空间分析在住宅价值评估中应用研究综述

住宅是一种异质性商品,它的构成使用价值的各个特征之间有明显的差异,因此特征价格定价模型广泛用于住宅的价值评估。但是由于住宅数据中常常表现出空间问题,使得传统的特征价格模型不再适用,空间效应在不动产领域的存在引起了学者们的广泛关注。对空间分析在住宅价值评估中的应用研究进行了回顾和阐述,首先分析空间效应的来源和影响,讨论了在传统模型中纳入空间效应的重要性,接着阐述如何对这些空间效应进行有效建模和检验,并分析了进一步研究的方向。     

基于MGWR模型的二手住宅价格研究——以成都市主城区为例

利用网络爬虫技术获取成都市二手住宅交易数据,基于多尺度地理加权回归模型研究成都市主城区2021年二手住宅价格空间关联特征与影响机制。结果表明：(1)成都市主城区二手住宅价格整体空间分异呈现明显的“核心—外围”模式,高值区集聚分布于核心增长区域内,空间非均衡性显著。(2) MGWR模型相较于传统的GWR模型结果更加可靠,这主要是因为MGWR模型能够捕捉到不同影响机制内部的尺度差异,从而避免模型中过多的噪声与误差。(3)住宅价格对区位特征较为敏感,而且呈现出显著的空间异质性,通过逐步回归法选取的所有变量中,教育设施的影响规模最低,其他具有空间异质性的影响因素依次包括：商业配套设施、地铁、休闲配套设施、住宅房龄、物业费及距城市中心距离。     

住宅建筑模型在设计构思阶段的作用

住宅建筑模型是在建筑设计中用以表现住宅建筑物的面貌和空间关系的一种手段,是建筑师进行建筑创作不可缺少的的设计"语言",它体现了建筑设计师对平面与立体、空间与建筑之间的感受,突破了传统二维表现的局限性,有利于设计方案的进一步深入和完善。文章通过对住宅建筑模型概念的介绍,分析了模型的设计特征和设计制作原则,阐述了模型的制作过程对整个设计构思阶段的作用。     

地铁沿线房地产价值评估模型分析

本文从实证角度出发,以成都市地铁1、2号线沿线住宅样本为例,研究了成都市地铁交通对沿线住宅价格的影响规律。采用特征价格模型(Hedonic模型)作为研究的基础模型,利用SPSS16.0软件对特征价格模型的线性、对数、半对数三种方程形式进行了回归分析,检验结果误差较小。该模型可用于成都市地铁沿线住宅价格的预测,具有一定的参考价值。     

新乡市普通住宅价格空间分布特征研究

文章利用新乡市2007—2008年普通住宅商品房的交易均价资料,借助arcgis9.2软件技术平台,采用GIS空间分析的方法对新乡市普通住宅房价空间分布进行了模拟,得到新乡市普通住宅价格的空间分布图和三维模型图,并通过计算Moran′I值对新乡住宅价格空间分布进行了自相关性分析,在此基础上揭示住宅价格的空间分布特征,分析其影响因素。研究结果表明:新乡市房价呈现出由中心向外递减的趋势,区域差异明显;空间分布上具有一定的正相关性。其中区位条件、交通可达性和城市规划指向性是影响住宅价格的主要因素。     

东北地区住宅价格变动的比较预测和分析

文章从市场入手，寻求影响住宅业务因素之间的相关关系，定量分析了影响住宅价格变动的因素，分析住宅价格时间上的变动趋势，并对住宅价格下一步的上涨空间进行了预测。并应用了灰色模型，对东北地区住宅价格进行了关联度分析预测。     

区域创新活动的空间效应及影响因素研究

研究目标：探究区域创新活动的空间效应及影响因素。研究方法：采用1998～2014年中国30个省份的面板数据,运用空间计量经济学,建立静态与动态空间面板模型,并从地理特征与社会经济特征两方面构建5个空间权重矩阵进行实证分析。研究发现：区域创新活动具有正向空间相关性,并呈现明显的空间集聚现象;地理特征与社会经济特征对区域创新活动均产生影响,其效果以社会经济特征更大;利用动态空间面板模型进行估计优于静态空间面板模型。研究创新：根据地理距离空间矩阵进行的空间相关性检验与R&D资本存量新估算方法使模型结果更准确;交通水平距离空间矩阵构建合理。研究价值：进行区域创新空间相关性分析时,可准确选择适当模型、估算方法及影响因素。     

