Analysis and Research on the Influencing Factors of Regional CPI Based on CVM-AHP Coupling Perspective

Dongjian Zhang; Hanjing Mu

doi:10.54097/hbem.v2i.2340

Authors

Dongjian Zhang
Hanjing Mu

DOI:

https://doi.org/10.54097/hbem.v2i.2340

Keywords:

CPI; influencing factors; CVM; AHP; lagrangian multiplier method.

Abstract

The consumer price index (CPI) is a statistical indicator to measure the macroeconomic development of a region. Studying the influencing factors of regional CPI is helpful to deeply explore the mechanism of CPI change, and then help to measure inflation, national economic accounting, and contract indexation adjustment. In this paper, the coefficient of variation method (CVM) and analytic hierarchy process (AHP) is used to determine the subjective and objective weights of the evaluation factors, and the coupling weights are calculated based on the Lagrange multiplier method. Shanghai, China, is selected for empirical analysis to evaluate the suitability of CPI influencing factors in the study area. The results show that regional CPI is closely related to population size, population density, the proportion of the elderly population, urban resident population, GDP, per capita disposable income, PPI, and fixed asset investment. Among them, GDP, per capita disposable income, and fixed asset investment have the most prominent impact on CPI. The proportion of the elderly population and PPI have a more obvious impact, and the impact of population size, population density, and urban resident population is not obvious. The research on the influencing factors of regional CPI in this paper is of great practical significance to explore the causes of China's inflation and formulate reasonable macroeconomic policies.

Downloads

Download data is not yet available.

References

Shanghai Municipal Bureau of Statistics, Shanghai June 2002 CPI data information [DB / OL] https://tjj.sh.gov.cn/[2022-8-16]

Xin Junking. Study on the fluctuation characteristics and conduction relationship between PPI and CPI in Shandong Province [D].Shandong University of Finance and Economics, 2018.

Chen Lin, Xie Jiachun, Ma Liangli. Optimal Models for Short-term CPI Forecasting in China - Selection and Optimization Based on Several Time Series Models [J]. Contemporary Economics, 2022, 39 (05): 9-16.

Li Jinhong. Research on the Impact of Population Aging on Consumption Level in Shanghai [J]. Inner Mongolia Coal Economy, 2021 (19): 199-200.DOI : 10.13487 / j.cnki.imce.021054.

Liu Weitang. Fluctuation analysis of the national consumer price index based on the multiple change-point theory [J]. Q, 2015 (10): 179-180.

Wang Dong, Liu Haiming. An empirical study on structural factors affecting CPI in Macao, China [J]. Inner Mongolia Science and Technology and Economy, 2017 (10): 34-36 + 38.

Zhao Na. Research on the influencing factors of Chengdu CPI based on principal component analysis [ J ]. China Statistics, 2019 (03) : 44-47.

Song Linqiang. Application of canonical correlation analysis in the correlation analysis of population and economic characteristics system [J].Western leather, 201,638 (22) : 109 + 131.

Luo Zhengyuan, Zhao Shixiu. The impact of population density on household consumption in the context of urbanization-Taking Chengdu-Chongqing urban agglomeration as an example [J].Commercial economic research, 2022 (14) : 64-67.

Zhang Yue. Research on the impact of population structure change on rural residents' consumption in Anhui Province-Based on the life cycle hypothesis theory [J]. Taxation, 2017 (19) : 112-113.

Ma Liping, Chen Yuxin. Research on the impact of CPI changes on the actual purchasing power of residents-Based on the CPI classification calculation of different income groups of the urban population in Beijing [J]. Price theory and practice, 2014 (10): 62-64.DOI : 10.19851 / j.cnki.cn11-1010 / f. 2014.10.021. Li Jinhong. Research on the Impact of Population Aging on Consumption Level in Shanghai [J ]. Inner Mongolia Coal Economy, 2021 (19): 199-200.DOI : 10.13487 / j.cnki. IMC e. 021054.

Zhan Mengyu. Correlation analysis between CPI change and GDP growth in Southwest China [J]. Journal of Shenyang Agricultural University ( Social Science Edition ), 2017, 19 (01): 12-17.

Li Huihui. Research on the Relationship between National Income, Money Supply and CPI [J]. China Market, 2018 (15) : 5-8.DOI : 10.13939 / j.cnki.zgsc. 2018.15.005.

Yang Yewei, Xu Xianchun. Analysis of the conduction effect of PPI and CPI [J]. Statistics and decision-making, 2022, 38 (13) : 62-66.DOI : 10.13546 / j.cnki. JYJ .2022.13.012.

Hou Tiantian, Yang Shuning. Trend Prediction and Influencing Factors Analysis of Consumer Price Index in China [J]. Statistical Theory and Practice, 2020 (04) : 34-41.

Li Shuai, Wei Hong, Ni Xilu, Gu Yanwen, Li Changxiao. Evaluation of urban human settlements quality in Ningxia based on analytic hierarchy process and entropy weight method [ J ]. Applied Ecology, 2014, 25 ( 09 ): 2700-2708.DOI : 10.13287 / j.1001-9332.2014.0215.