Analysis of the Spatiotemporal Heterogeneity and Influencing Factors of Regional Economic Resilience in China
This study estimates regional economic resilience in China from 2000 to 2022, focusing on economic resistance resilience, recovery resilience, and reorientation resilience. The entropy method, kernel density estimation, and spatial Durbin model are applied to examine the spatiotemporal evolution and...
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Veröffentlicht in: | Entropy (Basel, Switzerland) Switzerland), 2024-12, Vol.27 (1), p.23 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | This study estimates regional economic resilience in China from 2000 to 2022, focusing on economic resistance resilience, recovery resilience, and reorientation resilience. The entropy method, kernel density estimation, and spatial Durbin model are applied to examine the spatiotemporal evolution and influencing factors. The results show significant spatial clustering, with stronger resilience in the east and weaker resilience in the west. While economic resilience has generally improved, regional disparities persist. Key factors such as human capital, urban hospitals, financial development, market consumption, and environmental quality have a positive effect on resilience, with spatial spillover effects. However, human capital and urban hospitals also show a negative indirect impact on surrounding regions. The influence of these factors varies across regions and periods, indicating strong spatiotemporal heterogeneity. |
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ISSN: | 1099-4300 1099-4300 |
DOI: | 10.3390/e27010023 |