Spatial Dependence and House Price Index Construction

Accurate estimation of prevailing metropolitan housing prices is important for both business and research investigations of housing and mortgage markets. This is typically done by constructing quality-adjusted house price indices from hedonic price regressions for given metropolitan areas. A major limitation of currently available indices is their insensitivity to the geographic location of dwellings within the metropolitan area. Indices are constructed based on models that do not incorporate the underlying spatial structure in housing data sets. In this article, we argue that spatial structure, especially spatial dependence latent in housing data sets, will affect the precision and accuracy of resulting price estimates. We illustrate the importance of spatial dependence in both the specification and estimation of hedonic price models. Assessments are made on the importance of spatial dependence both on parameter estimates and on the accuracy of resulting indices.     

Spatial and Temporal Dependence in House Price Prediction

This paper incorporates spatial and temporal dependence among housing transactions in predicting future house prices. We employ the spatiotemporal autoregressive model and structure the spatial and temporal weighting matrices as in Pace et al. (1998). We control for the time variation of both the attribute prices and the spatial and temporal dependence parameters through performing the analysis on an annual basis. Spatial heterogeneity is accounted for using experience-based definition of submarkets by real estate professionals. Using a comprehensive housing transaction data set from the Dutch Randstad region, we show that integrating the spatial and temporal dependence within the hedonic modeling improves the prediction power as compared to traditional hedonic model that neglects these effects.     

Evaluating the Usefulness of the American Housing Survey for Creating House Price Indices

The American Housing Survey (AHS) is a valuable source of information on houses and occupants over time. The AHS has several advantages over sales data for use in the creation of price indices: it is readily available, has frequent observations over time and space, has data from the late 1970s through the mid-1990s, includes houses that do not sell, as well as those that do, and has information on the occupants. The drawbacks include: a time lag between the interview and the release of the data, data suppression issues, owner-stated house values, and a lack of neighborhood information. In this study, we use the metropolitan version of the AHS, which has been supplemented with the original survey data as well as Census tract data for three cities over 14 years to examine whether the AHS can be used to create indices. Indices are estimated using hedonic, repeat valuation, and hybrid techniques, overcoming some of the problems inherent in the estimation of indices. We find that the data-suppression issues and the owner-stated house values are not problematic. The biggest drawback of the AHS is its lack of objective information on neighborhood quality.     

Spatial Competition and Shopping Externalities: Evidence from the Housing Market

In search markets, greater spatial concentration of sellers increases price competition. At the same time, though, a greater concentration of sellers can create a shopping externality by attracting more buyers to the site. Using housing sales data, we test for spatial competition and shopping externality effects on prices and marketing time. We find that they reflect both competitive and shopping externality effects from surrounding houses, although the relative strength varies with how fresh the house is in the market, the freshness of surrounding houses, and the phase of the market cycle. New listings have the strongest shopping externality effect on neighboring houses that have been on the market for some time. Vacant houses have their strongest competition effects in the declining market and externality effects in the rising market. Fresh houses on the market reap little benefit from shopping externalities in all phases of the market cycle.     

House Price Markups and Mortgage Defaults

The transaction price of identical housing units can vary widely due to heterogeneity in buyer and seller preferences, matching, and search costs, generating what we term “markups” above or below the average market price. We measure markups for 3.4 million purchase-money mortgages and show that they can predict mortgage defaults and credit losses conditional on default even after accounting for collateral coverage (loan-to-value ratio) and a comprehensive set of other covariates. The findings suggest that standard collateral coverage estimation may be inaccurate, with implications for both individual and portfolio-level credit risk assessment.     

