Abstract
Within the context of China's ongoing urban cluster development, pronounced disparities in financial efficiency have emerged between central and peripheral cities. Although coordinated financial development within urban clusters is crucial, this issue has been largely overlooked. To address this gap, this study employs a two-regime spatial Durbin model to investigate the asymmetric spatial spillover effects of financial efficiency between central and peripheral cities, using panel data from 285 Chinese cities spanning 2011–2022. As artificial intelligence (AI) represents a strategic technology shaping future economic transformation, it is expected to play a pivotal role in reconfiguring financial efficiency. Accordingly, this paper further examines the influence of AI from both spatial and asymmetric perspectives. The results reveal significant differences in the spatial spillover effects of neighboring cities' financial efficiency across central and peripheral cities, thereby confirming the presence of asymmetric spillover effects. While AI generates an overall positive spatial spillover effect on financial efficiency, it intensifies existing asymmetries by weakening the positive spillover effects from neighboring cities for central cities and amplifying the negative spillover effects for peripheral cities. Moreover, the impact of AI on financial efficiency is subject to a digital finance threshold. These findings underscore the asymmetric nature of financial efficiency spillovers between central and peripheral cities, particularly as they are reshaped by AI, and provide important policy implications for promoting coordinated financial development during the integration of urban clusters.
| Original language | English |
|---|---|
| Article number | 105584 |
| Journal | International Review of Economics and Finance |
| Volume | 110 |
| DOIs | |
| Publication status | Published - Sept 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Artificial intelligence
- Central cities
- Financial efficiency
- Peripheral cities
- Spatial spillover effect
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