含空间自回归误差项的空间动态面板模型的检验与模拟

研究目标：探究含空间自回归误差项的空间动态面板数据（SDPD）模型选择和假设检验结果的水平扭曲、检验功效。研究方法：构建含空间自回归误差项的SDPD模型的空间Hausman、LM和LR检验统计量,选择蒙特卡洛模拟进行分析。研究发现：含空间自回归误差项的SDPD模型的各类检验统计量的大样本性质良好;时空滞后项对空间Hausman检验结果的影响比空间滞后项显著;条件LMλ|α、LRλ|α检验是含空间自回归误差项随机效应SDPD模型的最优检验统计量,时空滞后项对LM、LR检验结果的影响比自回归误差项更显著。研究创新：解析了SDPD模型中各空间关联项系数的波动对模型检验精度的影响。研究价值：探究含空间自回归误差项SDPD模型的选择问题,为实证提供理论依据。     

外商直接投资对我国能源强度的空间效应分析

现有有限的关于FDI影响能源强度的研究均从时间维度进行,忽略了FDI的空间外溢效应。本文利用空间自相关方法论证了FDI的空间特性。在此基础上,运用空间回归模型方法计量分析了FDI对能源强度作用的空间关系。基本结论是:(1)FDI具有显著的空间溢出效应;(2)不仅对本地区能源强度,FDI通过溢出效应对周边地区能源强度的降低也有明显的作用;(3)无论对本地区还是周边地区,FDI集聚对能源强度的作用在逐年增强。     

基于Hedonic模型的兰州市二手房住宅特征价格研究

Hedonic特征价格模型是研究住宅属性与价格关系的有效手段。文章将hedonic特征价格模型用于兰州市二手房市场研究,分析1150个兰州市二手房的详细资料,进行hedonic多重回归分析,并用SPSS软件模拟特征价格模型。结果显示,半对数模型拟合系数最高,通过半对数特征价格模型讨论了兰州市二手房价格和住房特征要素之间的定量关系。     

Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data

In this paper we investigate housing price volatility within a spatial econometrics setting. We propose an extended spatial regression model of the real estate market that includes the effects of both conditional heteroskedasticity and spatial autocorrelation. Our suggested model has features similar to those of autoregressive conditional heteroskedasticity (ARCH) in the time-series context. We utilize the spatial ARCH (SARCH) model to analyze Boston housing price data used by Harrison and Rubinfeld (1978) and Gilley and Pace (1996). We show that measuring the variability of housing prices is an important issue and our SARCH model captures the conditional spatial variability of Boston housing prices. We argue that there is a different source of spatial variation, which is independent of traditional housing and neighborhood characteristics, and is captured by the SARCH model.     

房价空间关联的动力机制——基于空间Durbin模型的实证研究

城市房价的一个重要特征就是其空间关联性。分析了房价空间关联的四种动力机制,基于一个消费者均衡模型并利用268个城市的房价数据,应用空间Durbin模型实证检验了城市房价的空间关联性。研究表明,我国城市房价存在显著的空间关联性和明显的地区差异,相对于东中部城市,西部城市间房地产市场至少在现阶段还缺乏城市问的关联机制。     

The house price determination process: Rational expectations with a spatial context

Applying the rational expectations hypothesis, this essay models the current value of a house as the conditional expectation of the discounted stream of housing services accruing to the owner of the house. The value of housing services is determined by neighborhood effects as well as the physical attributes of the property itself. In the existing hedonic literature, future transactions have not been utilized to describe neighborhood effects. The rational expectations asset pricing model in this study accounts for expected future neighborhood effects as well as observed current neighborhood effects. The reduced form of the rational expectations model is a spatial autoregressive (SAR) model with two spatial lags. After employing the generalized method of moments (GMM) in estimating the spatial asset pricing model, I find that both expected future transactions and prior transactions in the neighborhood are significant. The inclusion of expected future transaction prices in the neighborhood takes into account the influence of expected changes in the community and factors these potential changes into the current house price. This is consistent with forward-looking households. The forward-looking model generates superior out-of-sample prediction performance relative to both the conventional hedonic model without considering neighborhood effects or the standard spatial hedonic model including only past transactions.     

