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Could the new rural social pension insurance promote farmers' land transfer: Based on three waves panel data of CHARLS (新农保能促进农户土地流转吗?—基于CHARLS三期面板数据)

Yali Zhang*, Yunli Bai, Lin Zhen*, Liangjie Xin

Journal Title: Journal of Natural Resources (自然资源学报)

Volume/Issue/Page: Volume 34, Issue 5, 1016-1026

Published Time: 28 May 2019

Abstract

This paper aims to determine whether the new rural social pension insurance could promote farmland transfer or not based on the China Health and Pension Tracking Survey (CHARLS) database. Fixed-effect model was established by using three waves panel data of households information. The results indicate that the averaged rent out rate and rent in rate of farmland in China was only 14% and 6% (2015), respectively. The rent out rate of farmland increased and the rent in rate decreased, which highlights the phenomenon of farmland centralization in China. There is a wide disparity among regional land transfer in China. The order of rent out in farmland is: Northeast China, Eastern China, Central China, Northwest China, and Southwest China. The rent out rate of farmland is relatively high in the northwest region (9% in 2015) than other regions, of which the rent out rate is about 5%. The new rural social pension insurance plays a significant role in promoting the rent out of farmer over 60 years old. Policy implications can be drawn from the results. Firstly, the rural insurance should be improved to weaken the security function of land, thereby promoting rural land transfer. Secondly, the farmland management system should be reformed in the context of farmland centralization and designed to cultivate a group of new type of farmers. Thirdly, the regionally differentiated farmland management policies should be developed, so as to promote the implementation of land transfer trading platform for the region with more land transfer potential. 

Keywords: land transfer; rent out farmland; rent in farmland; new rural social pension insur- ance; fixed-effect model

Corresponding authors: Yali Zhang, zhangyali@igsnrr.ac.cn, Lin Zhen, zhenl@igsnrr.ac.cn

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