The Relationship Between Consumption Power and GDP Growth in China and Machine Learning Prediction Analysis - Hu Runsong (ITM Web of Conferences)
With the rapid development of China’s economy, consumption has become a key driving force to boost domestic demand and promote economic structural transformation. By analyzing the current situation of China's economic development, this paper focuses on the relationship between residents' consumption capacity and Gross Domestic Product (GDP) growth. The paper examines the use of machine learning for predicting consumption capacity by integrating various economic models, including Support Vector Regression (SVR) and Long Short-Term Memory Network (LSTM). Moreover, by analyzing data on China's GDP and consumption capacity from 1991 to 2020, the study demonstrates a strong positive correlation between the two. This finding further highlights the significant impact of consumption capacity on economic growth. The article also applies univariate and bivariate analyses to calculate the concentration trend and degree of dispersion of GDP and consumption capacity, and it uses regression models to explore the relationship between the two further. This article can provide policymakers with a deeper understanding of regional consumption differences and economic development trends, thus providing a decision-making basis for optimizing economic policies.