Abstract
The ‘low-altitude economy’ has garnered increasing attention from national authorities as a potential driver for China's new-quality productivity, with general aviation airports serving as its foundational infrastructure. Using panel data from 287 Chinese cities between 2018 and 2021, this study employs a Double Debiased Machine Learning (DDML) model to estimate the impact of general aviation airports on regional GDP. We conduct a series of robustness checks and heterogeneity analyses to validate the results. The findings indicate that the presence of general aviation airports significantly promotes regional economic growth. Further analysis shows that airports in China's western regions, as well as in areas with higher population density, exert a more pronounced positive impact on local economies. Additionally, the construction of general aviation airports does not result in significant impact on environment. This study suggests that general aviation airports play a crucial role in supporting regional economic growth and provide a foundation for further research on low-altitude infrastructure and its interactions with emerging technologies, such as urban air mobility, eVTOL aircraft, and autonomous aerial vehicles.
| Original language | English |
|---|---|
| Article number | 103880 |
| Journal | Transport Policy |
| Volume | 175 |
| DOIs | |
| State | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- General aviation airports
- Low-altitude economy
- Machine learning
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