This study explores the spatial effect of infrastructure development on real estate prices in the Yangtze River Delta. It constructs an evaluation system of the infrastructure development level across five dimensions (i.e., transportation, water supply and drainage, energy and power, postal communication, and ecological environment), analyzes the development characteristics of urban infrastructure in the Yangtze River Delta, and uses a spatial panel model to explore how urban infrastructure development affects real estate prices. Results indicate that (1) the overall development level of urban infrastructure in the Yangtze River Delta region shows an upward trend. Significant regional differences exist as the development level of urban infrastructure in the eastern region is ahead of that in the central region; (2) Spatial autocorrelation and real estate prices in the Yangtze River Delta region in infrastructure development and overall levels, respectively, are high; (3) Infrastructure directly affects local real estate market demand and improves the vitality of the housing market in adjacent areas; and (4) Infrastructure construction can significantly promote the rise of urban real estate prices in the eastern region, while this driving effect is not significant in the central region. This research will help the government promote the coordinated development of urban infrastructure and formulate relevant policies for the macro-control of the real estate market in urban agglomerations.
Railway carbon emissions reduction is of great significance. In this study, carbon emission efficiency in railway transportation in China’s 31 provinces is measured for 2006–2019 based on an unexpected output slack-based measure (SBM) model. A gravity matrix of the spatial correlation network for carbon emission efficiency is constructed using the modified gravity model, the spatial network structure is explored using social network analysis, and the factors influencing the spatial network are analyzed using the quadratic assignment procedure (QAP) model. Based on the results, several conclusions can be drawn: (1) the carbon emissions efficiency of railway transportation in China increased periodically during the study period, but there are still great differences between regions. (2) The carbon emission efficiency in railway transportation shows significant characteristics of spatial correlation networks. (3) The inter-provincial associations gradually increased, while there are still large regional differences in the spatial correlation network. (4) Differences in spatial adjacency, economic development and scientific and technological advancement have significant positive impacts on the spatial correlation network. This research will help policy makers formulate relevant policies to promote the regional coordinated development of low-carbon railway transportation.
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