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.

Improving resource allocation efficiency and fostering innovation are important dimensions of sustainable urban economic development. Public data trading platforms may contribute to these objectives by facilitating data circulation, reducing information frictions, and improving the coordination of productive resources. However, empirical evidence on their implications for urban productivity remains limited. This study examines the effects of public data trading platform establishment on urban total factor productivity (TFP), drawing on prefecture-level city panel data from China covering 2010–2024. By exploiting the staggered establishment of these platforms as a quasi-natural experiment, we employ a staggered difference-in-differences (DID) framework to estimate their productivity effects and investigate potential transmission mechanisms. The results indicate that public data trading platform establishment is positively associated with urban TFP after controlling for city and year fixed effects. The findings also reveal a positive association between platform establishment and technological innovation. Further mechanism analyses suggest that high-level human-capital agglomeration and the spatial agglomeration of scientific and technological resources may represent additional pathways linking data-market institutions to urban productivity. These findings highlight the potential role of institutional infrastructure for data exchange in supporting innovation-driven growth and more efficient resource utilization. From a sustainability perspective, the study provides evidence relevant to the socioeconomic and institutional dimensions of sustainable urban development and suggests that policies promoting data accessibility, effective data governance, and complementary innovation capabilities may help strengthen the foundations of long-term urban productivity. The results do not directly measure environmental sustainability and should therefore be interpreted primarily in terms of economic and institutional sustainability.