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Abstract Human migration is a direct indicator of rural attraction. As the world's most populous nation, China is experiencing a rural population decline. The government is actively focusing on a rural revitalization strategy to make rural areas sustainable. Based on data from the sixth census in 2010, this paper applies the Moran's I method and spatial lag regression model to analyze the spatial pattern and driving factors of China's rural migration. The main conclusions are listed as follows. (1) The areas, including the Yangtze River Delta, the Pearl River Delta, and the northwestern areas, were the most attractive destinations for rural migrants. (2) The inter-provincial rural migration pattern is close to the total rural migration pattern, but is different from the intra-provincial pattern. (3) In general, job opportunities in the secondary industry, rural income, rural investment, and the local economic levels were all main drivers for rural migration. The driving mechanisms varied in the eastern, central, and western provinces. To support China's efforts in rural revitalization, regionally different policies, urban-rural integration, and new economic factors are suggested and highlighted from the perspective of rural migration.
Highlights Exploring the spatial pattern and the driving factors of China's rural attraction from the perspective of rural migrants. The areas, including the Yangtze River Delta, the Pearl River Delta and the northwestern areas, were the most attractive destinations. The inter-provincial rural migration pattern is close to the total rural migration pattern, but is different from the intra-provincial pattern. Job opportunities of the secondary industry, rural income and the local economic levels were all main determinants for rural migration. The driving factors varied in eastern, central and western provinces. Regionally different policies, urban-rural integration and new economic factors are suggested for rural migration management.
Abstract Human migration is a direct indicator of rural attraction. As the world's most populous nation, China is experiencing a rural population decline. The government is actively focusing on a rural revitalization strategy to make rural areas sustainable. Based on data from the sixth census in 2010, this paper applies the Moran's I method and spatial lag regression model to analyze the spatial pattern and driving factors of China's rural migration. The main conclusions are listed as follows. (1) The areas, including the Yangtze River Delta, the Pearl River Delta, and the northwestern areas, were the most attractive destinations for rural migrants. (2) The inter-provincial rural migration pattern is close to the total rural migration pattern, but is different from the intra-provincial pattern. (3) In general, job opportunities in the secondary industry, rural income, rural investment, and the local economic levels were all main drivers for rural migration. The driving mechanisms varied in the eastern, central, and western provinces. To support China's efforts in rural revitalization, regionally different policies, urban-rural integration, and new economic factors are suggested and highlighted from the perspective of rural migration.
Highlights Exploring the spatial pattern and the driving factors of China's rural attraction from the perspective of rural migrants. The areas, including the Yangtze River Delta, the Pearl River Delta and the northwestern areas, were the most attractive destinations. The inter-provincial rural migration pattern is close to the total rural migration pattern, but is different from the intra-provincial pattern. Job opportunities of the secondary industry, rural income and the local economic levels were all main determinants for rural migration. The driving factors varied in eastern, central and western provinces. Regionally different policies, urban-rural integration and new economic factors are suggested for rural migration management.
Rural attraction: The spatial pattern and driving factors of China's rural in-migration
Journal of Rural Studies ; 93 ; 461-470
2019-03-10
10 pages
Article (Journal)
Electronic Resource
English
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