城市住宅地价时空演变及影响因素研究
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摘要
改革开放以来,我国城镇化水平从1978年的17.92%提高到2011年的51.27%,城市建成区面积由7438.0km2扩张到43603.2km2。在城镇化快速推进过程中,城市以其相对优越的地理区位条件、明确的行业分工协作、便利的交通运输条件和高效的行政服务能力等吸引周边人口向中心集聚,城市人口超越农村人口由1.72亿增加到6.91亿。人口的大量汇集需要在有限的城市土地空间上解决居住问题,于是住宅用地的价格与分布逐渐成为塑造城市时空格局的重要参量,并在时间维、二维地理空间与地价水平所构成的四维空间中不断演化与重构。
城市土地价格是城市土地管理的核心问题,而住宅用地价格又是土地价格中最为敏感、社会反映最强烈的部分。城市住宅用地价格在时间和空间上具有较强的关联性,表现为在时间具有连续性,在空间上具有依赖性。随着城市功能性扩张和结构性调整的推进,住宅地价的时空关系不断演化,并呈现一定的规律,探索和捕捉这种规律信息及其影响机制具有重要意义。本文在对我国城市住宅地价时空差异进行理论分析的基础上,运用ESDA和Hedonic模型对武汉市近十年土地交易数据进行实证研究。ESDA将重点揭示住宅用地的时空演变规律,而Hedonic模型将识别影响地价的特征因素,并对其影响程度进行测度。本文在以下5个方面获得一些重要结论：
(1)文献综述表明国内外对城市住宅地价时空演变机制及其影响因素的研究已经较为充分。城市住宅地价时空演变的动力机制主要来自内在传导机制和外在冲击机制,并且土地投机是城市住宅地价时空演变不可忽视的驱动因素。各国学者对影响因素的研究则主要从不同的分类体系展开。文献分析也揭示国内研究在研究方式、研究数据、研究技术手段和研究对象上存在一定的缺陷。
(2)从我国政府对住宅土地市场干预的行为特征来看,更符合理性“经济人”的角色定位,政府凭借其在定价中的完全话语权和在配置中的决策导向权,驱动着城市住宅地价呈现出明显的时间增长和空间分异特征。从城市住宅地价时空演变的理论依据来看,其在时间上增长满足供给与需求理论,政府在不同阶段对土地商品属性的认知程度和采取的供地策略的转变是导致住宅地价上涨的内生原因,而制度变迁过程中各级政府行为取向的非均衡和国家宏观经济的强势拉动是推动住宅地价上涨的外生原因；在不同尺度的空间迁移上满足竞价租金理论、亨利·乔治定理和特征价格理论,竞价租金理论能够合理地解释城市住宅地价的区位差异,亨利·乔治定理则对住宅邻里地价具有决定作用,特征价格理论可以将各个地块的地价差异性地表现出来。
(3)本文从研究数据的空间关联性以及时间序列的完整性出发,选取2003-2011年武汉市主城区出让的住宅用地和部分商住综合用地案例进行实证研究。在经过数据的录入、筛选、商住综合用地地价分摊、时间修正、缺值处理、异常点排除等处理后形成308个有效样点。统计分析表明样点总体分布存在一定的空间差异性,且比标准正态分布更陡峭,表现为尖峰分布。
(4)GIS技术支持下的武汉市住宅地价时空演变特征研究表明：①从十地政策演化和市场运行状况来看,武汉市住宅土地市场大致经历了1992-1998年、1999-2005年以及2006-2011年三个阶段。从交易案例的时间特征来看,2003-2008年间处于一个高值波动期,2009-2011年是住宅市场的高速发展时期；从交易案例的区域特征来看,洪山区在2003-2011年间成交的住宅用地数量最多为75宗,青山区最少仅为19宗；从交易案例的环线特征来看,2003-2011年59.09%的交易案例发生在二环线与三环线之间,并且从2008年开始住宅土地出让的重心逐步由二环内开始向三环转移；从交易案例的动态演化特征来看,2003-2011年住宅交易案例与参照点的平均距离由6.04km增加到8.73km,年均向外扩展0.30km；②住宅地价的全局空间自相关指数Moran's I表明“招拍挂”机制运行以来,总体上武汉市住宅地价呈现出某种空间相关性,而CV值则进一步揭示地价的空间差异由以往的低值集聚逐步向高值集聚转变；局部空间自相关Moran散点图表明武汉市住宅地价的空间关联性随着时间的推移不断加强,而LISA集聚图则显示两处住宅“热点”分别分布在汉口旧城组团以及中南组团,两处“冷点”分别在严西湖周围和黄家湖周围；③住宅地价空间自相关的各向异性分析表明,半变异函数在0°、45°、90°和135°四个方向上表现出带状向异性特征,且变程大都在12～15km左右；住宅地价空间自相关的各向同性分析表明,武汉市住宅地价最佳拟合模型为指数模型,其空间自相关范围为11.16km,而Co/(Co+C)值的大小表明武汉市住宅地价的空间变异46.2%由随机因素引起,而53.8%由结构性差异所引起；④地价的等值线图显示武汉市住宅地价的总体圈层模式仍然比较明显,而基于特定基点的剖面分析揭示了武汉市住宅地价既有渐变也有突变,但总体还是呈现从中心向边缘逐渐下降趋势。三个时段的住宅地价插值分析揭示住宅的高值区均聚焦于以传统商业中心为半径的一定范围内,表明现代城市的居住行为并未完全脱离对商服业的依赖,而相邻时段的减法运算则指出在2003-2008年期间武汉市住宅地价的空间演变连续性较强,尚未出现跳跃性的演变特征,2009-2011年期间则有多个局部住宅奇异点已经形成。
(5)基于Hedonic模型的住宅地价影响因素识别和测度研究表明：①采用规范分析与文献总结相结合的方式,对影响武汉市住宅地价的关键因素进行了识别,在对选取的因素进行相关性检验后,最终确定以单位地面价作为因变量,并从区位特征、邻里特征、个别特征和其他特征中选取22个自变量进入模型；②采用最小二乘法对武汉市住宅地价的线性、对数以及半对数三种形式的特征价格模型估计结果表明,对数形式的模型解释能力最强,其所能解释因变量差异的百分比约为58.9%,线性形式的模型的解释能力最差,其所能解释因变量差异的百分比仅为53.9%,半对数模型居于二者之间,其所能解释因变量差异的百分比为55.5%；③对数模型的显著性分析表明,通过模型10%显著性检验的特征变量有13个,说明这是引起武汉市住宅地价差异的主要原因；从系数的符号来看,除宗地形状的符号与预期不一样以及宗地面积为负以外,其余均与预期保持一致；变量的弹性分析则揭示,交易方式的价格弹性最大为62.580,宗地面积的价格弹性最小为-0.078；变量的影响度分析表明,22个变量对住宅地价的影响程度存在差异,对住宅地价影响程度最大的变量是容积率；④典型特征因素的测度研究表明,武汉市住宅地价的总体上涨趋势较为明显,而且地价对时间的敏感性程度较高；城市中心区位价值的空间分析揭示,城市中心对住宅地价的影响并不具备明显的时间特征,但对住宅地价的影响存在明显的空间梯度效应；轨道交通对住宅地价的空间影响范围在500m左右,并且其运营期间对住宅地价的影响要明显高于工程建设期；湖泊公园对住宅地价的影响范围为400m,并且其空间影响效应随着距离的变化并不是均匀的,而是存在一定的梯度差异；容积率对单位地面价的影响要比对楼面地价的影响敏感得多,并且其对地价的影响表现为从中心到外围逐步衰减。
国内关于城市住宅地价时空演变及影响因素的系统研究还比较缺乏,我国城市住宅市场成长于经济快速发展的转型年代,具有明显的制度痕迹,经济的发展和制度的改革引导着城市居住空间的阶段性演变。因此,本文在总结现有研究存在不足的基础上,对我国城市住宅地价时空演变的内在机理进行分析,进而以武汉市中心城区“招拍挂”机制运行以来的住宅用地案例进行实证研究。该成果不仅有助于深化和完善学科理论体系和指导今后实证研究,而且将为城市土地资源的优化配置和房地市场调控提供理论和实践指导。
The level of urbanization in China increased from17.92%in1978to51.27%in2011, and the urban built-up area expanded from7438.0km2to43603.2km2, since the reform and development. Urban with its relatively privileged geographic location conditions, specific industry division of work, convenient transportation conditions and efficient administrative services ability to attract the surrounding population concentrate to the center in the rapid progress of urbanization, and urban population exceeded the rural population from172million to691million. The large collection of the population need to solve the housing problem in the limited space on city land, so the price and distribution of residential land becoming an important parameter of shaping the tempo-spatial pattern of the city, and evolving and reconstructing in a four-dimensional space:time-dimension, two-dimensional geospatial and the level of land price.
The tempo-spatial pattern of urban residential land price evolved with some regularity in the driving of various factors, explore and capture the information and its impact mechanisms of this law has an important significance. This paper used the land transaction data of nearly a decade of Wuhan as a empirical study with the application of ESDA and Hedonic model based on the theoretical analysis of the tempo-spatial differences of China's urban residential land price. ESDA focus on revealed the tempo-spatial evolution law of the residential land and Hedonic model can identify the characteristic factors that affect the land price and can measure the degree of the influence. Some important conclusions obtained in the following five aspects:
(1) The literature review showed that the research of mechanisms and its influencing factors of urban residential land price tempo-spatial evolution has been more fully at home and abroad. The dynamic mechanisms of urban residential land price tempo-spatial evolution are mainly from the intrinsic conduction mechanism and external shock mechanism, and at the same time, land speculation is a driving factor of urban residential land price tempo-spatial evolution that can not be ignored. The researches of the influencing factors are mainly expanded from different classification system by scholars from various countries. The literature analysis also reveals that domestic researches have certain defects on research methods, research data, research technical means and research objects.
(2) View from our government intervention behavioral characteristics of the residential land market, its more coincidence with rational "economic man" role, government by virtue of its full right to speak in the pricing and decision-oriented rights in configuration, driven urban residential land price presented a significant characteristics in the time growth and space differentiation. View from the theoretical basis of the urban residential land price tempo-spatial evolution, its growth in time meet the supply and demand theory, the awareness level of the land product attributes and the transition of land provide strategy to take for government at different stages are the intrinsic reasons which lead the growth of residential land price, and the non-equilibrium of government behavior in all levels and national macroeconomic strong pull in the process of institutional change is the external reasons to promote residential land prices grow. Space migration in different scales meet the Bid Rent theory, Henry George theorem and Hedonic theory, Bid Rent theory can reasonably explain the differences in location of the urban residential land price, Henry George theorem played a decisive role in the residential neighborhood land price, Hedonic theory can differently manifest the land price of various plots.
(3) This paper started from the spatial correlation of the research data and the integrity of time sequence, selected the sell residential land and commercial and residential land case of the main city of Wuhan during the year2003-2011as an empirical study. Through data entry, screening, commercial and residential land price sharing, time correction, the handling of missing values, outliers exclusion, formed308valid samples. Statistical analysis showed that the overall sample point distribution has a certain amount of space differences, and steeper than the standard normal distribution, performance as spike distribution.
(4) The characteristics of Wuhan residential land price tempo-spatial evolution studies that supported buy GIS shows that:①View from the evolution of land policy and the operation situation of the market, the residential land market in Wuhan roughly experienced three stages:1992-1998,1999-2005and2006-2011. View from the time characteristics of the transaction cases, between2003and2008is a high-value fluctuation period,2009-2011is a rapid development period of the residential market. View from the regional characteristics of the transaction cases, the number of residential land transactions in Hongshan District is the largest which up to75and in Qingshan District the number is the smallest which only19. View from the ring characteristics of the trading case,59.09percent of the trading cases occurred between the Second Ring and Third Ring in the2003-2011period, and the center of the residential land transaction has transferred gradually from within the Second Ring to Third Ring since2008. View from the dynamic evolution characteristics of residential land transaction cases, the average distance between residential land transaction cases and the reference point increased from6.04km to8.73km in the2003-2011period, and the annual outward expansion has reached0.30km;②The global spatial autocorrelation index of residential land price Moran's I shows that Since the operation of "Bid Invitation, Auction and Listing system" mechanism, residential land price in Wuhan showing a certain space correlation in general, the CV value further reveals that the spatial difference of residential land price gradually transition from low value agglomeration to high value agglomeration; Local spatial autocorrelation Moran scatter plot shows that the spatial correlation of Wuhan residential land price continue to strengthen over time, the LISA shows that the two residential "hot spots" were distributed in Hankou old city district and Zhongnan district, two "cold spots" were around the Yanxi Lake and the Huangjia lake;③The anisotropic analysis of residential land prices spatial autocorrelation shows that the semivariogram at0°,45°,90°and135°four directions on the performance of ribbon anisotropic characteristics, and most of the change process in about12～15km. The anisotropic analysis of residential land prices spatial autocorrelation also shows that best-fit model for Wuhan residential land price is the index model, its spatial autocorrelation range is11.16km, while the value of Co/(Co+C) shows that the spatial variability of Wuhan residential land prices by46.2%caused by random factors, while53.8%was caused by structural differences.④The price contour map shows that the overall circle mode of Wuhan residential land prices are still quite obvious, based on the specific basis points in a cross-sectional analysis reveals residential land price showed both gradient and mutation in Wuhan, but still showed a gradually declining trend. The three periods residential land price interpolation analysis reveals the high value of residential area focus on traditional commercial center for the radius within a certain range, shows that modern urban living behavior has not completely out of the dependence on the commercial services industry. The adjacent period subtraction put out that the space evolution of residential land price in Wuhan showed a strong continuity in2003-2008period, yet appeared leap of evolution characterized, but in2009-2011period, multiple local residential singular points have been formed.
