The Forecast Analysis of Chinese Resident Consumption Based on the Residual Autoregressive Model

Abstract

This paper aims to improve the accuracy of resident consumption forecast by comparing different methods and selecting the residual autoregressive model. The model combines deterministic analysis method and autoregressive modeling to extract deterministic and random information, respectively, and improve the prediction accuracy. The paper introduces the modeling process of the residual autoregressive model and conducts empirical analysis on the consumption level data of Chinese residents to evaluate the fitting accuracy of the model. Finally, the model is used to forecast the consumption level of Chinese residents in 2021-2023, and the results indicate an average growth rate of about 7% over the next three years, assuming no major changes in the external environment. This paper contributes to the understanding of the residual autoregressive model and its application in the field of resident consumption forecasting, providing valuable insights for policymakers and researchers in this area.