Abstract
Urban shrinkage has emerged as a widespread phenomenon globally and has a significant impact on land, particularly in terms of land use and price. This study focuses on 2851 county-level cities in China in 2005–2018 (excluding Hong Kong, Macao, Taiwan, and ‘no data’ areas in Qinhai-Tibet Plateau) as the fundamental units of analysis. By employing nighttime light (NTL) data to identify shrinking cities, the propensity score matching (PSM) model was used to quantitatively examine the impact of shrinking cities on land prices, and evaluate the magnitude of this influence. The findings demonstrate the following: 1) there were 613 shrinking cities in China, with moderate shrinkage being the most prevalent and severe shrinkage being the least. 2) Regional disparities are evident in the spatial distribution of shrinking cities, especially in areas with diverse terrain. 3) The spatial pattern of land price exhibits a significant correlated to the economic and administrative levels. 4) Shrinking cities significantly negatively impact on the overall land price (ATT = −0.1241, P < 0.05). However, the extent of the effect varies significantly among different spatial regions. This study contributes novel insights into the investigation of land prices and shrinking cities, ultimately serving as a foundation for government efforts to promote the sustainable development of urban areas.
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All authors contributed to the study conception and design. WANG Xiaohui: methodology, software, writing-original draft; PENG Li: writing-review and editing, supervision; HUANG Kexin: data curation, visualization; DENG Wei: conceptualization, supervision.
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Foundation item: Under the auspices of National Natural Science Foundation of China (No. 42071222, 41771194)
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Understanding the Relationship Between Shrinking Cities and Land Prices: Spatial Pattern, Effectiveness, and Policy Implications
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Wang, X., Peng, L., Huang, K. et al. Understanding the Relationship Between Shrinking Cities and Land Prices: Spatial Pattern, Effectiveness, and Policy Implications. Chin. Geogr. Sci. 34, 1–18 (2024). https://doi.org/10.1007/s11769-023-1390-9
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DOI: https://doi.org/10.1007/s11769-023-1390-9