中文摘要：

为探究耕地流转价格的空间结构及其形成机制,该文以河南省耕地流转租金为研究对象,综合运用空间关联分析研究了耕地流转租金的空间集聚状况和空间布局,并通过建立指标体系,采用相关分析和空间计量模型去揭示耕地流转租金空间格局的形成机制。研究结果表明,在全局趋势上,河南省耕地流转租金在东西方向呈现明显的倒＂U＂型,在南北方向上总体呈北高南低的态势;全局Moran’s I达到0.63,表明耕地流转租金在空间上呈现明显的集聚现象;热点分析发现耕地流转租金的热点区和次热点区集中分布在南太行山前平原和豫东平原地区,次冷点区域分布于次热点区外围,冷点区主要布局在豫西伏牛山区和豫东南大别山区;相关分析表明耕地流转租金与耕地平均质量等别、国内生产总值（gross domestic product,GDP）、公共财政预算收入和农民人均纯收入等影响因子具有显著的统计相关性和空间耦合性;空间计量模型结果显示,空间误差模型（spatial error model,SEM）的拟合效果优于空间滞后模型（spatial lag model,SLM）,其中耕地平均质量等别、GDP和农民人均纯收入在模型中分别通过了0.01水平的显著性检验,公共财政预算收入通过了0.05水平的显著性检验;共线性诊断结果显示GDP与公共财政预算收入和农民人均纯收入之间存在共线性,从而解释了GDP在空间计量模型中系数为负的原因;逐步回归分析发现当模型只引入耕地平均质量等别和农民人均纯收入2个变量时达到最优。基于以上分析可知：河南省耕地流转租金在省域空间上并非随机分布,而是呈现很强的空间自相关性;在耕地流转租金空间格局的形成机制上,耕地流转租金受自然和社会经济因素的综合影响,其中耕地平均质量等别和农民人均纯收入较GDP、公共财政预算收入对耕地流转租金的影响更显著。

英文摘要：

In order to explore the spatial distribution and formation mechanism of the cultivated land transfer rent, the spatial agglomeration and spatial layout of the cultivated land transfer rent in Henan Province was studied by applying spatial correlation analysis, such as global spatial autocorrelation analysis and hot spot analysis. Based on the study, the system of driving force indicators was constructed from the field of nature, society and economics according to ＂Regulations for valuation on agricultural land＂, which includes the classification of agricultural land, gross domestic product（GDP）, proportion of the first industry, public revenue, public expenditure, urbanization rate, per capita GDP, and rural per capita net income. Meanwhile, correlation analysis and spatial econometric models were used to reveal the spatial pattern of cultivated land transfer rent and its forming mechanism. The results showed that, in general, the cultivated land transfer rent in Henan Province presented patterns of apparent invert U in the east-west direction and gradually emerged a descending trend from north to south. In the global spatial autocorrelation analysis, Moran＇s index reached 0.63, which indicated that the cultivated land transfer rent showed a significant clustering phenomenon in space, and specifically, the space pattern showed a high-high and low-low clustering. Furthermore, by applying hot spot analysis, it was found that the hot spots and sub hot spots were intensively distributed in the piedmont plain of Taihang Mountains and eastern plain of Henan Province, the sub cold spots in the periphery of the sub hot spots, such as cities of Pingdingshan, Eastern Nanyang and Zhumadian, and the cold spots mostly in Funiu Mountainous region and Dabie Mountainous region. The results of correlation analysis indicated that driving factors, including the classification of agricultural land, GDP, public revenue, urbanization rate, and rural per capita net income, were significantly correlated with the cultivated lan