经济适用房空间布局分析——以北京市为例

经济适用房的建设和布局对城市空间结构和居住者出行具有重要影响。首先采用Kernel密度估计方法计算了北京不同时期经济适用房在不同空间上的建设规模密度,分析其空间布局特征;其次,从经济适用房与地价、交通和主要就业地的相互关系分析经济适用房空间布局的演变。研究表明,北京经济适用房空间布局经历了逐步调整的过程,前期主要分布在城市北部城乡结合地带,后期考虑居民交通出行和到工作地方便等因素,在城市四周较均匀的配置和建设。总体来说,北京市经济适用住房基本分布在城市郊区,就业地与居住地相距较远的矛盾依然突出。建议今后经济适用房空间布局应更加注重主要就业地和居民交通出行的最佳匹配。     

Raising the bar (1)

In this editorial, we summarize and comment on the papers published in issue 11.1 so as to raise the bar in applied spatial economic research and highlight new trends. The first paper employs the J-test to discriminate between two economic-theoretical explanations for the wage curve. The second applies a two-step ML procedure to measure the impact of volatility on economic growth. The third tests for endogeneity in the Spatial lag of X (SLX) model and whether or not the model should be extended to contain a spatial lag. The fourth utilizes the gravity model to test whether or not grids should be merged into larger units of observations. Finally, the last adopts a time-space recursive model to test the ripple effect and (linguistic) border effect hypotheses on housing prices in Belgium.     

The reduced form price elasticity of housing

This paper focuses on the modeling of the housing market. First, there is a discussion of terminology. The importance of distinguishing between housing and structures, and between reduced form and supply elasticities is emphasized. Second, the role of tastes and technology is emphasized. Third, the integration of the housing market into a general equilibrium urban model to investigate such issues as the effects of a housing subsidy is discussed. Throughout attention is drawn to what additional information is needed to provide an adequate empirical characterization of the housing market.     

Hedonic Housing Prices in Paris: An Unbalanced Spatial Lag Pseudo‐Panel Model with Nested Random Effects

This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990–2003. This is done using maximum likelihood estimation, taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four quartiers (quarters), which in turn contain between 15 and 169 blocks (îlot, in French) per quartier. This is an unbalanced pseudo?panel data containing 156,896 transactions. Despite the richness of the data, many neighborhood characteristics are not observed, and we attempt to capture these neighborhood spillover effects using a spatial lag model. Using likelihood ratio tests, we find significant spatial lag effects as well as significant nested random error effects. The empirical results show that the hedonic housing estimates and the corresponding marginal effects are affected by taking into account the nested aspects of the Paris housing data as well as the spatial neighborhood effects.Copyright © 2014 John Wiley & Sons, Ltd.     

Spatial mismatch: An equilibrium analysis

The spatial mismatch hypothesis, first stated by Kain (1968) argues that job decentralization in US cities has contributed to low incomes and high unemployment rates for black Americans. Decentralization relocates job sites to white suburban communities far from the CBD, and housing segregation prevents blacks from relocating their residences near the new workplaces. The purpose of the paper is to analyze an urban equilibrium with spatial mismatch. Despite the existence of a suburban employment center, blacks in the model are forced to live in the central zone they occupied in the original monocentric city, commuting across the white residential area to access suburban jobs. This ‘mismatch’ equilibrium is contrasted with an unrestricted equilibrium where blacks are free to locate wherever they choose.     

北京市公共住房区位布局研究

本文针对城市公共住房的区位布局问题,运用Arcview GIS 3.3软件,采集了北京127个已经建设或即将建设的公共住房数据,分析出北京市公共住房区位布局存在的突出特点是北部过于集中、南部带状分布,不断向外扩张,并产生了空间失配等问题。根据以上问题,提出了在城市中心区、边缘区和新城的公共住房建设区位政策,并指出应大力发展混合住区。     

北京市人口老龄化的空间特征及影响因素

通过分析第五次人口普查资料发现:北京市老年人口呈圈层式分布特征,城市中心区老龄型家庭最多;多因素相关分析表明,自然加龄和非老年人口外迁是造成中心区老龄化的主要原因,年龄结构年轻化的外来人口迁入近郊也成为导致中心区老龄化水平相对更高的因素之一.提出了新建社区户型多样化、完善基层社区的老年福利设施和服务保障体系建设等针对性建议.