(5) The research of influencing factors to identify and measure for residential land price based on Hedonic model shows that:①With the way which combine normative analysis with literature concluding, identified the key that factors affecting residential land price in Wuhan, Through correlation test of selected factors, ultimately determine use the unit floor price as the dependent variable, and selected22independent variables into the model from the locational characteristics, neighborhood characteristics, individual characteristics, and other characteristics.②The estimation results which use least squares method with three forms of linear, logarithmic and semi-logarithmic Hedonic model of residential land price in Wuhan shows that, the logarithmic form model about the percentage differences in the dependent variable, it can explain58.9%, the linear form model is the worst explanatory power, it can explain only53.9%, semi-logarithmic form model is between the two, it can explain55.5%.③The significant analysis of logarithmic model shows that13characteristic variables can through the model significantly in10%of the test, shows that these are the main reason caused the residential land price differences in Wuhan. View from the sign of the coefficient, except for sign of parcel shape is not the same as expected, and the area of the parcel is negative, the rest are in accord with expected. The variable elastic analysis reveals that the maximum price elasticity is transactions, it is up to62.580, the minimum price elasticity is parcel area, it is-0.078; The degree of variables affect analysis shows that22variables had differences in the degree of influence the residential land price, volume rate was the greatest variable that influence the residential land price.④The typical characteristic factors Measure study shows that the upward trend of residential land prices in Wuhan is obvious, and the land price had a higher sensitivity to time. The space analysis of the city center location value reveals that residential land price of the city center does not have the obvious characteristics of the time, but there is obvious spatial gradient effect of the impact on residential land price. The space sphere of the influence of rail traffic on residential land price in about500m, and its impact on residential land price during operations was significantly higher than the construction period. The range of the impact which lakes and parks on residential land price is400m, and its space effect is not uniform as the distance changes, but there is a certain gradient differences. The impact of volume rate to ground price is much more sensitive than its to floor area price, and the price performance attenuation gradually from the center to the periphery.
The systematic study of the tempo-spatial evolution of urban residential land price and its influencing factors is relatively lack in the domestic. The urban residential land market grows in the transition era of rapid economic development, and has obvious traces of the system, the continuous adjustment of policies guide the phased evolution of urban residential space. Therefore, this paper analyzed the internal mechanism of the tempo-spatial evolution of urban residential land price in China from the perspective of the government action, and examined the economic functions of the government in the regulation of residential land price, then took Wuhan City residential land case since the operation of "Bid Invitation, Auction and Listing system" mechanism as empirical research. The results can not only help to deepen and improve disciplines theoretical system and provide guidance for future empirical research, and will provide guidance for the optimization of urban land resources and regulation of real estate market in both theory and practice.
城市土地价格是城市土地管理的核心问题,而住宅用地价格又是土地价格中最为敏感、社会反映最强烈的部分。城市住宅用地价格在时间和空间上具有较强的关联性,表现为在时间具有连续性,在空间上具有依赖性。随着城市功能性扩张和结构性调整的推进,住宅地价的时空关系不断演化,并呈现一定的规律,探索和捕捉这种规律信息及其影响机制具有重要意义。本文在对我国城市住宅地价时空差异进行理论分析的基础上,运用ESDA和Hedonic模型对武汉市近十年土地交易数据进行实证研究。ESDA将重点揭示住宅用地的时空演变规律,而Hedonic模型将识别影响地价的特征因素,并对其影响程度进行测度。本文在以下5个方面获得一些重要结论：
(1)文献综述表明国内外对城市住宅地价时空演变机制及其影响因素的研究已经较为充分。城市住宅地价时空演变的动力机制主要来自内在传导机制和外在冲击机制,并且土地投机是城市住宅地价时空演变不可忽视的驱动因素。各国学者对影响因素的研究则主要从不同的分类体系展开。文献分析也揭示国内研究在研究方式、研究数据、研究技术手段和研究对象上存在一定的缺陷。
(2)从我国政府对住宅土地市场干预的行为特征来看,更符合理性“经济人”的角色定位,政府凭借其在定价中的完全话语权和在配置中的决策导向权,驱动着城市住宅地价呈现出明显的时间增长和空间分异特征。从城市住宅地价时空演变的理论依据来看,其在时间上增长满足供给与需求理论,政府在不同阶段对土地商品属性的认知程度和采取的供地策略的转变是导致住宅地价上涨的内生原因,而制度变迁过程中各级政府行为取向的非均衡和国家宏观经济的强势拉动是推动住宅地价上涨的外生原因；在不同尺度的空间迁移上满足竞价租金理论、亨利·乔治定理和特征价格理论,竞价租金理论能够合理地解释城市住宅地价的区位差异,亨利·乔治定理则对住宅邻里地价具有决定作用,特征价格理论可以将各个地块的地价差异性地表现出来。
(3)本文从研究数据的空间关联性以及时间序列的完整性出发,选取2003-2011年武汉市主城区出让的住宅用地和部分商住综合用地案例进行实证研究。在经过数据的录入、筛选、商住综合用地地价分摊、时间修正、缺值处理、异常点排除等处理后形成308个有效样点。统计分析表明样点总体分布存在一定的空间差异性,且比标准正态分布更陡峭,表现为尖峰分布。
(4)GIS技术支持下的武汉市住宅地价时空演变特征研究表明：①从十地政策演化和市场运行状况来看,武汉市住宅土地市场大致经历了1992-1998年、1999-2005年以及2006-2011年三个阶段。从交易案例的时间特征来看,2003-2008年间处于一个高值波动期,2009-2011年是住宅市场的高速发展时期；从交易案例的区域特征来看,洪山区在2003-2011年间成交的住宅用地数量最多为75宗,青山区最少仅为19宗；从交易案例的环线特征来看,2003-2011年59.09%的交易案例发生在二环线与三环线之间,并且从2008年开始住宅土地出让的重心逐步由二环内开始向三环转移；从交易案例的动态演化特征来看,2003-2011年住宅交易案例与参照点的平均距离由6.04km增加到8.73km,年均向外扩展0.30km；②住宅地价的全局空间自相关指数Moran's I表明“招拍挂”机制运行以来,总体上武汉市住宅地价呈现出某种空间相关性,而CV值则进一步揭示地价的空间差异由以往的低值集聚逐步向高值集聚转变；局部空间自相关Moran散点图表明武汉市住宅地价的空间关联性随着时间的推移不断加强,而LISA集聚图则显示两处住宅“热点”分别分布在汉口旧城组团以及中南组团,两处“冷点”分别在严西湖周围和黄家湖周围；③住宅地价空间自相关的各向异性分析表明,半变异函数在0°、45°、90°和135°四个方向上表现出带状向异性特征,且变程大都在12～15km左右；住宅地价空间自相关的各向同性分析表明,武汉市住宅地价最佳拟合模型为指数模型,其空间自相关范围为11.16km,而Co/(Co+C)值的大小表明武汉市住宅地价的空间变异46.2%由随机因素引起,而53.8%由结构性差异所引起；④地价的等值线图显示武汉市住宅地价的总体圈层模式仍然比较明显,而基于特定基点的剖面分析揭示了武汉市住宅地价既有渐变也有突变,但总体还是呈现从中心向边缘逐渐下降趋势。三个时段的住宅地价插值分析揭示住宅的高值区均聚焦于以传统商业中心为半径的一定范围内,表明现代城市的居住行为并未完全脱离对商服业的依赖,而相邻时段的减法运算则指出在2003-2008年期间武汉市住宅地价的空间演变连续性较强,尚未出现跳跃性的演变特征,2009-2011年期间则有多个局部住宅奇异点已经形成。
(5)基于Hedonic模型的住宅地价影响因素识别和测度研究表明：①采用规范分析与文献总结相结合的方式,对影响武汉市住宅地价的关键因素进行了识别,在对选取的因素进行相关性检验后,最终确定以单位地面价作为因变量,并从区位特征、邻里特征、个别特征和其他特征中选取22个自变量进入模型；②采用最小二乘法对武汉市住宅地价的线性、对数以及半对数三种形式的特征价格模型估计结果表明,对数形式的模型解释能力最强,其所能解释因变量差异的百分比约为58.9%,线性形式的模型的解释能力最差,其所能解释因变量差异的百分比仅为53.9%,半对数模型居于二者之间,其所能解释因变量差异的百分比为55.5%；③对数模型的显著性分析表明,通过模型10%显著性检验的特征变量有13个,说明这是引起武汉市住宅地价差异的主要原因；从系数的符号来看,除宗地形状的符号与预期不一样以及宗地面积为负以外,其余均与预期保持一致；变量的弹性分析则揭示,交易方式的价格弹性最大为62.580,宗地面积的价格弹性最小为-0.078；变量的影响度分析表明,22个变量对住宅地价的影响程度存在差异,对住宅地价影响程度最大的变量是容积率；④典型特征因素的测度研究表明,武汉市住宅地价的总体上涨趋势较为明显,而且地价对时间的敏感性程度较高；城市中心区位价值的空间分析揭示,城市中心对住宅地价的影响并不具备明显的时间特征,但对住宅地价的影响存在明显的空间梯度效应；轨道交通对住宅地价的空间影响范围在500m左右,并且其运营期间对住宅地价的影响要明显高于工程建设期；湖泊公园对住宅地价的影响范围为400m,并且其空间影响效应随着距离的变化并不是均匀的,而是存在一定的梯度差异；容积率对单位地面价的影响要比对楼面地价的影响敏感得多,并且其对地价的影响表现为从中心到外围逐步衰减。
国内关于城市住宅地价时空演变及影响因素的系统研究还比较缺乏,我国城市住宅市场成长于经济快速发展的转型年代,具有明显的制度痕迹,经济的发展和制度的改革引导着城市居住空间的阶段性演变。因此,本文在总结现有研究存在不足的基础上,对我国城市住宅地价时空演变的内在机理进行分析,进而以武汉市中心城区“招拍挂”机制运行以来的住宅用地案例进行实证研究。该成果不仅有助于深化和完善学科理论体系和指导今后实证研究,而且将为城市土地资源的优化配置和房地市场调控提供理论和实践指导。
The level of urbanization in China increased from17.92%in1978to51.27%in2011, and the urban built-up area expanded from7438.0km2to43603.2km2, since the reform and development. Urban with its relatively privileged geographic location conditions, specific industry division of work, convenient transportation conditions and efficient administrative services ability to attract the surrounding population concentrate to the center in the rapid progress of urbanization, and urban population exceeded the rural population from172million to691million. The large collection of the population need to solve the housing problem in the limited space on city land, so the price and distribution of residential land becoming an important parameter of shaping the tempo-spatial pattern of the city, and evolving and reconstructing in a four-dimensional space:time-dimension, two-dimensional geospatial and the level of land price.
The tempo-spatial pattern of urban residential land price evolved with some regularity in the driving of various factors, explore and capture the information and its impact mechanisms of this law has an important significance. This paper used the land transaction data of nearly a decade of Wuhan as a empirical study with the application of ESDA and Hedonic model based on the theoretical analysis of the tempo-spatial differences of China's urban residential land price. ESDA focus on revealed the tempo-spatial evolution law of the residential land and Hedonic model can identify the characteristic factors that affect the land price and can measure the degree of the influence. Some important conclusions obtained in the following five aspects:
(1) The literature review showed that the research of mechanisms and its influencing factors of urban residential land price tempo-spatial evolution has been more fully at home and abroad. The dynamic mechanisms of urban residential land price tempo-spatial evolution are mainly from the intrinsic conduction mechanism and external shock mechanism, and at the same time, land speculation is a driving factor of urban residential land price tempo-spatial evolution that can not be ignored. The researches of the influencing factors are mainly expanded from different classification system by scholars from various countries. The literature analysis also reveals that domestic researches have certain defects on research methods, research data, research technical means and research objects.
(2) View from our government intervention behavioral characteristics of the residential land market, its more coincidence with rational "economic man" role, government by virtue of its full right to speak in the pricing and decision-oriented rights in configuration, driven urban residential land price presented a significant characteristics in the time growth and space differentiation. View from the theoretical basis of the urban residential land price tempo-spatial evolution, its growth in time meet the supply and demand theory, the awareness level of the land product attributes and the transition of land provide strategy to take for government at different stages are the intrinsic reasons which lead the growth of residential land price, and the non-equilibrium of government behavior in all levels and national macroeconomic strong pull in the process of institutional change is the external reasons to promote residential land prices grow. Space migration in different scales meet the Bid Rent theory, Henry George theorem and Hedonic theory, Bid Rent theory can reasonably explain the differences in location of the urban residential land price, Henry George theorem played a decisive role in the residential neighborhood land price, Hedonic theory can differently manifest the land price of various plots.
(3) This paper started from the spatial correlation of the research data and the integrity of time sequence, selected the sell residential land and commercial and residential land case of the main city of Wuhan during the year2003-2011as an empirical study. Through data entry, screening, commercial and residential land price sharing, time correction, the handling of missing values, outliers exclusion, formed308valid samples. Statistical analysis showed that the overall sample point distribution has a certain amount of space differences, and steeper than the standard normal distribution, performance as spike distribution.