政策不确定、宏观冲击与房价波动——基于LSTVAR模型的实证分析

本文利用Baker等人提供的中国政策不确定性指数,结合1999年1月-2014年3月我国宏观经济数据,在构建我国房价短期波动模型的基础上,采用LSTVAR模型以及广义脉冲响应函数实证分析了不同政策不确定性环境下宏观变量冲击对于房价波动的影响。理论模型表明,宏观环境向好会引起房价的正向波动,而且这种波动会随着政策不确定性的增加而加大;不同的政策不确定性背景下,宏观冲击对于房价波动的影响存在差异性。实证结果表明,在政策不确定程度较高和较低两种不同的状态下,宏观变量的冲击对于房价波动的影响具有明显的非对称性;较高的政策不确定性程度会延缓个人的购房消费和投资以及房地产企业的供给,甚至引起市场失灵,从而引起房价的无谓波动;政策不确定程度较高时,房屋买卖双方的预期也会引起房价的“超调”,进而加剧了房价的波动。     

Index Revision,House Price Risk,and the Market for House Price Derivatives

It is widely recognized that options and futures markets for housing can reduce and manage the risks inherent in consumers’ large investments in housing equity. The integrity of such markets depends, however, upon the use of transparent and replicable benchmarks for house prices and settlement values. In the USA, a series of state and metropolitan indexes have been produced by a government agency (the US Office of Housing Enterprise Oversight, OFHEO), and they have been widely disseminated for over a decade. By construction, the entire historical path of each of these indexes is, in principle, subject to revision quarterly, that is, every time the index is recalculated and data are published. This paper provides the first analysis of the magnitude and bias of these revisions, and it analyzes their systematic effects on the settlement prices in housing options markets. The paper considers the implications of these magnitudes for the development of risk-reducing futures markets.

银行信贷、房地产价格与经济增长的非线性关系研究——基于省际面板平滑转换模型的实证检验

选用中国2000~2014年31个省的面板数据,以银行信贷为转换变量,通过构建面板平滑转换模型对我国房地产价格与经济增长的非线性关系进行考察。研究发现：当信贷增长率低于28.74%时,房价增长率对经济增长产生比较显著的正向影响;当信贷增长率高于28.74%时,房价增长率对经济增长起到了明显的阻碍作用。因此,为了实现“稳定房价和保持经济平稳增长”的目标,央行应将信贷增速维持在低增长体制的最优区间中。同时,央行还应该改善信贷结构,鼓励和引导金融资源进行合理配置。     

The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales,Hedonic-Regression,and Hybrid Approaches

This article examines a number of hypotheses that underpin the repeat-sales and hedonic approaches to the construction of housing price indices, as well as the practical problems associated with the implementation of either approach. We also examine a hybrid procedure that combines elements of both the repeat-sales and hedonic-regression techniques. For our sample of individual home sales in Oakland and Fremont California over an 18-year period, repeat-sales methods are subject to sample selection bias; the maintained assumption of time constancy of implicit prices of housing attributes is violated; the repeat-sales estimator is extremely sensitive to influential observations; and the usual method used to correct for heteroskedasticity in repeat-sale housing returns is inappropriate in our sample. Hedonic techniques are better suited to contend with index number problems per se, as they can accommodate changing attribute prices over time. They also appear to give rise to more reliable estimates of price indices, as unusual observations have less effect on estimated price indices. Drawbacks of the hedonic approach include the usual concern with omitted attributes, and their effect on the estimated price index.     

房价调控、地方政府债务与宏观经济波动

在地方政府债务高企的背景下,房价调控能否使资本流向非房地产部门？房价调控如果触发地方政府债务违约,宏观政策应如何应对？本文基于中国宏观经济的特征事实,引入地方政府的土地财政行为,将房价变动与地方政府的偿债能力联系起来。研究表明,由于地方政府依赖土地出让和土地抵押贷款筹集收入,房价管控导致的地价下降会带来地方政府收入的下降,直接影响地方政府的偿债能力。如果地方政府债务不出现违约,那么房价管控带来的地价下降会降低地方政府从金融部门获得的抵押融资额,使非基建部门的融资成本下降,非基建部门投资和产出上升。而如果调控房价带来的地价下降导致地方政府出现债务违约,金融部门资产受损,使金融中介减少贷款和提高贷款成本,带来整个社会的信贷紧缩,经济中各个部门的产出大幅下降。进一步的政策分析表明,有必要在避免地方政府债务违约的同时,使用财政资金补充银行资本金等多种方式稳定金融中介的资产负债表,从而将房价调控对经济的负面影响程度降到最低。     

