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Arid Land Geography ›› 2025, Vol. 48 ›› Issue (6): 1103-1114.doi: 10.12118/j.issn.1000-6060.2024.512

• Regional Development • Previous Articles     Next Articles

Spatio-temporal differentiation of economic resilience in the Yellow River region based on multidimensional evaluation methods

XUE Chenhao1,2(), BAI Yongping1(), WANG Shengpeng2   

  1. 1. College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, Gansu, China
    2. College of Management, Northwest Minzu University, Lanzhou 730030, Gansu, China
  • Received:2024-08-24 Revised:2024-11-24 Online:2025-06-25 Published:2025-06-18
  • Contact: BAI Yongping E-mail:xuechenhaovip@126.com;baiyp@nwnu.edu.cn

Abstract:

Scientifically measuring economic resilience in the Yellow River region is essential for enhancing regional development quality and sustainability. This study constructed a comprehensive indicator system to evaluate economic resilience across the Yellow River region from 2003 to 2022, examining three critical dimensions: Resistance, resilience, and transformation. We employed the Theil index to quantify regional disparities and the Moran’s index to analyze spatial correlation patterns. Our analysis revealed four key findings: (1) Regional performance: The Yellow River region demonstrated stable economic operation with strong overall resilience during the study period, though a significant gap persists compared to national economic resilience levels. Among the dimensional subsystems, resilience scored highest while transformation scored lowest. (2) Spatial distribution: Economic resilience exhibits a clear center-periphery structure at the prefecture level. Higher resilience areas are concentrated in the Shandong Peninsula, provincial capitals in central and western China, and mineral-rich cities. Lower resilience characterizes Qinghai, Ningxia, most of Gansu, Shaanxi, Henan, western Inner Mongolia, and western Shandong. (3) Temporal trends: The overall difference in economic resilience across the Yellow River region showed a decreasing trend over most of the study year. Regional differences contributed more than 75% to overall inequality, highlighting the need for coordinated intra-regional strategies. (4) Spatial correlation: Positive Moran’s index values throughout the study period indicate significant autocorrelation in economic resilience. Local spatial clustering revealed predominant “low-low” agglomeration (concentrated in Qinghai, Gansu, and Ningxia) and “high-high” agglomeration (primarily in Shandong).

Key words: economic resilience, spatiotemporal differentiation, indicator system method, the Yellow River region