(4) The characteristics of Wuhan residential land price tempo-spatial evolution studies that supported buy GIS shows that:①View from the evolution of land policy and the operation situation of the market, the residential land market in Wuhan roughly experienced three stages:1992-1998,1999-2005and2006-2011. View from the time characteristics of the transaction cases, between2003and2008is a high-value fluctuation period,2009-2011is a rapid development period of the residential market. View from the regional characteristics of the transaction cases, the number of residential land transactions in Hongshan District is the largest which up to75and in Qingshan District the number is the smallest which only19. View from the ring characteristics of the trading case,59.09percent of the trading cases occurred between the Second Ring and Third Ring in the2003-2011period, and the center of the residential land transaction has transferred gradually from within the Second Ring to Third Ring since2008. View from the dynamic evolution characteristics of residential land transaction cases, the average distance between residential land transaction cases and the reference point increased from6.04km to8.73km in the2003-2011period, and the annual outward expansion has reached0.30km;②The global spatial autocorrelation index of residential land price Moran's I shows that Since the operation of "Bid Invitation, Auction and Listing system" mechanism, residential land price in Wuhan showing a certain space correlation in general, the CV value further reveals that the spatial difference of residential land price gradually transition from low value agglomeration to high value agglomeration; Local spatial autocorrelation Moran scatter plot shows that the spatial correlation of Wuhan residential land price continue to strengthen over time, the LISA shows that the two residential "hot spots" were distributed in Hankou old city district and Zhongnan district, two "cold spots" were around the Yanxi Lake and the Huangjia lake;③The anisotropic analysis of residential land prices spatial autocorrelation shows that the semivariogram at0°,45°,90°and135°four directions on the performance of ribbon anisotropic characteristics, and most of the change process in about12～15km. The anisotropic analysis of residential land prices spatial autocorrelation also shows that best-fit model for Wuhan residential land price is the index model, its spatial autocorrelation range is11.16km, while the value of Co/(Co+C) shows that the spatial variability of Wuhan residential land prices by46.2%caused by random factors, while53.8%was caused by structural differences.④The price contour map shows that the overall circle mode of Wuhan residential land prices are still quite obvious, based on the specific basis points in a cross-sectional analysis reveals residential land price showed both gradient and mutation in Wuhan, but still showed a gradually declining trend. The three periods residential land price interpolation analysis reveals the high value of residential area focus on traditional commercial center for the radius within a certain range, shows that modern urban living behavior has not completely out of the dependence on the commercial services industry. The adjacent period subtraction put out that the space evolution of residential land price in Wuhan showed a strong continuity in2003-2008period, yet appeared leap of evolution characterized, but in2009-2011period, multiple local residential singular points have been formed.
(5) The research of influencing factors to identify and measure for residential land price based on Hedonic model shows that:①With the way which combine normative analysis with literature concluding, identified the key that factors affecting residential land price in Wuhan, Through correlation test of selected factors, ultimately determine use the unit floor price as the dependent variable, and selected22independent variables into the model from the locational characteristics, neighborhood characteristics, individual characteristics, and other characteristics.②The estimation results which use least squares method with three forms of linear, logarithmic and semi-logarithmic Hedonic model of residential land price in Wuhan shows that, the logarithmic form model about the percentage differences in the dependent variable, it can explain58.9%, the linear form model is the worst explanatory power, it can explain only53.9%, semi-logarithmic form model is between the two, it can explain55.5%.③The significant analysis of logarithmic model shows that13characteristic variables can through the model significantly in10%of the test, shows that these are the main reason caused the residential land price differences in Wuhan. View from the sign of the coefficient, except for sign of parcel shape is not the same as expected, and the area of the parcel is negative, the rest are in accord with expected. The variable elastic analysis reveals that the maximum price elasticity is transactions, it is up to62.580, the minimum price elasticity is parcel area, it is-0.078; The degree of variables affect analysis shows that22variables had differences in the degree of influence the residential land price, volume rate was the greatest variable that influence the residential land price.④The typical characteristic factors Measure study shows that the upward trend of residential land prices in Wuhan is obvious, and the land price had a higher sensitivity to time. The space analysis of the city center location value reveals that residential land price of the city center does not have the obvious characteristics of the time, but there is obvious spatial gradient effect of the impact on residential land price. The space sphere of the influence of rail traffic on residential land price in about500m, and its impact on residential land price during operations was significantly higher than the construction period. The range of the impact which lakes and parks on residential land price is400m, and its space effect is not uniform as the distance changes, but there is a certain gradient differences. The impact of volume rate to ground price is much more sensitive than its to floor area price, and the price performance attenuation gradually from the center to the periphery.
The systematic study of the tempo-spatial evolution of urban residential land price and its influencing factors is relatively lack in the domestic. The urban residential land market grows in the transition era of rapid economic development, and has obvious traces of the system, the continuous adjustment of policies guide the phased evolution of urban residential space. Therefore, this paper analyzed the internal mechanism of the tempo-spatial evolution of urban residential land price in China from the perspective of the government action, and examined the economic functions of the government in the regulation of residential land price, then took Wuhan City residential land case since the operation of "Bid Invitation, Auction and Listing system" mechanism as empirical research. The results can not only help to deepen and improve disciplines theoretical system and provide guidance for future empirical research, and will provide guidance for the optimization of urban land resources and regulation of real estate market in both theory and practice.
引文
[1]刘卫东,谭韧骠.杭州城市蔓延评估体系及其治理对策[J].地理学报,2009,64(4)：417-425.
[2]许妍,李雪铭,高俊峰,等.近10年来大连城市居住小区时空变动与演化模式[J].地理科学,2009,29(6)：825-832.
[3]陈思源,曲福田,倪绍祥,等.GIS空间分析支持下的城市地价分布研究——以江苏省镇江市为例[J].南京农业大学学报,2005,28(3)：119-122.
[4]宋金平,王恩儒,张文新,等.北京住宅郊区化与就业空间错位[J].地理学报,2007,62(4)：387-396.
[5]曾忠平,卢新海.武汉城市用地结构演变模式研究[J].中国土地科学,2009,23(3)：44-48.
[6]彭建超,吴群.国内外城市地价时空演变研究进展[J].资源科学,2008,30(1)：64-71.
[7]Alonso W. Location and Land Use:Toward a general theory of land use[M]. Cambridge:Harvard University Press,1964.
[8]Clapp J M, Rodriguez M, Kelley Pace R. Residential land values and the decentralization of jobs[J]. The Journal of Real Estate Finance and Economics, 2001,22(1):43-61.
[9]van der Vlist A J, Czamanski D, Folmer H. Immigration and urban housing market dynamics:the case of Haifa[J]. The Annals of Regional Science,2011,47(3):585-598.
[10]Chapin F S, Weiss S F, Donnelly T G. Factors influencing land development: evaluation of inputs for a forecast model[M]. Institute for Research in Social Science, University of North Carolina,1962.
[11]Czamanski S. Effects of public investments on urban land values[J]. Journal of the American Institute of Planners,1966,32(4):204-217.
[12]Wheaton W C. Urban residential growth under perfect foresight[J]. Journal of Urban Economics,1982,12(1):1-21.
[13]Witte A D. The determination of interurban residential site price differences:a derived demand model with empirical testing[J]. Journal of Regional Science, 1975,15(3):351-364.
[14]Follain J R, Jimenez E. Estimating the demand for housing characteristics:A survey and critique[J]. Regional Science and Urban Economics,1985,15(1):77-107.
[15]Segal D, Srinivasan P. The impact of suburban growth restrictions on US housing price inflation,1975--1978[J]. Urban Geography,1985,6(1):14-26.
[16]Hammer T R, Coughlin R E, Horn IV E T. The effect of a large urban park on real estate value[J]. Journal of the American Institute of Planners,1974,40(4):274-277.
[17]Grimes A, Liang Y. Spatial Determinants of Land Prices:Does Auckland's Metropolitan Urban Limit Have an Effect?[J]. Applied Spatial Analysis and Policy, 2009,2(1):23-45.
[18]Ihlanfeldt K R. The effect of land use regulation on housing and land prices[J]. Journal of Urban Economics,2007,61(3):420-435.
[19]杨东峰,熊国平.我国大城市空间增长机制的实证研究及政策建议——经济发展·人口增长·道路交通·土地资源[J].城市规划学刊,2008(3)：51-56.
[20]宋金平,王恩儒,张文新,等.北京住宅郊区化与就业空间错位[J].地理学报,2007,62(4)：387-396.
[21]石忆邵,李木秀.上海市住房价格梯度及其影响因素分析[J].地理学报,2006,61(6)：604-612.
[22]沈悦,刘洪玉.住宅价格与经济基本面：1995—2002年中国14城市的实证研究[J].经济研究,2004(6)：78-86.
[23]阮连法,包洪洁,温海珍.重大事件对城市住宅价格的影响——来自杭州市的证据[J].中国七地科学,2012,26(12)：41-47.
[24]袁雯,朱喜钢,马国强.南京居住空间分异的特征与模式研究——基于南京主城拆迁改造的透视[J].人文地理,2010,,25(2)：65-69.
[25]况伟大.预期、投机与中国城市房价波动[J].经济研究,2010(9)：67-78.
[26]张红霞,谭术魁.城市土地市场调控政策工具的时滞研究——以武汉市为例[J].中国土地科学,2010,24(1)：50-55.
[27]Wang S. State Misallocation and Housing Prices:Theory and Evidence from China[J]. American Economic Review,2011(8):2081-2107.
[28]叶剑平,廖年生.和谐发展房地产市场的调控要点[J].中共中央党校学报,2007,11(5)：73-77.
[29]宫汝凯,黄宗远.什么推动了中国城镇房价上涨?来自制度变量的证据[J].南方经济,2012(9)：3-16.
[30]黄振宇.我国住宅市场供给对住宅价格影响的实证分析——基于1998—2007年我国房地产市场数据[J].宏观经济研究,2011(3)：21-31.
[31]况伟大.公共政策与我国房地产业发展[J].税务研究,2004(9)：2-7.
[32]任超群,张娟锋,贾生华.土地出让价格信号对区域新建商品住宅价格的影响[J].中国土地科学,2011,25(7)：60-65.
[33]熊剑平,刘承良,袁俊.武汉市住宅小区的空间结构与区位选择[J].经济地理,2006,26(4)：605-609.
[34]马智利,杨艳.重庆市普通住宅地价空间分布与影响因素研究[J].地域研究与开发,2009,28(5)：119-123.
[35]石崧.城市空间结构演变的动力机制分析[J].城市规划汇刊,2004(1)：50-52.
[36]刘红萍,杨钢桥.城市住宅用地空间扩张机制与调控对策[J].经济地理,2005,25(1)：109-112.
[37]牛俊蜻,吕园,刘科伟.城市规划视角下西安市主城区住宅空间结构演变研究[J]. 人文地理,2011,26(4)：48-53.
[38]廖邦固,徐建刚,梅安新.1947～2007年上海中心城区居住空间分异变化——基于居住用地类型视角[J].地理研究,2012,31(6)：1089-1102.
[39]任辉,吴群.基于ESDA的城市住宅地价时空分异研究——以南京市为例[J].经济地理,2011,31(5)：760-765.
[40]公云龙,张绍良,章兰兰.城市地价空间自相关分析——以宿州市为例[J].经济地理,2011,31(11)：1906-1911.
[41]陈思源.探索性空间数据分析支持下的城市地价分布规律研究[J].生态经济,2010(6)：28-30.
[42]梅志雄,黎夏.基于ESDA和Kriging方法的东莞市住宅价格空间结构[J].经济地理,2008,28(5)：862-866.
[43]刘洪彬,王秋兵.基于特征价格模型的城市住宅用地出让价格影响因素研究[J].经济地理,2011,31(6)：1008-1013.
[44]秦波,焦永利.北京住宅价格分布与城市空间结构演变[J].经济地理,2010,30(11)：1815-1820.
[45]程亚鹏,李传昭,吴刚.Hedonic住房价格模型的选择与实证检验[J].系统工程理论与实践,2010(11)：1921-1930.
[46]梅志雄,黄亮.房地产价格分布的空间自相关分析——以东莞市为例[J].中国土地科学,2008,22(2)：49-54.
[47]宋雪娟,卫海燕,王莉.西安市住宅价格空间结构和分异规律分析[J].测绘科学,2011,36(2)：171-174.
[48]梅志雄.基于半变异函数的住宅价格空间异质性分析——以东莞市为例[J].华南师范大学学报：自然科学版,2008(4)：123-128.
[49]曹天邦,黄克龙,李剑波,等.南京市主城区住宅地价的时空演变[J].地理研究,2012,31(6)：1029-1038.
[50]王霞,朱道林.基于Kriging方法和GIS技术的地价时空格局研究[J].重庆建筑大学学报,2007,29(1)：101-105.
[51]王宇航,缪亚敏,杨昕.采样点数目对反距离加权插值结果的敏感性分析[J].地理信息世界,2012,10(4)：31-35.
[52]邓羽,刘盛和,姚峰峰,等.基于协同克里格的基准地价评估及空间结构分析[J].地理科学进展,2009,28(3)：403-408.
Hu S, Cheng Q, Wang L, et al. Multifractal characterization of urban residential land price in space and time[J]. Applied Geography,2012,34:161-170.
[54]温海珍,李旭宁,张凌.城市景观对住宅价格的影响——以杭州市为例[J].地理研究,2012,31(10)：1806-1814.
[55]孙玉环.基于海量交易数据的房地产特征价格模型的构建[J].统计与决策,2011(2)：9-13.
[56]张静,张丽芳,濮励杰,等.基于GWR模型的城市住宅地价的时空演变研究——以江苏省为例[J].地理科学,2012,32(7)：828-834.
[57]汤庆园,徐伟,艾福利.基于地理加权回归的上海市房价空间分异及其影响因子 研究[J].经济地理,2012,32(2)：52-58.
