Research of Forecasting Chinese Gross Domestic Product Based on Auto Regressive Integrated Moving Average Algorithm and Linear Regression Model

Abstract

Gross domestic product (GDP) is an important indicator for measuring a country's economic development level. By studying GDP, it can analyze the economic structure of a country or region, determine the development trend of a country. GDP is widely applied in fields such as macroeconomic analysis, policy formulation, and international economic comparison. After Chinese reform and opening up, the economy has developed rapidly, and the GDP has shown a trend of increasing year by year. Therefore, the analysis of Chinese GDP is meaningful. This article analyzes GDP data from 2001 to 2017. Linear regression method is used for prediction first but the goodness of fit for this model to predict GDP is not very high. So then the Auto Regressive Integrated Moving Average (ARIMA) model is used for prediction. The results indicate that the ARIMA algorithm has higher goodness of fit and can better illustrate the situation, which can be used for short-term prediction in China. All this model is realized in the python.