Acta Geographica Sinica ›› 2016, Vol. 71 ›› Issue (2): 205-.doi: 10.11821/dlxb201602003

• Population and Political Geography • Previous Articles     Next Articles

Multilateral mechanism analysis of interprovincial migration flows in China

Yingxia PU1,2,3(), Hongling HAN4, Ying GE5, Fanhua KONG2,6   

  1. 1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
    2. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    4. College of Business, Linyi University, Linyi 276000, Shandong, China
    5. School of Earth Science and Engineering, Hohai University, Nanjing 210097, China
    6. International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
  • Received:2015-05-14 Revised:2015-08-01 Online:2016-02-15 Published:2016-02-15
  • Supported by:
    National Natural Science Foundation of China, No.41271388;Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD);Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application


Population migration flows between different regions are related to not only the origin- and destination-specific characteristics, but also to the migration flows to and from neighborhoods. Intuitively, changes in the characteristics of a single region will impact both inflows and outflows to and from other regions. In order to explore the spatial interaction mechanism driving the increasing population migration in China, this paper builds the spatial OD model of interprovincial migration flows based on the sixth national population census data and related social-economic data. The findings are as follows: (1) Migration flows show significant autocorrelation effects among origin and destination regions, which means that the migration behavior of migrants in some region is influenced by that of migrants in other places. The positive effects indicate the outflows from an origin or the inflows to a destination tend to cluster in a similar way. Simultaneously, the negative effects suggest the flows from the neighborhood of an origin to the neighborhood of a destination tend to disperse in a dissimilar way. (2) Multilateral effects of the regional economic and social factors through the spatial network system lead to the clustering migration flows across interrelated regions. Distance decay effect plays the most influential force in shaping the patterns of migration flows among all the factors and the negative spillover effect further aggravates the friction of distance. As for destinations, the influence of wage level and migration stocks is beyond that of GDP and the positive spillover effects of these factors enhance the attraction of neighborhood regions. The spillover effects of unemployment rate and college enrollment of higher education are significantly negative while the effect of population in a destination is not significant. As for origins, population and migration stocks lead to positive spillover effects on the neighborhoods while the effects of other factors are negative. (3) Changes in the regional characteristics will potentially lead to a series of events to the whole migration system, and the flows to and from the center of oscillation and its neighborhoods vibrate greatly compared with other regions. The simulation results of 5% GDP increase in Jiangsu province indicate that the outflows to other regions decrease while the inflows from all others increase to some different extent. Comparatively, the influence on the flows to and from the regions neighboring Jiangsu is significant while that of remote regions is much less, which cannot be explained by the traditional gravity model.

Key words: population migration flows, network autocorrelation, multilateral effects, spatial OD model, spatial mechanism analysis, China