[58]吕萍,甄辉.基于GWR模型的北京市住宅用地价格影响因素及其空间规律研究[J].经济地理,2010,30(3)：472-478.
[59]董冠鹏,张文忠,武文杰,等.北京城市住宅士地市场空间异质性模拟与预测[J].地理学报,2011,66(6)：750-760.
[60]Huang B, Wu B, Barry M. Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2010,24(3):383-401.
[61]张金牡,刘彪,吴波,等.应用改进的时空地理加权模型分析城市住宅价格变化[J].东华理工大学学报：自然科学版,2010,33(1)：53-59.
[62]冯长春,李维瑄,赵蕃蕃.轨道交通对其沿线商品住宅价格的影响分析——以北京地铁5号线为例[J].地理学报,2011,66(8)：1055-1062.
[63]宋佳楠,金晓斌,唐健,等.中国城市地价水平及变化影响因素分析[J].地理学报,2011,66(8)：1045-1054.
[64]陈安明,廖奇云,周焯华.基于Bootstrap方法的土地出让价格影响因素分析[J].重庆大学学报：自然科学版,2007,30(5)：150-153.
[65]党云晓,张文忠,武文杰.北京城市居民住房消费行为的空间差异及其影响因素[J].地理科学进展,2011,30(10)：1203-1209.
[66]郑思齐,张文忠.住房成本与通勤成本的空间互动关系——来自北京市场的微观证据及其宏观含义[J].地理科学进展,2007,26(2)：35-42.
[67]武文杰,张文忠,董冠鹏,等.转型期北京住宅用地投标租金曲线的空间形态与演化[J].地理科学,2011,31(5)：520-527.
[68]郑新奇,王家耀,阎弘文,等.数字地价模型在城市地价时空分析中的应用[J].资源科学,2004,26(1)：14-21.
[69]于伟,宋金平,张萌.近十年来北京市住宅用地出让与空间演变研究[J].中国土地科学,2012,26(3)：86-90.
[70]Rupasingha A, Goetz S J. Social and political forces as determinants of poverty:A spatial analysis[J]. Journal of Socio-Economics,2007,36(4):650-671.
[71]Katz L, Rosen K T. The interjurisdictional effects of growth controls on housing prices[J]. Journal of Law and Economics,1987,30(1):149-160.
[72]Green R K. Land Use Regulation and the Price of Housing in a Suburban Wisconsin County[J]. Journal of Housing Economics,1999,8(2):144-159.
[73]Malpezzi S. Housing prices, externalities, and regulation in US metropolitan areas[J]. Journal of Housing Research,1996,7:209-242.
[74]Malpezzi S, Mayo S K. Getting housing incentives right:a case study of the effects of regulation, taxes, and subsidies on housing supply in Malaysia[J]. Land Economics, 1997:372-391.
[75]Stone Jr B. Paving over paradise:how land use regulations promote residential imperviousness[J]. Landscape and Urban Planning,2004,69(1):101-113.
[76]Lichtenberg E, Tra C, Hardie I. Land use regulation and the provision of open space in suburban residential subdivisions[J]. Journal of Environmental Economics and Management,2007,54(2):199-213.
[77]Landry S, Pu R. The impact of land development regulation on residential tree cover: An empirical evaluation using high-resolution IKONOS imagery[J]. Landscape and Urban Planning,2010,94(2):94-104.
[78]Quigley J M, Rosenthal L A. The Effects of Land Use Regulation on the Price of Housing:What do we know? What can we learn?[J]. Cityscape,2005:69-137.
[79]Glickfeld M, Levine N. Regional growth--local reaction:the enactment and effects of local growth control and management measures in California[M]. Lincoln Inst of Land Policy,1992.
[80]Linneman P. The state of local growth management[M]. Real Estate Center, Wharton School of the University of Pennsylvania,1990.
[81]Brueckner J K. Testing for strategic interaction among local governments:The case of growth controls[J]. Journal of urban economics,1998,44(3):438-467.
[82]Brueckner J K. Strategic control of growth in a system of cities[J]. Journal of Public Economics,1995,57(3):393-416.
[83]Guidry K, Shilling J D, Sirmans C F. Land-Use Controls, Natural Restrictions, and Urban Residential Land Prices[J]. Review of Regional Studies,1999,29(2):105-110.
[84]Knaap G J. The price effects of urban growth boundaries in metropolitan Portland, Oregon[J]. Land Economics,1985,61(1):26-35.
[85]Fainstein S S. Promoting economic development urban planning in the United States and Great Britain[J]. Journal of the American Planning Association,1991,57(1):22-33.
[86]Bramley G. The impact of land use planning and tax subsidies on the supply and price of housing in Britain[J]. Urban Studies,1993,30(1):5-30.
[87]Evans A W. The impact of land use planning and tax subsidies on the supply and price of housing in Britain:a comment[J]. Urban Studies,1996,33(3):581-585.
[88]Chattopadhyay S. Estimating the demand for air quality:new evidence based on the Chicago housing market[J]. Land Economics,1999:22-38.
[89]Heinberg J D, Oates W E. The incidence of differential property taxes on urban housing:A comment and some further evidence[M]. The Urban Institute,1970.
[90]King A T, Thomas A. Property taxes, amenities, and residential land values[M]. Ballinger Publishing Company,1974.
[91]Yinger J, Bloom H S, Boersch-Supan A, et al. Property taxes and house values:The theory and estimation of intrajurisdictional property tax capitalization[M]. Academic Press San Diego,1988.
[92]Mieszkowski P. The property tax:An excise tax or a profits tax?[J]. Journal of Public Economics,1972,1(1):73-96.
[93]Grether D M, Mieszkowski P. Determinants of real estate values[J]. Journal of Urban Economics,1974,1(2):127-145.
[94]Zodrow G R, Mieszkowski P M. The new view of the property tax A reformulation[J]. Regional Science and Urban Economics,1986,16(3):309-327.
[95]Epple D. Hedonic prices and implicit markets:estimating demand and supply functions for differentiated products[J]. The Journal of Political Economy,1987,95(1):59-80.
[96]Fehribach F A, Rutherford R C, Eakin M E. An analysis of the determinants of industrial property valuation[J]. Journal of Real Estate Research,1993,8(3):365-376.
[97]Wheaton W C. Urban residential growth under perfect foresight[J]. Journal of Urban Economics,1982,12(1):1-21.
[98]Beaton W P. The impact of regional land-use controls on property values:the case of the New Jersey Pinelands[J]. Land Economics,1991,67(2):172-194.
[99]Guntermann K L. Residential land prices prior to development[J]. Journal of Real Estate Research,1997,14(1):1-17.
[100]野口悠纪雄.土地经济学[M].第1版.北京：商务印书馆,1997.
[101]Henneberry D M, Barrows R L. Capitalization of exclusive agricultural zoning into farmland prices[J]. Land Economics,1990,66(3):249-258.
[102]Skidmore M, Peddle M. Do development impact fees reduce the rate of residential development?[J]. Growth and Change,1998,29(4):383-400.
[103]Hushak L J. The urban demand for urban-rural fringe land[J]. Land Economics, 1975,51(2):112-123.
[104]Plantinga A J, Lubowski R N, Stavins R N. The effects of potential land development on agricultural land prices[J]. Journal of Urban Economics,2002,52(3):561-581.
[105]Mankiw N G, Weil D N. The baby boom, the baby bust, and the housing market[J]. Regional Science and Urban Economics,1989,19(2):235-258.
[106]Bartik T J. Who benefits from state and local economic development policies?[J]. Books from Upjohn Press,1991.
[107]Abraham J M, Hendershott P H. Bubbles in metropolitan housing markets[R].National Bureau of Economic Research,1994.
[108]Rodriguez M, Sirmans C F. Quantifying the value of a view in single-family housing markets[J]. Appraisal Journal,1994,62:600.
[109]Forrest D, Glen J, Ward R. The impact of a light rail system on the structure of house prices:a hedonic longitudinal study[J]. Journal of Transport Economics and Policy, 1996:15-29.
[110]Michaels R G, Smith V K. Market segmentation and valuing amenities with hedonic models:the case of hazardous waste sites[J].1990.
[111]Shimizu C, Nishimura K. Biases in appraisal land price information:the case of Japan[J]. Journal of Property Investment\& Finance,2006,24(2):150-175.
[112]So H M, Tse R Y C, Ganesan S. Estimating the influence of transport on house prices: evidence from Hong Kong[J]. Journal of Property Valuation and Investment, 1997,15(1):40-47.
[113]Haurin D R, Brasington D. The impact of school quality on real house prices: Interjurisdictional effects[J]. Journal of Housing Economics,1996,5(4):351-368.
[114]Downes T A, Zabel J E. The impact of school characteristics on house prices:Chicago 1987-1991[J]. Journal of Urban Economics,2002,52(1):1-25.
[115]Richardson H W, Vipond J, Furbey R A. Determinants of urban house prices[J]. Urban studies,1974,11(2):189-199.
[116]Carroll T M, Clauretie T M, Jensen J. Living next to godliness:Residential property values and churches[J]. The Journal of Real Estate Finance and Economics, 1996,12(3):319-330.
[117]Hayes K J, Taylor L L. Neighborhood school characteristics:what signals quality to homebuyers?[J]. Economic Review-Federal Reserve Bank of Dallas,1996:2-9.
[118]Tyrv A Inen L, Miettinen A. Property prices and urban forest amenities[J]. Journal of environmental economics and management,2000,39(2):205-223.
[119]Mok H M K, Chan PPK, Cho Y S. A hedonic price model for private properties in Hong Kong[J]. The Journal of Real Estate Finance and Economics,1995,10(1):37-48.
[120]Smith V K, Huang J C. Can markets value air quality? A meta-analysis of hedonic property value models[J]. Journal of political economy,1995:209-227.
[121]Linneman P. Some empirical results on the nature of the hedonic price function for the urban housing market[J]. Journal of Urban Economics,1980,8(1):47-68.
[122]Garrod G D, Willis K G. Valuing goods' characteristics:An application of the hedonic price method to environmental attributes[J]. Journal of Environmental Management, 1992,34(1):59-76.
[123]Espey M, Lopez H. The impact of airport noise and proximity on residential property values[J]. Growth and Change,2000,31(3):408-419.
[124]Pennington G, Topham N, Ward R. Aircraft noise and residential property values adjacent to Manchester International Airport[J]. Journal of Transport Economics and Policy,1990:49-59.
[125]Wilkinson R K. House prices and the measurement of externalities[J]. The Economic Journal,1973,83(329):72-86.
[126]Tse R Y C, Love P E D. Measuring residential property values in Hong Kong[J]. Property management,2000,18(5):366-374.
[127]Kain J F, Quigley J M. Measuring the value of housing quality[J]. Journal of the American Statistical Association,1970:532-548.
[128]Buck A J, Deutsch J, Hakim S, et al. A von Thunen model of crime, casinos and property values in New Jersey[J]. Urban Studies,1991,28(5):673.
[129]Damm D, Lerman S R, Lerner-Lam E, et al. Response of urban real estate values in anticipation of the Washington Metro[J]. Journal of Transport Economics and Policy, 1980:315-336.
[130]Grether D M, Mieszkowski P. The effects of nonresidential land uses on the prices of adjacent housing:some estimates of proximity effects[J]. Journal of Urban Economics, 1980,8(1):1-15.
[131]Diaz R B. Impacts of rail transit on property values,1999[C].
[132]Almeida T M. Impact of Proximity to Light Rail Rapid Transit on Station-area Property Values in Buffalo, New York[D]. State University of New York at Buffalo, 2004.
[133]Gatzlaff D H, Smith M T. The impact of the Miami Metrorail on the value of residences near station locations[J]. Land Economics,1993:54-66.
[134]Haider M, Miller E J. Effects of transportation infrastructure and location on residential real estate values:application of spatial autoregressive techniques[J]. Transportation Research Record:Journal of the Transportation Research Board,2000,1722(-1):1-8.
[135]Kim J, Zhang M. Determining transit's impact on Seoul commercial land values:an application of spatial econometrics [J]. International Real Estate Review, 2005,8(1):1-26.
[136]Anderson R J, Crocker T D, Others. Air pollution and residential property values[J]. Urban Studies,1971,8(3):171-180.
[137]Leggett C G, Bockstael N E. Evidence of the effects of water quality on residential land prices[J]. Journal of Environmental Economics and Management,2000,39(2):121-144.
[138]金家鼎.房地产开发中的地价因素分析[J].中南财经大学学报,1994(4)：63-66.
[139]杨继瑞.影响城市地价的因素体系探析[J].城市规划汇刊,1994(5)：14-20.
[140]唐焱.区域经济一体化背景下城市土地价格影响因素的理论与实证研究[J].华中农业大学学报：社会科学版,2006(5)：47-50.
[141]宋佳楠,金晓斌,唐健,等.中国城市地价水平及变化影响因素分析[J].地理学报,2011,66(8)：1045-1054.
[142]肖更生,山口三十四.影响我国城市住宅地价因素力度的计量分析[J].求索,2008(6)：28-29.
[143]国土资源部.GB/T 18508-2001城镇土地估价规程[S].国家质检总局,2001.
[144]张裕凤,李静.呼和浩特市旗县城镇基准地价及影响因素比较分析[J].地理研究,2007,26(2)：373-382.
[145]张娟锋,刘洪玉.住宅价格与土地价格的城市差异及其决定因素[J].统计研究,2010,27(3)：37-44.
[146]李倢.人口密度分布对地价影响的实证研究[J].国外城市规划,2006,21(4)：82-85.
