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Multidimensional Spatiotemporal Correlation Effect of County-Scale Population Shrinkage: A Case Study of Northeast China

Author

Listed:
  • Zhixuan Xue

    (School of Geographical Sciences, Harbin Normal University, Harbin 150025, China)

  • Xiangli Wu

    (School of Geographical Sciences, Harbin Normal University, Harbin 150025, China)

  • Yilin Zhang

    (School of Geographical Sciences, Harbin Normal University, Harbin 150025, China)

  • Siji Zhu

    (Faculty of Geography, Yunnan Normal University, Kunming 650500, China)

  • Ni Zhang

    (School of Sociology and Anthropology, Xiamen University, Xiamen 361005, China)

  • Shuhang Zhao

    (School of Geographical Sciences, Harbin Normal University, Harbin 150025, China)

Abstract

There is a mutual causal relationship between population shrinkage and the level of regional social–economic–ecological development and their coordinated development. It is of great significance to reveal the correlation effect between population shrinkage and regional development for the adjustment and optimization of the relationship between regional population and social, economic and ecological development. Taking 142 counties in the three provinces of Northeast China as samples, the population contraction was identified and classified in different segments, and a comprehensive evaluation index system was constructed. The entropy method, coupled coordination model, grey correlation degree model, bivariate spatial autocorrelation model and other analysis methods were used. This paper measures the level of social, economic, ecological and synthetical development and the coordination degree among the three in different periods, and it analyzes the spatio-temporal correlation with population shrinkage. The obstacle degree model is used to analyze the main factors affecting the coordinated development under different population shrinkage levels. The results show that: (1) The number of counties with a shrinking population accounted for 57.04% from 2000 to 2010, showing a “Nearly half of the increase and half of the decrease” situation; from 2010 to 2020, the number of counties with population contraction type accounted for 99.3%, and the region entered a state of comprehensive contraction, and the contraction amplitude increased significantly. (2) From 2000 to 2010, the degree of population shrinkage was negatively correlated with the level of social, economic, synthetical and coordinated development but positively correlated with the level of ecological development. From 2010 to 2020, the degree of population shrinkage was still negatively correlated with the level of social, economic, synthetical and coordinated development, but it is not significantly correlated with the level of ecological development. During the study period, the correlation between population shrinkage and social development level was strong, while that between population shrinkage and ecological development level was weak. (3) During the study period, the social and economic system factors were the main obstacles in the process of coordinated development. From 2000 to 2010, the common important obstacle factors of the three types of population shrinkage level counties were the number of industrial enterprises above designated size, average night light index and gross regional product, and the common main obstacle factor was population density. From 2010 to 2020, the common important obstacle factors of the three types of population shrinking counties were the number of industrial enterprises above designated size and the per capita balance of loans from financial institutions at the end of the year, and the obstacle levels of indicators in different types of population shrinking counties are significantly different.

Suggested Citation

  • Zhixuan Xue & Xiangli Wu & Yilin Zhang & Siji Zhu & Ni Zhang & Shuhang Zhao, 2024. "Multidimensional Spatiotemporal Correlation Effect of County-Scale Population Shrinkage: A Case Study of Northeast China," Sustainability, MDPI, vol. 16(11), pages 1-28, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4498-:d:1402073
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