地理学报 ›› 2021, Vol. 76 ›› Issue (3): 753-763.doi: 10.11821/dlxb202103018

• 环境与生态系统服务 • 上一篇    下一篇

中国耕地规模化流转租金的分异特征及其影响因素

徐羽1,2(), 李秀彬1,2(), 辛良杰1   

  1. 1.中国科学院地理科学与资源研究所 中国科学院陆地表层格局与模拟重点实验室,北京 100101
    2.中国科学院大学,北京 100049
  • 收稿日期:2019-09-29 修回日期:2020-11-26 出版日期:2021-03-25 发布日期:2021-05-25
  • 通讯作者: 李秀彬(1962-), 男, 河北固安人, 研究员, 博士生导师, 主要从事土地利用变化研究。E-mail: lixb@igsnrr.ac.cn
  • 作者简介:徐羽(1991-), 男, 江西信丰人, 博士生, 主要从事土地利用变化研究。E-mail: xuy. 17b@igsnrr.ac.cn
  • 基金资助:
    国家自然科学基金项目(41930757);国家自然科学基金项目(41571095);中国科学院重点部署项目(ZDBS-SSW-DQC)

Differentiation of scale-farmland transfer rent and its influencing factors in China

XU Yu1,2(), LI Xiubin1,2(), XIN Liangjie1   

  1. 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-09-29 Revised:2020-11-26 Published:2021-03-25 Online:2021-05-25
  • Supported by:
    National Natural Science Foundation of China(41930757);National Natural Science Foundation of China(41571095);Key Deployment Project of Chinese Academy of Sciences(ZDBS-SSW-DQC)

摘要:

通过土地流转实现规模化经营是农地利用变化的重要趋势,土地规模化流转市场的租金关乎规模经营主体的形成及其可持续发展,但目前对全国层面耕地规模化流转租金的研究还较为欠缺。基于土地流转信息发布平台的2万余宗规模化流转地块,论文揭示了中国耕地规模化流转租金的总体水平与区域差异,并采用分位数回归方法识别地块属性特征对耕地租金分化的影响及异质性。结果表明:全国耕地平均租金为11339.10元/hm2,租金介于≤ 7500元/hm2、7500~15000元/hm2、15000~22500元/hm2、> 22500元/hm2区间的地块数量比例分别为38.93%、37.97%、14.52%和8.59%;云贵高原区和黄淮海平原区租金较高,比全国平均值分别高出32%和23%,而北方干旱半干旱区租金较低,租金约为全国均值的一半。地块质量特征、地块规模化特征、地块区位特征、地块产权特征对耕地租金具有显著的影响;对低租金地块而言,灌溉条件、土地平整度、道路质量的边际效应更大,而邻近高速公路则对高租金地块具有更强的增值效应。为降低农业生产的土地成本,政府应努力降低土地规模化流转过程中的交易成本、减少农业补贴对农地租金的干预、加强农田基础设施建设与农地流转租金的常态化监测。

关键词: 耕地租金, 土地流转, 规模经营, 分位数回归, 影响因素, 中国

Abstract:

Developing large-scale farm management through farmland transfer is an important trend of agricultural land use change in China. The farmland rents regarding large parcels have profound impacts on the establishment of large farms and their sustainable development, however, there is still a lack of systematic monitoring and research on the rent of large consolidated land at the national level. Based on more than 20000 farmland parcels collected from the most influential land transfer information releasing platform (www.tuliu.com) in China, this paper reveals the overall picture and regional differences of farmland transfer price, and employs the quantile regression method to identify the impacts of parcel attributes on farmland rent differentiation and their heterogeneity. The results show that the average and median of scale-farmland rent are 11339.10 yuan per hectare and 9511.95 yuan per hectare, respectively. The farmland rents were further divided into four levels, namely, ≤ 7500 yuan per hectare, 7500~15000 yuan per hectare, 15000~22500 yuan per hectare and > 22500 yuan per hectare. According to this classification, the proportions of parcels in different rent ranges are 38.93%, 37.97%, 14.52% and 8.59%, respectively. Regarding regional difference, the farmland rents in the Yunnan-Guizhou Plateau and Huang-Huai-Hai Plain are relatively high, 32% and 23% higher than the national average respectively, while the rent in the arid and semiarid regions of northern China was relatively low, which was about half of the national average. Quantile regression results show that land quality, land suitability for large-scale farming operation, land location and land property attributes exert significant impacts on farmland rent. In particular, for lower-rent parcels, the marginal effects of irrigation availability, land flatness and road quality are stronger. However, expressway proximity has a stronger value-added effect on these higher-rent parcels. To reduce the farmland cost of agricultural production in China, the governments at all levels should continue to reduce transaction costs, set up market-based land rent mechanisms, strengthen the construction of farmland infrastructure, and establish a price monitoring system for large-scale land circulation.

Key words: farmland rent, farmland transfer, scale farming operation, quantile regression, influencing factor, China