[147]陈会广。刘忠原.中国普通住宅房价与地价关系的理论及实证研究[J].资源科学,2011,33(5)：856-862.
[148]华文,范黎,吴群,等.城市地价水平影响因素的相关分析——以江苏省为例[J].经济地理,2005,25(2)：203-205.
[149]郭淑芬,袁梦萍.太原市城市地价空间分布的影响因素分析[J].中国房地产：学术版,2011(10)：70-76.
[150]龙莹.空间异质性与区域房地产价格波动的差异——基于地理加权回归的实证研究[J].中央财经大学学报,2010(11)：80-85.
[151]钱建平,周勇.基于DSR的城乡结合部土地价格影响因素体系的构建[J].地理与地理信息科学,2004,20(6)：57-60.
[152]肖更生,李贞玉.政府行为因素对城市地价影响力度的计量分析[J].江西社会科 学,2008(1)：86-90.
[153]秦波,孙亮.容积率和出让方式对地价的影响——基于特征价格模型[J].中国土地科学,2010,24(3)：70-74.
[154]张文新.城市土地储备对我国城市土地供求与地价的影响分析[J].资源科学,2005,27(6)：58-64.
[155]徐颖,周寅康,许丰功.区域基准地价影响力模型的初步研究[J].经济地理,2003,23(3)：355-358.
[156]刘志霞,张加恭,赵永国.深圳经济特区住宅基准地价空间分布特征与影响要素分析[J].华南师范大学学报：自然科学版,2009(2)：111-116.
[157]温海珍,贾生华,郭晓宇.Hedonic price analysis of urban housing:An empirical research on Hangzhou, China[J].浙江大学学报：A卷英文版,2005,6(8)：907-914.
[158]温海珍,贾生华.市场细分与城市住宅特征价格分析[J].浙江大学学报：人文社会科学版,2006,36(2)：155-161.
[159]张洪,金杰.中国省会城市地价空间变化实证研究——以昆明市为例[J].中国土地科学,2007,21(1)：24-30.
[160]张洪,金杰.城市地价空间的计量经济分析——以昆明市为例[J].资源科学,2007,29(4)：25-32.
[161]马智利,杨艳.重庆市普通住宅地价空间分布与影响因素研究[J].地域研究与开发,2009,28(5)：119-123.
[162]辜寄蓉,朱明仓,吴合镇.重庆市房价与地价影响因素实证研究[J].测绘与空间地理信息,2009,32(4)：1-4.
[163]梁青槐,孔令洋,邓文斌.城市轨道交通对沿线住宅价值影响定量计算实例研究[J].土木工程学报,2007,40(4)：98-103.
[164]李君兰,白鹏,宋彦.轨道交通建设对城市住宅价格的影响——以深圳福田区为例[J].城市规划学刊,2009(4)：61-67.
[165]谷一桢,郑思齐.轨道交通对住宅价格和土地开发强度的影响——以北京市13号线为例[J].地理学报,2010,65(2)：213-223.
[166]张娟锋,贾生华.城市间住宅土地价格差异的决定因素——基于长江三角洲城市的实证研究[J].中国软科学,2008(5)：74-80.
[167]李志,周生路,张红富,等.基于GWR模型的南京市住宅地价影响因素及其边际价格作用研究[J].中国土地科学,2009,23(10)：20-25.
[168]王松涛,郑思齐,冯杰.公共服务设施可达性及其对新建住房价格的影响——以北京中心城为例[J].地理科学进展,2007,26(6)：78-85.
[169]陈珧,刘师竹.大学对周边住宅价格影响研究——以浙江大学紫金港校区为例[J].浙江海洋学院学报：人文科学版,2010,27(3)：148-151.
[170]钟海玥,张安录,蔡银莺.武汉市南湖景观对周边住宅价值的影响——基于Hedonic模型的实证研究[J].中国土地科学,2009,23(12)：63-68.
[171]陈立定,欧阳安蛟.试论城市地价动态变化与城市动态规划的互动关系[J].城市发展研究,2005,12(1)：54-57.
[172]高金兰,袁希平,甘淑.城市用地规模与城市地价的相关性研究——以湖北省为 例[J].昆明理工大学学报：社会科学版,2011,11(2)：69-73.
[173]谢戈力,张晓平.宏观规划要素对城市间地价水平差异的影响——以广东省为例[J].热带地理,2011,31(5)：474477.
[174]冷炳荣,杨永春,韦玲霞,等.转型期中国城市容积率与地价关系研究——以兰州市为例[J].城市发展研究,2010,17(4)：116-122.
[175]郭文刚,崔新明,温海珍.城市住宅特征价格分析：对杭州市的实证研究[J].经济地理,2006,26(S1)：172-177.
[176]罗罡辉,吴次芳,郑娟尔.宗地面积对住宅地价的影响[J].中国土地科学,2007,21(5)：66-69.
[177]曾向阳,张安录.土地出让微观决策对地价的影响：模型与实证[J].资源与产业,2007,9(3)：77-80.
[178]唐兴霖.诺思的国家与政府理论述评[J].中国矿业大学学报：社会科学版,2000(2)：22-29.
[179]盖凯程,李俊丽.中国城市土地市场化进程中的地方政府行为研究[J].财贸经济,2009(6)：121-126.
[180]曼昆.经济学原理：微观经济学分册[M].梁小民,梁砾,译.第五版.北京：北京大学出版社,2009.
[181]保罗·萨缪尔森,威廉·诺德豪斯.经济学[M].萧琛,译.第18版.人民邮电出版社,2008.
[182]张小宏,郑思齐.住宅用地供给短缺背后的地方政府动机[J].探索与争鸣,2010(11)：54-58.
[183]郑思齐,师展.“土地财政”下的土地和住宅市场：对地方政府行为的分析[J].广东社会科学,2011(2)：5-10.
[184]Alonso W. Location and Land Use[M]. Cambridge, MA:Harvard University Press, 1964.
[185]杜宁.汽车使用税费与城市空间发展的关联性研究——基于城市土地租金竞价函数的分析方法[J].城市规划,2010,34(12)：64-70.
[186]Aaron H J, Feldstein M S, Inman R. The Economics of Public Services[J]. The Economics of Public Services,1977.
[187]Arnott R J, Lewis F D. The transition of land to urban use[J]. The Journal of Political Economy,1979:161-169.
[188]Lancaster K J. A new approach to consumer theory[J]. Journal of political economy, 1966,74(2):132-157.
[189]Rosen S. Hedonic prices and implicit markets:product differentiation in pure competition[J]. Journal of political economy,1974,82(1):35-55.
[190]李玲,朱道林,胡克林.北京市城区住宅地价的时空变化规律[J].经济地理,2011,31(4)：655-659.
[191]武文杰,张文忠,刘志林,等.北京市居住用地出让的时空格局演变[J].地理研究,2010,29(4)：683-692.
[192]朱晨.中国中心城市第二住宅的地理空间分布特征[J].经济地理, 2006,26(6)：945-948.
[193]赵晶,陈华根,许惠平.20世纪下半叶上海市居住用地扩展模式、强度及空间分异特征[J].自然资源学报,2005,20(3)：400-406.
[194]余琪.转型期上海城市居住空间生产模式及布局形态演进[J].城市规划学刊,2010(5)：15-25.
[195]齐心,鲁黛迪.北京城市内部居住迁移的空间模式研究[J].城市发展研究,2012,19(12)：16-21.
[196]李志刚.中国大都市新移民的住房模式与影响机制[J].地理学报,2012,67(2)：189-200.
[197]易成栋,黄友琴.中国城市自有多套住宅家庭的空间模式实证研究[J].经济地理,2010,30(4)：585-590.
[198]苏振民,林炳耀.城市居住空间分异控制：居住模式与公共政策[J].城市规划,2007,31(2)：45-49.
[199]范雪峰.小城镇基准地价评估中立体型综合用地地价研究[D].吉林大学土地资源管理,2006.
[200]杜彬,张丽.应用基准地价评估小城镇立体型综合用地地价研究[J].农机化研究,2005(4)：19-22.
[201]杜彬,张丽,赵英娜.应用基准地价评估城镇综合用地地价的方法[J].南京师大学报：自然科学版,2005,28(2)：112-116.
[202]卢新海,李书宁,赵凯.城镇基准地价土地用途细化分类研究——以武汉市商业用地为例[J].中国房地产,2012(4)：18-28.
[203]唐健,谭永忠,徐小峰.中国商住用地价格倒挂及其产生机理[J].中国土地科学,2011,25(1)：22-29.
[204]陈英,张军,周冬梅,等.立体综合用地宗地价格评估方法研究[J].中国土地科学,2010,24(8)：9-15.
[205]中华人民共和国国土资源部.GB/T 18508-2001城镇土地估价规程[S].国家质检总局,2001.
[206]陆丽珍.城镇综合用地宗地地价评估方法研究[J].经济地理,2002,22(S 1)：96-99.
[207]颜好洁,冯友健.基准地价分类修正综合法在综合用地地价评估中的应用[J].浙江大学学报：理学版,2005,32(5)：579-583.
[208]冯友健,林志鹤.小城镇综合用地宗地地价评估方法研究[J].中国资产评估,1999(6)：25-27.
[209]徐一萍,李国安,唐绍祥,等.商住综合用地评估的加价模型[J].宁波大学学报：理工版,2000,13(4)：55-58.
[210]中华人民共和国住房和城乡建设部.GB 50137-2011城市用地分类与规划建设用地标准[s].中国建筑工业出版社,2010.
[211]Little R J A, Rubin D B. Statistical analysis with missing data[M]. Wiley New York, 1987.
[212]韩卫国,王劲峰,胡建军.交通流量数据缺失值的插补方法[J].交通与计算机,2005,23(1)：39-42.
[213]Roger B, Others. Implementing spatial data analysis software tools in R[J].
[214]Yuan Y C. Multiple imputation for missing data:concepts and new development (version 9.0),2000[C].
[215]Muth E N B, Kaplan D, Hollis M. On structural equation modeling with data that are not missing completely at random[J]. Psychometrika,1987,52(3):431-462.
[216]Hox J J. A review of current software for handling missing data[J]. Kwantitatieve Methoden,1999,20:123-138.
[217]赵慧,甘仲惟,肖明.多变量统计数据中异常值检验方法的探讨[J].华中师范大学学报：自然科学版,2003,37(2)：133-137.
[218]毋红军,刘章.统计数据的异常值检验[J].华北水利水电学院学报,2003(1)：69-72.
[219]张德然.统计数据中异常值的检验方法[J].统计研究,2003(5)：53-55.
[220]薛薇.SPSS统计分析方法及应用[M].第2版.电子工业出版社,2010.
[221]冯艳.1990年代以来武汉城市土地开发及空间发展规律研究[D].华中科技大学,2007.
[222]吴曙光.武汉城市空间演变与土地出让研究[D].中国地质大学(武汉),2012.
[223]任超群.土地出让价格信号对房价的影响研究[D].浙江大学企业管理,2011.
[224]梅志雄,黄亮.房地产价格分布的空间自相关分析——以东莞市为例[J].中国土地科学,2008,22(2)：49-54.
[225]孟斌,张景秋,王劲峰,等.空间分析方法在房地产市场研究中的应用——以北京市为例[J].地理研究,2005,24(6)：956-964.
[226]陈思源,曲福田,曹大贵,等.ESDA支持下的城市地价分布信息提取[J].国土资源遥感,2006(3)：47-50.
[227]Anselin L. Interactive techniques and exploratory spatial data analysis[J]. Geographical Information Systems principles techniques management and applications,1996,1.
[228]Rey S J. Spatial empirics for economic growth and convergence[J]. Geographical Analysis,2001,33(3):195-214.
[229]张鸿辉,曾永年,吴林,等.南京市地价空间结构的演变[J].资源科学,2008,30(4)：591-597.
[230]高伟丽.基于因子分析和1ESDA的我国旅游业发展差异性及其影响因素研究[D].南京理工大学,2012.
[231]刘聪粉,张瑞荣.云南省地区经济差异的空间统计分析[J].云南财经大学学报,2009,25(3)：118-126.
[232]马晓冬,马荣华,徐建刚.基于ESDA-GIS的城镇群体空间结构[J].地理学报,2004,56(6)：1048-1057.
[233]陈思源,曲福田,倪绍祥,等.GIS空间分析支持下的城市地价分布研究——以江苏省镇江市为例[J].南京农业大学学报,2005,28(3)：119-122.
[234]郭龙,张海涛,陈家赢,等.基于协同克里格插值和地理加权回归模型的土壤属性空间预测比较[J].土壤学报,2012,49(5)：1037-1042.
[235]温海珍.城市住宅的特征价格：理论分析与实证研究[D].浙江大学企业管理,2004.
[236]Hass G C. A Statistical Analysis of Farm Sales in Blue Earth County, Minnesota, as a Basis for Farm Land Appraisal [D]. the University of Minnesota,1922.
[237]Court A T. Hedonic Price Indexes with Antomotive Examples:General Motors, New York,1936[C].
[238]Waugh F V. Quality factors in fluencing vegetable prices[J]. Journal of Farm Economics,1928(10):185-196.
[239]Goodman A C. Andrew Court and the invention of hedonic price analysis[J]. Journal of Urban Economics,1998,44(2):291-298.
[240]Griliches Z. Price Indexes and QuaIity Change[M]. Cambridge:Harvard University Press ,1971.
[241]毕宝德.土地经济学[M].第五版.北京：中国人民大学出版社.
[242]Mok H M K, Chan P P K, Cho Y S. A hedonic price model for private properties in Hong Kong[J]. The Journal of Real Estate Finance and Economics,1995,10(1):37-48.
