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<p>Accurately identifying the evolving trends of regional economic inequality is crucial for promoting coordinated regional development and achieving Chinese-style modernization. This paper, based on continuous nighttime light data from 1992 to 2019, uses the Dagum Gini coefficient, emerging hot spot analysis, and XGBoost-SHAP interpretable machine learning models to analyze the spatiotemporal evolution of multi-scale regional economic inequality in China, as well as the spatial cold spots and hot spots and inter-regional and intra-regional inequalities among different subregions. It also reveals the impact contributions of natural and economic factors on regional economic inequality. The results show that: (1) During the study period, provincial-level economic inequality in China gradually increased before 2003 and then decreased afterward. After 2012, the decline at the provincial level slowed down, while city-level and county-level economic inequality slightly increased. (2) The Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta city clusters remain persistent nighttime light hotspots. Multiple eastern and central city clusters are gradually becoming new hotspots, while cold spots in western regions are decreasing, and hotspots in northeastern regions are also decreasing. (3) Regional economic inequality in China exhibits significant heterogeneity both within and between regions. Differences between eastern, central, western, and northeastern regions contribute significantly to overall inequality. Differences between regions on either side of the Hu Huanyong line remain stable, but north-south differences have intensified, and differences within and outside the Yangtze Basin Economic Belt have expanded. Differences within the Yellow River Basin region remain stable. (4) Both the first and second nature factors exert complex nonlinear impacts on the formation of regional economic inequality. Factors such as industrial agglomeration, globalization, innovation, and distance from the coast show strong explanatory power. The influence of the demand of first nature and the endogenous capacity of second nature is gradually increasing. Based on the above research findings, this paper proposes policy recommendations to promote balanced regional economic development in China.</p>

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Evolution and influencing factors of regional economic inequality in China based on data from nighttime lights

  • 期刊论文

  • 发表日期：

    2025年5月20日

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  • Zuge Xing,
  • Canfei He,
  • Jiale Lin

摘要

Accurately identifying the evolving trends of regional economic inequality is crucial for promoting coordinated regional development and achieving Chinese-style modernization. This paper, based on continuous nighttime light data from 1992 to 2019, uses the Dagum Gini coefficient, emerging hot spot analysis, and XGBoost-SHAP interpretable machine learning models to analyze the spatiotemporal evolution of multi-scale regional economic inequality in China, as well as the spatial cold spots and hot spots and inter-regional and intra-regional inequalities among different subregions. It also reveals the impact contributions of natural and economic factors on regional economic inequality. The results show that: (1) During the study period, provincial-level economic inequality in China gradually increased before 2003 and then decreased afterward. After 2012, the decline at the provincial level slowed down, while city-level and county-level economic inequality slightly increased. (2) The Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta city clusters remain persistent nighttime light hotspots. Multiple eastern and central city clusters are gradually becoming new hotspots, while cold spots in western regions are decreasing, and hotspots in northeastern regions are also decreasing. (3) Regional economic inequality in China exhibits significant heterogeneity both within and between regions. Differences between eastern, central, western, and northeastern regions contribute significantly to overall inequality. Differences between regions on either side of the Hu Huanyong line remain stable, but north-south differences have intensified, and differences within and outside the Yangtze Basin Economic Belt have expanded. Differences within the Yellow River Basin region remain stable. (4) Both the first and second nature factors exert complex nonlinear impacts on the formation of regional economic inequality. Factors such as industrial agglomeration, globalization, innovation, and distance from the coast show strong explanatory power. The influence of the demand of first nature and the endogenous capacity of second nature is gradually increasing. Based on the above research findings, this paper proposes policy recommendations to promote balanced regional economic development in China.