The consumer price index (CPI) measures the relative number of changes in the price level of consumer goods and services over time, reflecting the trend and degree of changes in the price level of goods and services purchased by residents. This article uses the ARMA model to analyze the fluctuation trend of the CPI (taking Chongqing as an example) and make short-term predictions. To test the predictive performance of the model, the observation values from January to December 2023 were retained as the reference object for evaluating the predictive accuracy of the model. Finally, through trial predictions of the data from May to August 2023, it was found that the constructed model had good fitting performance.
References
[1]
Fama, E.F. (1970) Efficient Capital Market: A Review of Hypothesis and Empirical Work. Journal of Finance, 25, 383-417. https://doi.org/10.2307/2325486
[2]
Judge, G. (1985) The Theory and Practice of Econometricst. John Wiley and Sons, New York.
[3]
Hosking, J.R.M. (1984) Modeling Persistence in Hydrological Time Series Using Fractional Differencing. Water Resources Research, 20, 1898-1908. https://doi.org/10.1029/WR020i012p01898
[4]
Box, G., Jenkins, G.M., Reinsel, G.C. and Ljung, G.M. (2015) Time Series Analysis: Forecasting and Control. John Wiley & Sons, Hoboken.
[5]
Lv, Y. and Chen, B. (2017) Analysis and Prediction of Income Gap between Urban and Rural Residents Based on ARMA Model—Taking Gansu as an Example. Business Economics Research, 2, 3.
[6]
Chen, X. (2020) Analysis and Prediction of the Information Consumption Gap between Urban and Rural Residents in Hunan Province—Based on ARMA Model. Fujian Quality Management, 9, 117.
[7]
Lv, Y. and Zhao, Y. (2015) Analysis of the Information Consumption Gap between Urban and Rural Residents in Hebei Province Based on ARMA Model. Journal of Baoding University, 2, 32-36.
[8]
Lu, X. and He, G. (2012) Prediction of Income Trends of Rural Residents in Sichuan Province Based on ARMA Model. Chinese Journal of Agronomy, 110-114.
[9]
Ren, Q. and Hou, D. (2011) Random Methods for Population Prediction: Based on Leslie Matrix and ARMA Model. Population Research, 35, 28-42.
[10]
Hu, Y., Wu, Z., Li, D. and Zhuo, M. (2006) Measuring Sustainable Development of Water Resources with Aquatic Ecological Footprint in Guangzhou Based on ARIMA Model. Ecology and Environment, 15, 94-98.
[11]
Akaike, H. (1974) A New Look at Statistical Model Identification. IEEE Transaction on Automatics Control, 19, 716-723. https://doi.org/10.1109/TAC.1974.1100705
[12]
Akaike, H. (1978) A Bayesian Analysis of the Minimum AIC Procedure. Annals of the Institute of Statistical Mathematics, 30, 9-14. https://doi.org/10.1007/BF02480194