[243]Yang Z. An application of the hedonic price model with uncertain attribute-The case of the People's Republic of China[J]. Property management,2001,19(1):50-63.
[244]冯艳芬,梁小斯,吴大放.基于Hedonic模型的广州地铁1号沿线住宅价格分析[J].广州大学学报：自然科学版,2011,10(4)：90-95.
[245]聂冲,温海珍,樊晓锋.城市轨道交通对房地产增值的时空效应[J].地理研究,2010,29(5)：801-810.
[246]蒋芳,朱道林.基于GIS的地价空间分布规律研究——以北京市住宅地价为例[J].经济地理,2005,25(2)：199-202.
[247]石忆邵,郭惠宁.上海南站对住宅价格影响的时空效应分析[J].地理学报,2009,64(2)：167-176.
[248]石忆邵,张蕊.大型公园绿地对住宅价格的时空影响效应——以上海市黄兴公园绿地为例[J].地理研究,2010,29(3)：510-520.
[249]钟海明,张安录,蔡银莺.武汉市南湖景观对周边住宅价值的影响——基于Hedonic模型的实证研究[J].中国土地科学,2009,23(12)：63-68.
[250]李郇,符文颖.城市政府基础设施投资在住宅市场的资本化考察——基于广州价格数据的Hedonic模型构建[J].地理研究,2010,29(7)：1269-1280.
[251]秦波,孙亮.容积率和出让方式对地价的影响——基于特征价格模型[J].中国土地科学,2010,24(3)：70-74.
[252]王婵婵,丁和庚,吴群.容积率对城市住宅用地交易价格影响的定量研究——以南京市为例[J].资源科学,2009,31(1)：123-129.
[253]党杨.中国城市土地价格影响因素研究[D].吉林大学区域经济,2011.
[254]刘春燕,沈禹民.宗地面积影响地价的作用机制和规律[J].浙江国土资源,2005(8)：45-47.
[255]苏海龙,徐芳.上海地铁8号线对城市住宅价格的时空效应定量研究[J].上海交通大学学报,2010,44(12)：1704-1710.
[256]Bowes D R, Ihlanfeldt K R. Identifying the impacts of rail transit stations on residential property values[J]. Journal of Urban Economics,2001,50(1):1-25.
[257]Bae C H C, Jun M J, Park H. The impact of Seoul's subway Line 5 on residential property values[J]. Transport Policy,2003,10(2):85-94.
[258]李志辉.基于Hedonic模型的武汉住宅特征价格研究[D].华中农业大学土地资源管理,2008.
[2]许妍,李雪铭,高俊峰,等.近10年来大连城市居住小区时空变动与演化模式[J].地理科学,2009,29(6)：825-832.
[3]陈思源,曲福田,倪绍祥,等.GIS空间分析支持下的城市地价分布研究——以江苏省镇江市为例[J].南京农业大学学报,2005,28(3)：119-122.
[4]宋金平,王恩儒,张文新,等.北京住宅郊区化与就业空间错位[J].地理学报,2007,62(4)：387-396.
[5]曾忠平,卢新海.武汉城市用地结构演变模式研究[J].中国土地科学,2009,23(3)：44-48.
[6]彭建超,吴群.国内外城市地价时空演变研究进展[J].资源科学,2008,30(1)：64-71.
[7]Alonso W. Location and Land Use:Toward a general theory of land use[M]. Cambridge:Harvard University Press,1964.
[8]Clapp J M, Rodriguez M, Kelley Pace R. Residential land values and the decentralization of jobs[J]. The Journal of Real Estate Finance and Economics, 2001,22(1):43-61.
[9]van der Vlist A J, Czamanski D, Folmer H. Immigration and urban housing market dynamics:the case of Haifa[J]. The Annals of Regional Science,2011,47(3):585-598.
[10]Chapin F S, Weiss S F, Donnelly T G. Factors influencing land development: evaluation of inputs for a forecast model[M]. Institute for Research in Social Science, University of North Carolina,1962.
[11]Czamanski S. Effects of public investments on urban land values[J]. Journal of the American Institute of Planners,1966,32(4):204-217.
[12]Wheaton W C. Urban residential growth under perfect foresight[J]. Journal of Urban Economics,1982,12(1):1-21.
[13]Witte A D. The determination of interurban residential site price differences:a derived demand model with empirical testing[J]. Journal of Regional Science, 1975,15(3):351-364.
[14]Follain J R, Jimenez E. Estimating the demand for housing characteristics:A survey and critique[J]. Regional Science and Urban Economics,1985,15(1):77-107.
[15]Segal D, Srinivasan P. The impact of suburban growth restrictions on US housing price inflation,1975--1978[J]. Urban Geography,1985,6(1):14-26.
[16]Hammer T R, Coughlin R E, Horn IV E T. The effect of a large urban park on real estate value[J]. Journal of the American Institute of Planners,1974,40(4):274-277.
[17]Grimes A, Liang Y. Spatial Determinants of Land Prices:Does Auckland's Metropolitan Urban Limit Have an Effect?[J]. Applied Spatial Analysis and Policy, 2009,2(1):23-45.
[18]Ihlanfeldt K R. The effect of land use regulation on housing and land prices[J]. Journal of Urban Economics,2007,61(3):420-435.
[19]杨东峰,熊国平.我国大城市空间增长机制的实证研究及政策建议——经济发展·人口增长·道路交通·土地资源[J].城市规划学刊,2008(3)：51-56.
[20]宋金平,王恩儒,张文新,等.北京住宅郊区化与就业空间错位[J].地理学报,2007,62(4)：387-396.
[21]石忆邵,李木秀.上海市住房价格梯度及其影响因素分析[J].地理学报,2006,61(6)：604-612.
[22]沈悦,刘洪玉.住宅价格与经济基本面：1995—2002年中国14城市的实证研究[J].经济研究,2004(6)：78-86.
[23]阮连法,包洪洁,温海珍.重大事件对城市住宅价格的影响——来自杭州市的证据[J].中国七地科学,2012,26(12)：41-47.
[24]袁雯,朱喜钢,马国强.南京居住空间分异的特征与模式研究——基于南京主城拆迁改造的透视[J].人文地理,2010,,25(2)：65-69.
[25]况伟大.预期、投机与中国城市房价波动[J].经济研究,2010(9)：67-78.
[26]张红霞,谭术魁.城市土地市场调控政策工具的时滞研究——以武汉市为例[J].中国土地科学,2010,24(1)：50-55.
[27]Wang S. State Misallocation and Housing Prices:Theory and Evidence from China[J]. American Economic Review,2011(8):2081-2107.
[28]叶剑平,廖年生.和谐发展房地产市场的调控要点[J].中共中央党校学报,2007,11(5)：73-77.
[29]宫汝凯,黄宗远.什么推动了中国城镇房价上涨?来自制度变量的证据[J].南方经济,2012(9)：3-16.
[30]黄振宇.我国住宅市场供给对住宅价格影响的实证分析——基于1998—2007年我国房地产市场数据[J].宏观经济研究,2011(3)：21-31.
[31]况伟大.公共政策与我国房地产业发展[J].税务研究,2004(9)：2-7.
[32]任超群,张娟锋,贾生华.土地出让价格信号对区域新建商品住宅价格的影响[J].中国土地科学,2011,25(7)：60-65.
[33]熊剑平,刘承良,袁俊.武汉市住宅小区的空间结构与区位选择[J].经济地理,2006,26(4)：605-609.
[34]马智利,杨艳.重庆市普通住宅地价空间分布与影响因素研究[J].地域研究与开发,2009,28(5)：119-123.
[35]石崧.城市空间结构演变的动力机制分析[J].城市规划汇刊,2004(1)：50-52.
[36]刘红萍,杨钢桥.城市住宅用地空间扩张机制与调控对策[J].经济地理,2005,25(1)：109-112.
[37]牛俊蜻,吕园,刘科伟.城市规划视角下西安市主城区住宅空间结构演变研究[J]. 人文地理,2011,26(4)：48-53.
[38]廖邦固,徐建刚,梅安新.1947～2007年上海中心城区居住空间分异变化——基于居住用地类型视角[J].地理研究,2012,31(6)：1089-1102.
[39]任辉,吴群.基于ESDA的城市住宅地价时空分异研究——以南京市为例[J].经济地理,2011,31(5)：760-765.
[40]公云龙,张绍良,章兰兰.城市地价空间自相关分析——以宿州市为例[J].经济地理,2011,31(11)：1906-1911.
[41]陈思源.探索性空间数据分析支持下的城市地价分布规律研究[J].生态经济,2010(6)：28-30.
[42]梅志雄,黎夏.基于ESDA和Kriging方法的东莞市住宅价格空间结构[J].经济地理,2008,28(5)：862-866.
[43]刘洪彬,王秋兵.基于特征价格模型的城市住宅用地出让价格影响因素研究[J].经济地理,2011,31(6)：1008-1013.
[44]秦波,焦永利.北京住宅价格分布与城市空间结构演变[J].经济地理,2010,30(11)：1815-1820.
[45]程亚鹏,李传昭,吴刚.Hedonic住房价格模型的选择与实证检验[J].系统工程理论与实践,2010(11)：1921-1930.
[46]梅志雄,黄亮.房地产价格分布的空间自相关分析——以东莞市为例[J].中国土地科学,2008,22(2)：49-54.
[47]宋雪娟,卫海燕,王莉.西安市住宅价格空间结构和分异规律分析[J].测绘科学,2011,36(2)：171-174.
[48]梅志雄.基于半变异函数的住宅价格空间异质性分析——以东莞市为例[J].华南师范大学学报：自然科学版,2008(4)：123-128.
[49]曹天邦,黄克龙,李剑波,等.南京市主城区住宅地价的时空演变[J].地理研究,2012,31(6)：1029-1038.
[50]王霞,朱道林.基于Kriging方法和GIS技术的地价时空格局研究[J].重庆建筑大学学报,2007,29(1)：101-105.
[51]王宇航,缪亚敏,杨昕.采样点数目对反距离加权插值结果的敏感性分析[J].地理信息世界,2012,10(4)：31-35.
[52]邓羽,刘盛和,姚峰峰,等.基于协同克里格的基准地价评估及空间结构分析[J].地理科学进展,2009,28(3)：403-408.
Hu S, Cheng Q, Wang L, et al. Multifractal characterization of urban residential land price in space and time[J]. Applied Geography,2012,34:161-170.
[54]温海珍,李旭宁,张凌.城市景观对住宅价格的影响——以杭州市为例[J].地理研究,2012,31(10)：1806-1814.
[55]孙玉环.基于海量交易数据的房地产特征价格模型的构建[J].统计与决策,2011(2)：9-13.
[56]张静,张丽芳,濮励杰,等.基于GWR模型的城市住宅地价的时空演变研究——以江苏省为例[J].地理科学,2012,32(7)：828-834.
[57]汤庆园,徐伟,艾福利.基于地理加权回归的上海市房价空间分异及其影响因子 研究[J].经济地理,2012,32(2)：52-58.
[58]吕萍,甄辉.基于GWR模型的北京市住宅用地价格影响因素及其空间规律研究[J].经济地理,2010,30(3)：472-478.
[59]董冠鹏,张文忠,武文杰,等.北京城市住宅士地市场空间异质性模拟与预测[J].地理学报,2011,66(6)：750-760.
[60]Huang B, Wu B, Barry M. Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2010,24(3):383-401.
[61]张金牡,刘彪,吴波,等.应用改进的时空地理加权模型分析城市住宅价格变化[J].东华理工大学学报：自然科学版,2010,33(1)：53-59.
[62]冯长春,李维瑄,赵蕃蕃.轨道交通对其沿线商品住宅价格的影响分析——以北京地铁5号线为例[J].地理学报,2011,66(8)：1055-1062.
[63]宋佳楠,金晓斌,唐健,等.中国城市地价水平及变化影响因素分析[J].地理学报,2011,66(8)：1045-1054.
[64]陈安明,廖奇云,周焯华.基于Bootstrap方法的土地出让价格影响因素分析[J].重庆大学学报：自然科学版,2007,30(5)：150-153.
[65]党云晓,张文忠,武文杰.北京城市居民住房消费行为的空间差异及其影响因素[J].地理科学进展,2011,30(10)：1203-1209.
[66]郑思齐,张文忠.住房成本与通勤成本的空间互动关系——来自北京市场的微观证据及其宏观含义[J].地理科学进展,2007,26(2)：35-42.
[67]武文杰,张文忠,董冠鹏,等.转型期北京住宅用地投标租金曲线的空间形态与演化[J].地理科学,2011,31(5)：520-527.
[68]郑新奇,王家耀,阎弘文,等.数字地价模型在城市地价时空分析中的应用[J].资源科学,2004,26(1)：14-21.
[69]于伟,宋金平,张萌.近十年来北京市住宅用地出让与空间演变研究[J].中国土地科学,2012,26(3)：86-90.
[70]Rupasingha A, Goetz S J. Social and political forces as determinants of poverty:A spatial analysis[J]. Journal of Socio-Economics,2007,36(4):650-671.
[71]Katz L, Rosen K T. The interjurisdictional effects of growth controls on housing prices[J]. Journal of Law and Economics,1987,30(1):149-160.
[72]Green R K. Land Use Regulation and the Price of Housing in a Suburban Wisconsin County[J]. Journal of Housing Economics,1999,8(2):144-159.
[73]Malpezzi S. Housing prices, externalities, and regulation in US metropolitan areas[J]. Journal of Housing Research,1996,7:209-242.
