Research on the Influencing Factors of Beijing’s Economic Growth via Multiple Regression Analysis

In recent years, academic circles have continued to discuss and study the factors influencing internal economic growth in typical regions. On the basis of the existing theoretical basis of regional economic growth research, the Cobb‒Douglas production function, this paper combines the influencing factors of Beijing economic growth with economic level indicators (Zhang et al., 2018). Using multiple regression methods, this study investigates the factors influencing economic growth in Beijing from 2003--2022. Eleven indicators, including per capita fixed asset investment (FAI) and the employment level (LR), were selected to measure the annual per capita GDP growth rate of Beijing across 11 dimensions, such as capital input, labor force input, and globalization. The research results were validated by constructing a multiple linear regression equation. The key findings indicate that the proportion of service industry output in total output (IDU) and per capita retail sales of consumer goods (CGP) significantly positively correlate with the per capita GDP growth rate (RG). On the basis of these findings, the study proposes adjusting industrial structures and formulating policies to vigorously develop the service sector and driving consumption upgrades through targeted campaigns to stimulate domestic demand. The model demonstrates good fit, providing valuable references for analyzing regional economic factors.