rural residents from 2020 to 2023. On this basis, the grey prediction method is applied to establish a prediction model of residents' income level and various consumption expenditures, to predict the income level and various consumption expenditures, and to analyze the future change trend of the relationship between leisure consumption and income level under the background of changes in consumption structure.

Keywords

Income of residents, Consumption structure, Grey correlation, Forecast

Cite This Paper

Haifei Xiang. Grey Correlation Analysis and Forecast of Residents' Income and Consumption Structure. Academic Journal of Business & Management (2020) Vol. 2, Issue 3: 6-14. https://doi.org/10.25236/AJBM.2020.020302.

References

[1] Xiao Jun, Li Zhongfei. Grey correlation analysis of the impact of population aging on consumption structure in Shaanxi Province [J]. Contemporary Economy, 2016, 000 (033): 144-145.
[2] Li Wei, Shi Jie, Duan Xiaohong. Gray correlation analysis of the impact of changes in rural residents income growth on consumption structure in Gansu Province [J]. Heilongjiang Agricultural Sciences, 2015 (07): 140-144.
[3]  Zhou Huiqiu, Liang Rongcheng. An Empirical Study on the Gray Correlation of Consumption Structure of Rural Residents in Heilongjiang Province [J]. Journal of Shijiazhuang University of Economics, 2017, 000 (003): 59-63.
[4]  Wang Hongzhang, Liang Conggang. Research on residential environmental consumption structure based on improved gray correlation analysis method [J]. Environmental Science and Management, 2015, 040 (003): 163-168.
[5] Ji Zhenglong. Grey correlation analysis of consumption structure and industrial structure in Jiangsu Province [J]. Business Times, 2015, 000 (031): 23-25.
[6]  Nie Yi. Gray correlation analysis of the consumption structure of farmers in Yunnan Province \ r and its trend prediction [J]. Chemical Engineering Management, 2018, 000 (032): 217-218.
[7] Chen Chen, Wu Guoyong. Grey Correlation Analysis and Prediction Study of Virtual Water Consumption of Urban and Rural Residents in Guizhou Province [J]. Eco-Economy, 2018, 034 (010): 119-124.
[8] Tong Xia. Generalized Grey Correlation Analysis of the Consumption Structure of Migrant Workers Households——Comparison with Urban and Rural Households [J]. Rural Economy and Science and Technology, 2018, 29 (21): 155-157.
[9] Zhu Pingping. Analysis of the correlation between residents' consumption level and industrial structure \ r——Taking Xinjiang as an example [J]. National Business Situation and Theoretical Research, 2018, 000 (025): 73-75.