[74]Malpezzi S, Mayo S K. Getting housing incentives right:a case study of the effects of regulation, taxes, and subsidies on housing supply in Malaysia[J]. Land Economics, 1997:372-391.
[75]Stone Jr B. Paving over paradise:how land use regulations promote residential imperviousness[J]. Landscape and Urban Planning,2004,69(1):101-113.
[76]Lichtenberg E, Tra C, Hardie I. Land use regulation and the provision of open space in suburban residential subdivisions[J]. Journal of Environmental Economics and Management,2007,54(2):199-213.
[77]Landry S, Pu R. The impact of land development regulation on residential tree cover: An empirical evaluation using high-resolution IKONOS imagery[J]. Landscape and Urban Planning,2010,94(2):94-104.
[78]Quigley J M, Rosenthal L A. The Effects of Land Use Regulation on the Price of Housing:What do we know? What can we learn?[J]. Cityscape,2005:69-137.
[79]Glickfeld M, Levine N. Regional growth--local reaction:the enactment and effects of local growth control and management measures in California[M]. Lincoln Inst of Land Policy,1992.
[80]Linneman P. The state of local growth management[M]. Real Estate Center, Wharton School of the University of Pennsylvania,1990.
[81]Brueckner J K. Testing for strategic interaction among local governments:The case of growth controls[J]. Journal of urban economics,1998,44(3):438-467.
[82]Brueckner J K. Strategic control of growth in a system of cities[J]. Journal of Public Economics,1995,57(3):393-416.
[83]Guidry K, Shilling J D, Sirmans C F. Land-Use Controls, Natural Restrictions, and Urban Residential Land Prices[J]. Review of Regional Studies,1999,29(2):105-110.
[84]Knaap G J. The price effects of urban growth boundaries in metropolitan Portland, Oregon[J]. Land Economics,1985,61(1):26-35.
[85]Fainstein S S. Promoting economic development urban planning in the United States and Great Britain[J]. Journal of the American Planning Association,1991,57(1):22-33.
[86]Bramley G. The impact of land use planning and tax subsidies on the supply and price of housing in Britain[J]. Urban Studies,1993,30(1):5-30.
[87]Evans A W. The impact of land use planning and tax subsidies on the supply and price of housing in Britain:a comment[J]. Urban Studies,1996,33(3):581-585.
[88]Chattopadhyay S. Estimating the demand for air quality:new evidence based on the Chicago housing market[J]. Land Economics,1999:22-38.
[89]Heinberg J D, Oates W E. The incidence of differential property taxes on urban housing:A comment and some further evidence[M]. The Urban Institute,1970.
[90]King A T, Thomas A. Property taxes, amenities, and residential land values[M]. Ballinger Publishing Company,1974.
[91]Yinger J, Bloom H S, Boersch-Supan A, et al. Property taxes and house values:The theory and estimation of intrajurisdictional property tax capitalization[M]. Academic Press San Diego,1988.
[92]Mieszkowski P. The property tax:An excise tax or a profits tax?[J]. Journal of Public Economics,1972,1(1):73-96.
[93]Grether D M, Mieszkowski P. Determinants of real estate values[J]. Journal of Urban Economics,1974,1(2):127-145.
[94]Zodrow G R, Mieszkowski P M. The new view of the property tax A reformulation[J]. Regional Science and Urban Economics,1986,16(3):309-327.
[95]Epple D. Hedonic prices and implicit markets:estimating demand and supply functions for differentiated products[J]. The Journal of Political Economy,1987,95(1):59-80.
[96]Fehribach F A, Rutherford R C, Eakin M E. An analysis of the determinants of industrial property valuation[J]. Journal of Real Estate Research,1993,8(3):365-376.
[97]Wheaton W C. Urban residential growth under perfect foresight[J]. Journal of Urban Economics,1982,12(1):1-21.
[98]Beaton W P. The impact of regional land-use controls on property values:the case of the New Jersey Pinelands[J]. Land Economics,1991,67(2):172-194.
[99]Guntermann K L. Residential land prices prior to development[J]. Journal of Real Estate Research,1997,14(1):1-17.
[100]野口悠纪雄.土地经济学[M].第1版.北京：商务印书馆,1997.
[101]Henneberry D M, Barrows R L. Capitalization of exclusive agricultural zoning into farmland prices[J]. Land Economics,1990,66(3):249-258.
[102]Skidmore M, Peddle M. Do development impact fees reduce the rate of residential development?[J]. Growth and Change,1998,29(4):383-400.
[103]Hushak L J. The urban demand for urban-rural fringe land[J]. Land Economics, 1975,51(2):112-123.
[104]Plantinga A J, Lubowski R N, Stavins R N. The effects of potential land development on agricultural land prices[J]. Journal of Urban Economics,2002,52(3):561-581.
[105]Mankiw N G, Weil D N. The baby boom, the baby bust, and the housing market[J]. Regional Science and Urban Economics,1989,19(2):235-258.
[106]Bartik T J. Who benefits from state and local economic development policies?[J]. Books from Upjohn Press,1991.
[107]Abraham J M, Hendershott P H. Bubbles in metropolitan housing markets[R].National Bureau of Economic Research,1994.
[108]Rodriguez M, Sirmans C F. Quantifying the value of a view in single-family housing markets[J]. Appraisal Journal,1994,62:600.
[109]Forrest D, Glen J, Ward R. The impact of a light rail system on the structure of house prices:a hedonic longitudinal study[J]. Journal of Transport Economics and Policy, 1996:15-29.
[110]Michaels R G, Smith V K. Market segmentation and valuing amenities with hedonic models:the case of hazardous waste sites[J].1990.
[111]Shimizu C, Nishimura K. Biases in appraisal land price information:the case of Japan[J]. Journal of Property Investment\& Finance,2006,24(2):150-175.
[112]So H M, Tse R Y C, Ganesan S. Estimating the influence of transport on house prices: evidence from Hong Kong[J]. Journal of Property Valuation and Investment, 1997,15(1):40-47.
[113]Haurin D R, Brasington D. The impact of school quality on real house prices: Interjurisdictional effects[J]. Journal of Housing Economics,1996,5(4):351-368.
[114]Downes T A, Zabel J E. The impact of school characteristics on house prices:Chicago 1987-1991[J]. Journal of Urban Economics,2002,52(1):1-25.
[115]Richardson H W, Vipond J, Furbey R A. Determinants of urban house prices[J]. Urban studies,1974,11(2):189-199.
[116]Carroll T M, Clauretie T M, Jensen J. Living next to godliness:Residential property values and churches[J]. The Journal of Real Estate Finance and Economics, 1996,12(3):319-330.
[117]Hayes K J, Taylor L L. Neighborhood school characteristics:what signals quality to homebuyers?[J]. Economic Review-Federal Reserve Bank of Dallas,1996:2-9.
[118]Tyrv A Inen L, Miettinen A. Property prices and urban forest amenities[J]. Journal of environmental economics and management,2000,39(2):205-223.
[119]Mok H M K, Chan PPK, Cho Y S. A hedonic price model for private properties in Hong Kong[J]. The Journal of Real Estate Finance and Economics,1995,10(1):37-48.
[120]Smith V K, Huang J C. Can markets value air quality? A meta-analysis of hedonic property value models[J]. Journal of political economy,1995:209-227.
[121]Linneman P. Some empirical results on the nature of the hedonic price function for the urban housing market[J]. Journal of Urban Economics,1980,8(1):47-68.
[122]Garrod G D, Willis K G. Valuing goods' characteristics:An application of the hedonic price method to environmental attributes[J]. Journal of Environmental Management, 1992,34(1):59-76.
[123]Espey M, Lopez H. The impact of airport noise and proximity on residential property values[J]. Growth and Change,2000,31(3):408-419.
[124]Pennington G, Topham N, Ward R. Aircraft noise and residential property values adjacent to Manchester International Airport[J]. Journal of Transport Economics and Policy,1990:49-59.
[125]Wilkinson R K. House prices and the measurement of externalities[J]. The Economic Journal,1973,83(329):72-86.
[126]Tse R Y C, Love P E D. Measuring residential property values in Hong Kong[J]. Property management,2000,18(5):366-374.
[127]Kain J F, Quigley J M. Measuring the value of housing quality[J]. Journal of the American Statistical Association,1970:532-548.
[128]Buck A J, Deutsch J, Hakim S, et al. A von Thunen model of crime, casinos and property values in New Jersey[J]. Urban Studies,1991,28(5):673.
[129]Damm D, Lerman S R, Lerner-Lam E, et al. Response of urban real estate values in anticipation of the Washington Metro[J]. Journal of Transport Economics and Policy, 1980:315-336.
[130]Grether D M, Mieszkowski P. The effects of nonresidential land uses on the prices of adjacent housing:some estimates of proximity effects[J]. Journal of Urban Economics, 1980,8(1):1-15.
[131]Diaz R B. Impacts of rail transit on property values,1999[C].
[132]Almeida T M. Impact of Proximity to Light Rail Rapid Transit on Station-area Property Values in Buffalo, New York[D]. State University of New York at Buffalo, 2004.
[133]Gatzlaff D H, Smith M T. The impact of the Miami Metrorail on the value of residences near station locations[J]. Land Economics,1993:54-66.
[134]Haider M, Miller E J. Effects of transportation infrastructure and location on residential real estate values:application of spatial autoregressive techniques[J]. Transportation Research Record:Journal of the Transportation Research Board,2000,1722(-1):1-8.
[135]Kim J, Zhang M. Determining transit's impact on Seoul commercial land values:an application of spatial econometrics [J]. International Real Estate Review, 2005,8(1):1-26.
[136]Anderson R J, Crocker T D, Others. Air pollution and residential property values[J]. Urban Studies,1971,8(3):171-180.
[137]Leggett C G, Bockstael N E. Evidence of the effects of water quality on residential land prices[J]. Journal of Environmental Economics and Management,2000,39(2):121-144.
[138]金家鼎.房地产开发中的地价因素分析[J].中南财经大学学报,1994(4)：63-66.
[139]杨继瑞.影响城市地价的因素体系探析[J].城市规划汇刊,1994(5)：14-20.
[140]唐焱.区域经济一体化背景下城市土地价格影响因素的理论与实证研究[J].华中农业大学学报：社会科学版,2006(5)：47-50.
[141]宋佳楠,金晓斌,唐健,等.中国城市地价水平及变化影响因素分析[J].地理学报,2011,66(8)：1045-1054.
[142]肖更生,山口三十四.影响我国城市住宅地价因素力度的计量分析[J].求索,2008(6)：28-29.
[143]国土资源部.GB/T 18508-2001城镇土地估价规程[S].国家质检总局,2001.
[144]张裕凤,李静.呼和浩特市旗县城镇基准地价及影响因素比较分析[J].地理研究,2007,26(2)：373-382.
[145]张娟锋,刘洪玉.住宅价格与土地价格的城市差异及其决定因素[J].统计研究,2010,27(3)：37-44.
[146]李倢.人口密度分布对地价影响的实证研究[J].国外城市规划,2006,21(4)：82-85.
[147]陈会广。刘忠原.中国普通住宅房价与地价关系的理论及实证研究[J].资源科学,2011,33(5)：856-862.
[148]华文,范黎,吴群,等.城市地价水平影响因素的相关分析——以江苏省为例[J].经济地理,2005,25(2)：203-205.
[149]郭淑芬,袁梦萍.太原市城市地价空间分布的影响因素分析[J].中国房地产：学术版,2011(10)：70-76.
[150]龙莹.空间异质性与区域房地产价格波动的差异——基于地理加权回归的实证研究[J].中央财经大学学报,2010(11)：80-85.
[151]钱建平,周勇.基于DSR的城乡结合部土地价格影响因素体系的构建[J].地理与地理信息科学,2004,20(6)：57-60.
[152]肖更生,李贞玉.政府行为因素对城市地价影响力度的计量分析[J].江西社会科 学,2008(1)：86-90.
[153]秦波,孙亮.容积率和出让方式对地价的影响——基于特征价格模型[J].中国土地科学,2010,24(3)：70-74.
[154]张文新.城市土地储备对我国城市土地供求与地价的影响分析[J].资源科学,2005,27(6)：58-64.
[155]徐颖,周寅康,许丰功.区域基准地价影响力模型的初步研究[J].经济地理,2003,23(3)：355-358.
[156]刘志霞,张加恭,赵永国.深圳经济特区住宅基准地价空间分布特征与影响要素分析[J].华南师范大学学报：自然科学版,2009(2)：111-116.
[157]温海珍,贾生华,郭晓宇.Hedonic price analysis of urban housing:An empirical research on Hangzhou, China[J].浙江大学学报：A卷英文版,2005,6(8)：907-914.
[158]温海珍,贾生华.市场细分与城市住宅特征价格分析[J].浙江大学学报：人文社会科学版,2006,36(2)：155-161.
[159]张洪,金杰.中国省会城市地价空间变化实证研究——以昆明市为例[J].中国土地科学,2007,21(1)：24-30.
[160]张洪,金杰.城市地价空间的计量经济分析——以昆明市为例[J].资源科学,2007,29(4)：25-32.
[161]马智利,杨艳.重庆市普通住宅地价空间分布与影响因素研究[J].地域研究与开发,2009,28(5)：119-123.
[162]辜寄蓉,朱明仓,吴合镇.重庆市房价与地价影响因素实证研究[J].测绘与空间地理信息,2009,32(4)：1-4.
[163]梁青槐,孔令洋,邓文斌.城市轨道交通对沿线住宅价值影响定量计算实例研究[J].土木工程学报,2007,40(4)：98-103.
