Research on Gross Domestic Product forecasting in Shanghai based on Auto Regressive Integrated Moving Average Model

Yujun Cao

doi:10.62051/ijcsit.v4n3.32

Authors

Yujun Cao

DOI:

https://doi.org/10.62051/ijcsit.v4n3.32

Keywords:

Time Series analysis, Economic forecast, ARIMA, GDP, Shanghai

Abstract

GDP is an important reflection of economic development, and the correct prediction of GDP can provide an important reference for predicting economic development. The economy of various provinces and cities is an important influencing factor in China's GDP, and Shanghai, as a province and city with rapid economic development, has played a key driving role in the national economy. Therefore, this study will analyze the GDP value of Shanghai. This paper analyzes the GDP data of Shanghai from 2000 to 2022, establishes the ARIMA (0, 2, 2) model, and uses this model to predict Shanghai GDP data in 2023. Compared with the actual value, it is concluded that the model has high credibility and high prediction accuracy, and can be used for Shanghai. The city's GDP is forecasted in the short term to provide reference for government departments to formulate corresponding response policies.

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