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Measurement and Spatiotemporal Variation in High-Quality Population Development in the Yangtze River Economic Belt
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Measurement and Spatiotemporal Variation in High-Quality Population Development in the Yangtze River Economic Belt
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Journal Article
Measurement and Spatiotemporal Variation in High-Quality Population Development in the Yangtze River Economic Belt
2024
Overview
High-quality population development is a crucial component of high-quality economic growth and holds significant importance for achieving sustainable development goals and advancing the process of modernization with Chinese characteristics. Combining theories of sustainable population development, and starting from the population elements subsystem and the population support subsystem, this study constructs a comprehensive evaluation index system for high-quality population development by focusing on the following six key dimensions: population size, population quality, population structure, population distribution, population–socioeconomic relations, and population–environment relations. Utilizing the entropy weight–TOPSIS method, the study gauges the extent of high-quality population development within the Yangtze River Economic Belt spanning from 2013 to 2022. The temporal and spatial evolution characteristics and regional disparities of high-quality population development are depicted using methods such as natural breaks, the Dagum Gini coefficient, kernel density estimation, and spatial correlation analysis. Findings reveal the following: (1) The research region demonstrates a notable advancement in high-quality population development, with a gradient structure gradually emerging as “higher in the downstream areas, lower in the upstream regions, and central in the intermediary zones”. (2) The overall disparity exhibits a “V-shaped” upward trend, with significantly higher differences in downstream areas than in upstream and midstream areas. While intra-regional differences are decreasing overall, inter-regional differences are continuously widening, making them the primary driver of the overall disparity. (3) “High–High” and “Low–Low” spatial agglomeration effects are observed in the high-quality population development level within the area of investigation, with a trend towards bipolarization.
Publisher
MDPI AG