[164]李君兰,白鹏,宋彦.轨道交通建设对城市住宅价格的影响——以深圳福田区为例[J].城市规划学刊,2009(4)：61-67.
[165]谷一桢,郑思齐.轨道交通对住宅价格和土地开发强度的影响——以北京市13号线为例[J].地理学报,2010,65(2)：213-223.
[166]张娟锋,贾生华.城市间住宅土地价格差异的决定因素——基于长江三角洲城市的实证研究[J].中国软科学,2008(5)：74-80.
[167]李志,周生路,张红富,等.基于GWR模型的南京市住宅地价影响因素及其边际价格作用研究[J].中国土地科学,2009,23(10)：20-25.
[168]王松涛,郑思齐,冯杰.公共服务设施可达性及其对新建住房价格的影响——以北京中心城为例[J].地理科学进展,2007,26(6)：78-85.
[169]陈珧,刘师竹.大学对周边住宅价格影响研究——以浙江大学紫金港校区为例[J].浙江海洋学院学报：人文科学版,2010,27(3)：148-151.
[170]钟海玥,张安录,蔡银莺.武汉市南湖景观对周边住宅价值的影响——基于Hedonic模型的实证研究[J].中国土地科学,2009,23(12)：63-68.
[171]陈立定,欧阳安蛟.试论城市地价动态变化与城市动态规划的互动关系[J].城市发展研究,2005,12(1)：54-57.
[172]高金兰,袁希平,甘淑.城市用地规模与城市地价的相关性研究——以湖北省为 例[J].昆明理工大学学报：社会科学版,2011,11(2)：69-73.
[173]谢戈力,张晓平.宏观规划要素对城市间地价水平差异的影响——以广东省为例[J].热带地理,2011,31(5)：474477.
[174]冷炳荣,杨永春,韦玲霞,等.转型期中国城市容积率与地价关系研究——以兰州市为例[J].城市发展研究,2010,17(4)：116-122.
[175]郭文刚,崔新明,温海珍.城市住宅特征价格分析：对杭州市的实证研究[J].经济地理,2006,26(S1)：172-177.
[176]罗罡辉,吴次芳,郑娟尔.宗地面积对住宅地价的影响[J].中国土地科学,2007,21(5)：66-69.
[177]曾向阳,张安录.土地出让微观决策对地价的影响：模型与实证[J].资源与产业,2007,9(3)：77-80.
[178]唐兴霖.诺思的国家与政府理论述评[J].中国矿业大学学报：社会科学版,2000(2)：22-29.
[179]盖凯程,李俊丽.中国城市土地市场化进程中的地方政府行为研究[J].财贸经济,2009(6)：121-126.
[180]曼昆.经济学原理：微观经济学分册[M].梁小民,梁砾,译.第五版.北京：北京大学出版社,2009.
[181]保罗·萨缪尔森,威廉·诺德豪斯.经济学[M].萧琛,译.第18版.人民邮电出版社,2008.
[182]张小宏,郑思齐.住宅用地供给短缺背后的地方政府动机[J].探索与争鸣,2010(11)：54-58.
[183]郑思齐,师展.“土地财政”下的土地和住宅市场：对地方政府行为的分析[J].广东社会科学,2011(2)：5-10.
[184]Alonso W. Location and Land Use[M]. Cambridge, MA:Harvard University Press, 1964.
[185]杜宁.汽车使用税费与城市空间发展的关联性研究——基于城市土地租金竞价函数的分析方法[J].城市规划,2010,34(12)：64-70.
[186]Aaron H J, Feldstein M S, Inman R. The Economics of Public Services[J]. The Economics of Public Services,1977.
[187]Arnott R J, Lewis F D. The transition of land to urban use[J]. The Journal of Political Economy,1979:161-169.
[188]Lancaster K J. A new approach to consumer theory[J]. Journal of political economy, 1966,74(2):132-157.
[189]Rosen S. Hedonic prices and implicit markets:product differentiation in pure competition[J]. Journal of political economy,1974,82(1):35-55.
[190]李玲,朱道林,胡克林.北京市城区住宅地价的时空变化规律[J].经济地理,2011,31(4)：655-659.
[191]武文杰,张文忠,刘志林,等.北京市居住用地出让的时空格局演变[J].地理研究,2010,29(4)：683-692.
[192]朱晨.中国中心城市第二住宅的地理空间分布特征[J].经济地理, 2006,26(6)：945-948.
[193]赵晶,陈华根,许惠平.20世纪下半叶上海市居住用地扩展模式、强度及空间分异特征[J].自然资源学报,2005,20(3)：400-406.
[194]余琪.转型期上海城市居住空间生产模式及布局形态演进[J].城市规划学刊,2010(5)：15-25.
[195]齐心,鲁黛迪.北京城市内部居住迁移的空间模式研究[J].城市发展研究,2012,19(12)：16-21.
[196]李志刚.中国大都市新移民的住房模式与影响机制[J].地理学报,2012,67(2)：189-200.
[197]易成栋,黄友琴.中国城市自有多套住宅家庭的空间模式实证研究[J].经济地理,2010,30(4)：585-590.
[198]苏振民,林炳耀.城市居住空间分异控制：居住模式与公共政策[J].城市规划,2007,31(2)：45-49.
[199]范雪峰.小城镇基准地价评估中立体型综合用地地价研究[D].吉林大学土地资源管理,2006.
[200]杜彬,张丽.应用基准地价评估小城镇立体型综合用地地价研究[J].农机化研究,2005(4)：19-22.
[201]杜彬,张丽,赵英娜.应用基准地价评估城镇综合用地地价的方法[J].南京师大学报：自然科学版,2005,28(2)：112-116.
[202]卢新海,李书宁,赵凯.城镇基准地价土地用途细化分类研究——以武汉市商业用地为例[J].中国房地产,2012(4)：18-28.
[203]唐健,谭永忠,徐小峰.中国商住用地价格倒挂及其产生机理[J].中国土地科学,2011,25(1)：22-29.
[204]陈英,张军,周冬梅,等.立体综合用地宗地价格评估方法研究[J].中国土地科学,2010,24(8)：9-15.
[205]中华人民共和国国土资源部.GB/T 18508-2001城镇土地估价规程[S].国家质检总局,2001.
[206]陆丽珍.城镇综合用地宗地地价评估方法研究[J].经济地理,2002,22(S 1)：96-99.
[207]颜好洁,冯友健.基准地价分类修正综合法在综合用地地价评估中的应用[J].浙江大学学报：理学版,2005,32(5)：579-583.
[208]冯友健,林志鹤.小城镇综合用地宗地地价评估方法研究[J].中国资产评估,1999(6)：25-27.
[209]徐一萍,李国安,唐绍祥,等.商住综合用地评估的加价模型[J].宁波大学学报：理工版,2000,13(4)：55-58.
[210]中华人民共和国住房和城乡建设部.GB 50137-2011城市用地分类与规划建设用地标准[s].中国建筑工业出版社,2010.
[211]Little R J A, Rubin D B. Statistical analysis with missing data[M]. Wiley New York, 1987.
[212]韩卫国,王劲峰,胡建军.交通流量数据缺失值的插补方法[J].交通与计算机,2005,23(1)：39-42.
[213]Roger B, Others. Implementing spatial data analysis software tools in R[J].
[214]Yuan Y C. Multiple imputation for missing data:concepts and new development (version 9.0),2000[C].
[215]Muth E N B, Kaplan D, Hollis M. On structural equation modeling with data that are not missing completely at random[J]. Psychometrika,1987,52(3):431-462.
[216]Hox J J. A review of current software for handling missing data[J]. Kwantitatieve Methoden,1999,20:123-138.
[217]赵慧,甘仲惟,肖明.多变量统计数据中异常值检验方法的探讨[J].华中师范大学学报：自然科学版,2003,37(2)：133-137.
[218]毋红军,刘章.统计数据的异常值检验[J].华北水利水电学院学报,2003(1)：69-72.
[219]张德然.统计数据中异常值的检验方法[J].统计研究,2003(5)：53-55.
[220]薛薇.SPSS统计分析方法及应用[M].第2版.电子工业出版社,2010.
[221]冯艳.1990年代以来武汉城市土地开发及空间发展规律研究[D].华中科技大学,2007.
[222]吴曙光.武汉城市空间演变与土地出让研究[D].中国地质大学(武汉),2012.
[223]任超群.土地出让价格信号对房价的影响研究[D].浙江大学企业管理,2011.
[224]梅志雄,黄亮.房地产价格分布的空间自相关分析——以东莞市为例[J].中国土地科学,2008,22(2)：49-54.
[225]孟斌,张景秋,王劲峰,等.空间分析方法在房地产市场研究中的应用——以北京市为例[J].地理研究,2005,24(6)：956-964.
[226]陈思源,曲福田,曹大贵,等.ESDA支持下的城市地价分布信息提取[J].国土资源遥感,2006(3)：47-50.
[227]Anselin L. Interactive techniques and exploratory spatial data analysis[J]. Geographical Information Systems principles techniques management and applications,1996,1.
[228]Rey S J. Spatial empirics for economic growth and convergence[J]. Geographical Analysis,2001,33(3):195-214.
[229]张鸿辉,曾永年,吴林,等.南京市地价空间结构的演变[J].资源科学,2008,30(4)：591-597.
[230]高伟丽.基于因子分析和1ESDA的我国旅游业发展差异性及其影响因素研究[D].南京理工大学,2012.
[231]刘聪粉,张瑞荣.云南省地区经济差异的空间统计分析[J].云南财经大学学报,2009,25(3)：118-126.
[232]马晓冬,马荣华,徐建刚.基于ESDA-GIS的城镇群体空间结构[J].地理学报,2004,56(6)：1048-1057.
[233]陈思源,曲福田,倪绍祥,等.GIS空间分析支持下的城市地价分布研究——以江苏省镇江市为例[J].南京农业大学学报,2005,28(3)：119-122.
[234]郭龙,张海涛,陈家赢,等.基于协同克里格插值和地理加权回归模型的土壤属性空间预测比较[J].土壤学报,2012,49(5)：1037-1042.
[235]温海珍.城市住宅的特征价格：理论分析与实证研究[D].浙江大学企业管理,2004.
[236]Hass G C. A Statistical Analysis of Farm Sales in Blue Earth County, Minnesota, as a Basis for Farm Land Appraisal [D]. the University of Minnesota,1922.
[237]Court A T. Hedonic Price Indexes with Antomotive Examples:General Motors, New York,1936[C].
[238]Waugh F V. Quality factors in fluencing vegetable prices[J]. Journal of Farm Economics,1928(10):185-196.
[239]Goodman A C. Andrew Court and the invention of hedonic price analysis[J]. Journal of Urban Economics,1998,44(2):291-298.
[240]Griliches Z. Price Indexes and QuaIity Change[M]. Cambridge:Harvard University Press ,1971.
[241]毕宝德.土地经济学[M].第五版.北京：中国人民大学出版社.
[242]Mok H M K, Chan P P K, Cho Y S. A hedonic price model for private properties in Hong Kong[J]. The Journal of Real Estate Finance and Economics,1995,10(1):37-48.
[243]Yang Z. An application of the hedonic price model with uncertain attribute-The case of the People's Republic of China[J]. Property management,2001,19(1):50-63.
[244]冯艳芬,梁小斯,吴大放.基于Hedonic模型的广州地铁1号沿线住宅价格分析[J].广州大学学报：自然科学版,2011,10(4)：90-95.
[245]聂冲,温海珍,樊晓锋.城市轨道交通对房地产增值的时空效应[J].地理研究,2010,29(5)：801-810.
[246]蒋芳,朱道林.基于GIS的地价空间分布规律研究——以北京市住宅地价为例[J].经济地理,2005,25(2)：199-202.
[247]石忆邵,郭惠宁.上海南站对住宅价格影响的时空效应分析[J].地理学报,2009,64(2)：167-176.
[248]石忆邵,张蕊.大型公园绿地对住宅价格的时空影响效应——以上海市黄兴公园绿地为例[J].地理研究,2010,29(3)：510-520.
[249]钟海明,张安录,蔡银莺.武汉市南湖景观对周边住宅价值的影响——基于Hedonic模型的实证研究[J].中国土地科学,2009,23(12)：63-68.
[250]李郇,符文颖.城市政府基础设施投资在住宅市场的资本化考察——基于广州价格数据的Hedonic模型构建[J].地理研究,2010,29(7)：1269-1280.
[251]秦波,孙亮.容积率和出让方式对地价的影响——基于特征价格模型[J].中国土地科学,2010,24(3)：70-74.
[252]王婵婵,丁和庚,吴群.容积率对城市住宅用地交易价格影响的定量研究——以南京市为例[J].资源科学,2009,31(1)：123-129.
[253]党杨.中国城市土地价格影响因素研究[D].吉林大学区域经济,2011.
[254]刘春燕,沈禹民.宗地面积影响地价的作用机制和规律[J].浙江国土资源,2005(8)：45-47.
[255]苏海龙,徐芳.上海地铁8号线对城市住宅价格的时空效应定量研究[J].上海交通大学学报,2010,44(12)：1704-1710.
[256]Bowes D R, Ihlanfeldt K R. Identifying the impacts of rail transit stations on residential property values[J]. Journal of Urban Economics,2001,50(1):1-25.
[257]Bae C H C, Jun M J, Park H. The impact of Seoul's subway Line 5 on residential property values[J]. Transport Policy,2003,10(2):85-94.
[258]李志辉.基于Hedonic模型的武汉住宅特征价格研究[D].华中农业大学土地资源管理,2008.