Efficacy Evaluation of Statistical Prediction Models: A Comparative Analysis based on ARIMA Model, Grey Model and Polynomial Regression Model

Abstract

This paper uses ARIMA model, grey model and polynomial regression model to estimate and forecast two important indicators of China's real GDP growth rate and consumer price index (CPI). The results show that the sequence predicted by the polynomial regression model has the highest degree of agreement with the actual value, and has the lowest prediction error and the best prediction performance, while the other two types of models are not suitable for long-term prediction.