LAUSR

People migrate between places constantly, promoting population redistribution and socioeconomic element flows. Since China’s interprovincial population migration flows are highly concentrated in particular places and there are comparatively few studies using a spatial concentration perspective in this field, there is room for a spatial analysis. The Gini Index (GI) is commonly used in analysing the concentration of topological data, and it works well with migration flow data. Also, GI is scale-invariant due to its normalized nature, and hence it is readily interpretable. However, due to missing data, the traditional GI specification is often an underestimate. Thus, the authors propose the GIc for better standardisation, and demonstrate its utility in the characterization of interprovincial migration flows in China from 1985 to 2015, quantifying the spatial concentration of migration. The results indicate that (a) the GIc measures the concentration degree of population migration better; (b) collectively, the concentration is consistently high, and it shows a trend in an inverse U-shape over six periods, and there are strong linkages between regions with high origin GIcs and regions with high destination GIcs; (c) since 1995, the concentration at migration origins is high in middle China and some western regions; migration destinations with high concentration are the Yangtze River Delta and the Pearl River Delta, which show a smooth temporal change; (d) origins with high concentration are often connected to destinations with high concentration by strong migration flows that move large populations.