Empirical Analysis of Peasant Household Land Outflow Behavior in Major Grain Producing Areas

Abstract:

According to 273 peasant household samples in major grain producing areas of Tieling city, Liaoning province, the paper establishes binary Logistic regression model to analyze the influence factors of peasant household land outflow behavior. It turns out that age, education level, migrant workers number, family economic income structure, non-agricultural employment ability and distance between farmland and county have significant positive correlation with peasant household land outflow behavior, farmland fragmentary degree has significant negative correlation. On this basis, the paper suggests that the government should strengthen peasant household non-agricultural employment ability, change family income structure, broaden the income channels to increase the driving force of land outflow, and perfect the rural social security system, weaken the land safeguard function to reduce the worries of land outflow.

• Periodical: Advanced Materials Research (Volumes 962-965)
• Pages: 2229-2233
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.962-965.2229
• Online since: June 2014
• Authors: Li Shuang Wang, Chun Ping Wang*, Wei Ma
• Keywords: Land Outflow, Logistic Regression Model, Major Grain Producing Areas, Peasant Household Behavior

References

[1] Guanliang Ding. Journal of Zhejiang University (Humanities and Social Science Edition), 2004, 34(3)27-34 (In Chinese).

[2] Yang Yao. Social Sciences in China, 2000, (2): 54-65 (In Chinese).

[3] Dijk T. S. Land Use Policy, 2003, 20(2): 149-158.

[4] Teklu T, Lemi A. Agricultural Economics, 2004, 30(2): 117-128.

[5] Jingqiong Wu. Peasant Household Farmland Transfer Behavioral Research. Hangzhou: Zhejiang University, 2002 (In Chinese).

[6] Taiyang Zhong, Xianjin Huang, Ping Kong. China Land Science, 2005, 19(1): 49-55 (In Chinese).

[7] Xinghuan Han, Lu Tian. Journal of Jilin Agricultural University, 2012, 34 (2): 225-229 (In Chinese).

[8] Jichuan Wang, Zhigang Guo. Logistic Regression Model: Method and Application[M]. Higher Education Press, 2001 (In Chinese).

[9] Information on http: / baike. baidu. com/subview/5451/12525439. htm.