Prediction Analysis of Shenzhen GDP Based on ARIMA Model and Implementation in R Language

Abstract

GDP can measure the development level and economic situation of a region to a certain extent. This paper selects the GDP data of Shenzhen from 1980 to 2020, and constructs the Arima(2, 2, 3) model to predict the GDP data in the next 5 years. First, after Box-Cox transformation and difference operation are performed on the selected data, the Augmented Dickey-Fuller (ADF) stationarity test is carried out. Under the condition of passing the ADF test, this paper uses the maximum likelihood method to iteratively estimate the parameters of the model based on the initial value of the least squares’ estimation, and then performs a mixed test on the residual data to verify the validity of the parameters. Finally, the h steps forward method is used to predict the GDP data of Shenzhen in the next five years, and the corresponding confidence interval is obtained. The relative error between the prediction results in 2021 and the actual data is 2.9%, indicating that the prediction results of the model are good and have certain feasibility.