Housing returns,precautionary savings and consumption: Micro evidence from China

We investigate how changes in home prices affect consumption in China via a wealth channel. Examining a panel of 7955 households via fixed effects and instrumental variable methods, we find a marginal propensity to consume out of housing wealth (home-price MPC) that is concentrated on goods consumed for pleasure rather than necessity. This trend is driven by the value of second homes rather than that of primary residences, suggesting a wealth channel. We further examine whether returns on housing investment, including rental income and home appreciation, fund the wealth channel; however, we find little supporting evidence. In contrast, a reduction in health risk increases the home-price MPC, but a reduction in income risk that also relieves precautionary saving motives does not. Our results are robust to alternative data, common-factor progress, expenditure shocks and bequest motives. We contribute by examining second homes, which carry little of the dual nature of housing that primary residences do, to identify a controversial wealth channel, and by studying the relative effects of health and income risks on the wealth channel.     

住房投机与政策调控对房价波动的影响——基于中国40个重点城市的数据

构建住房需求结构、政策调控和价格的动态系统模型,依据2007-2021年40个重点城市季度数据,考量政策调控对于住房投机和房价波动实施效果。结果显示：住房投机推动了房价上涨,政府住房调控政策对房价波动影响差异显著;异质性分析显示,不同地区政策调控实施效果存在差异。鉴于此,应因城施策、分类指导,同时积极畅通房地产调控政策传导机制,提高传导效率,促进房地产市场平稳健康发展。     

Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models

This research reports results from a competition on modeling spatial and temporal components of house prices. A large, well-documented database was prepared and made available to anyone wishing to join the competition. To prevent data snooping, out-of-sample observations were withheld; they were deposited with one individual who did not enter the competition, but had the responsibility of calculating out-of-sample statistics for results submitted by the others. The competition turned into a cooperative effort, resulting in enhancements to previous methods including: a localized version of Dubins kriging model, a kriging version of Clapps local regression model, and a local application of Cases earlier work on dividing a geographic housing market into districts. The results indicate the importance of nearest neighbor transactions for out-of-sample predictions: spatial trend analysis and census tract variables do not perform nearly as well as neighboring residuals.     

房价、工资与资源配置效率——基于微观家庭数据的实证分析

本文基于中国房价不断提高这一现实背景,利用中国城镇住户微观数据,系统地研究房价对当地住户工资的影响、作用机制及其对地区资源配置效率的影响。研究发现:房价上涨会通过“生活成本效应”和“闲暇替代效应”显著提高当地居民的平均工资水平。同时,由于缺乏劳动生产率为支柱的工资上涨会恶化资源配置效率,本文进一步基于资本劳动比和要素扭曲的视角,考察房价对资源配置的影响及工资在其中的作用,结果发现房价引致的工资上涨确实导致了我国过度的资本深化和过快的产业升级,并降低了地区的资源配置效率。本文为房价影响工资和资源配置问题提供了来自微观家庭的经验证据。     

资源依赖、制度安排与区域创新能力 —基于空间杜宾模型

区域创新能力提升是我国加快建设创新型国家、实现高质量发展的现实需求。 本文通过构建涵盖资源依赖、制度安排与区域创新能力的理论模型分析其内在关系并提出假 说,运用2000-2016年全国30个省（区、市）的面板数据与空间杜宾模型,检验三者之间的影 响及空间溢出效应。研究结果表明：（1）资源依赖程度越高,越不利于本地区创新能力提升;（2）有效率的制度安排对区域创新能力有正向促进作用;（3）从空间溢出效应来看,本地区 资源依赖程度越高,越抑制周边地区区域创新能力提升,有效的制度安排能助推周边地区创新能力提高。