Drivers of Economic Growth in the Guangdong–Hong Kong–Macao Greater Bay Area: Evidence from Ridge Regression

Lv Hao

doi:10.63944/fhg01.rcs

***Drivers of Economic Growth in the Guangdong–Hong* *Kong–Macao Greater Bay Area: Evidence from Ridge Regression***

Lv Hao (作者)

Department of Statistics, School of Mathematics , Guangdong University of Education, China

DOI：https://doi.org/10.63944/fhg01.rcs

关键词：

Guangdong-Hong Kong-Macao Greater Bay Area, economic forecasting, ridge regression

已出版

2026-05-31

摘要

This study investigates the main factors associated with economic growth in the Guangdong–Hong Kong–Macao Greater Bay Area from 2000 to 2023. Based on official statistical data, the paper constructs a multidimensional indicator system covering economic output, population and labor, science and technology input, infrastructure, openness, logistics, and the global economic environment. In the data preprocessing stage, missing values are treated through linear interpolation, and multicollinearity among explanatory variables is examined using the variance inflation factor. The results show that most explanatory variables have high VIF values, indicating serious multicollinearity in the dataset. To reduce dimensionality and improve the stability of model estimation, KMO and Bartlett tests are conducted, and principal component analysis is applied to suitable variable categories. On this basis, ridge regression is introduced to estimate the relationship between different explanatory factors and GBA GDP.

The empirical results show that industrial structure, population and labor scale, innovation input, openness, and the external economic environment are closely associated with changes in GBA GDP. In particular, the secondary and tertiary sectors show positive coefficients in the ridge regression model, indicating that manufacturing and service industries remain important supports for regional economic growth. Population and employed population also show positive associations with GDP, suggesting that labor scale and demographic agglomeration provide a basic foundation for economic expansion. R&D expenditure has a positive coefficient, reflecting the role of innovation input in promoting economic upgrading. At the same time, the results should be interpreted cautiously because the explanatory variables are highly correlated, and ridge regression coefficients mainly reflect the relative direction and stability of variable associations rather than strict causal effects. Overall, this study provides a quantitative reference for identifying key drivers of economic growth in the GBA and offers policy implications for industrial upgrading, innovation enhancement, openness expansion, and regional coordination.

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Drivers of Economic Growth in the Guangdong–Hong Kong–Macao Greater Bay Area: Evidence from Ridge Regression

如何引用

***Drivers of Economic Growth in the Guangdong–Hong* *Kong–Macao Greater Bay Area: Evidence from Ridge Regression***