A Comparative Analysis of ARIMA Models for Forecasting China’s GDP

Dongjie Wu

doi:10.54254/3029-0880/2025.26616

Advances in Operation Research and Production ManagementOpen access

A Comparative Analysis of ARIMA Models for Forecasting China’s GDP

Research Article

Open Access

A Comparative Analysis of ARIMA Models for Forecasting China’s GDP

Dongjie Wu ^1*

¹ School of Mathematics and Physics, Xiamen University Malaysia, Sepang, 43900, Malaysia

^*Corresponding author: MAT2209457@xmu.edu.my

Published on 11 September 2025

AORPM Vol.4 Issue 2

ISSN (Print): 3029-0899

ISSN (Online): 3029-0880

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Abstract

Gross Domestic Product (GDP) is the total market value of final goods and services produced by a country in a year. This study attempted to find the best-fit Autoregressive Integrated Moving Average (ARIMA) model for forecasting China’s GDP over the next five years (2025 to 2029). In this study, we collected historical GDP data for China from 1960 to 2024 from the World Bank. Using the Box-Jenkins approach, we examined the ACF and PACF plots, performed stationarity tests, and tested several models using the AIC criterion. We determined ARIMA(1,2,1) would be the best model to fit the data. We then used the fitted model to forecast the following five years for GDP in China, demonstrating the capabilities of ARIMA as an effective forecasting model.This study provides valuable insights for policymakers and economists in planning sustainable economic strategies for China's future development.

Keywords:

ARIMA, Box-Jenkins approach, GDP forecasting, ACF, PACF, stationarity tests, AIC criterion, predictive modeling

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