Resources Science ›› 2020, Vol. 42 ›› Issue (5): 894-906.doi: 10.18402/resci.2020.05.08

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Influence of “explicit citizenship” and “implicit citizenship” on farmers’ land transfer behavior

XIN Yi1, GONG Weiwen2, ZHAO Yafei1   

  1. 1. School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China;
    2. Beijing Branch of China Development Institute, Beijing 100038, China
  • Received:2019-08-16 Revised:2020-01-07 Online:2020-05-25 Published:2020-07-25


In recent years, the growth rate of rural land transfer in China has shown a continuous downward trend. At the same time, the scale of urban-rural floating population formed by migrants has reached a new high in history. This process of incomplete citizenization of “leave the countryside without leaving behind the land” has hindered the development of land transfer. To examine the influencing mechanism and degree of different states of farmers’ citizenization on their land transfer behavior, this study used a combination of theoretical analysis and empirical econometric modeling. The theoretical concepts of “explicit citizenization” and “implicit citizenization” were proposed to reflect the gradual characteristics of the current farmers’ citizenization process in China, and the structural differences between these two types of citizenization have complex effects on farmers’ land transfer behavior. The conclusions of our study are: (1) The process of farmers’ citizenization has a positive impact on their land transfer behavior. (2) The process of land transfer is a long-term gradual process accompanied by the aging of rural permanent residents. (3) The improvement of urban pension security, land transfer rents, and improvement of farmers’ human capital levels are conducive to promoting farmers’ transfer of land. The results of this study explore the impact of farmers’ citizenization on rural land transfer and related policies.

Key words: land transfer, farmers’ citizenization, explicit citizenization, implicit citizenization, land rent, Logistics regression model, CHIPS2013