Price Indices Based on the Hedonic Repeat-Sales Method: Application to the Housing Market

Shiller (1993) proposes the hedonic repeated-measures (HRM) approach to measuring constant quality price indices for heterogeneous assets such as some bonds and real estate. We derive a mathematical relationship between the coefficients of the HRM model and those from the standard repeat-sales model, and we demonstrate how hedonic characteristics should be chosen for inclusion in the HRM model. Empirical estimates using Fairfax, Virginia, housing transactions data show that the HRM price index evaluated at the mean of the hedonic variable is virtually identical to the standard repeat sales index, just as predicted by our mathematical relationship. But the HRM allows estimation of different price paths for heterogeneous assets. We demonstrate that use of assessed value as the only hedonic characteristic allows parsimonious HRM estimates.     

The Investment Performance of Art in Mainland China

This article investigates price determinants and investment performance for paintings from mainland China using hedonic regression analysis applied to a new dataset from over 190,000 auction transactions. The price index obtained indicates that from 2000 to 2015, the average annual appreciation in value of Chinese art was 8.42% in real USD. Compared with American artwork, global artwork, and traditional financial assets, Chinese art possesses a comparatively better risk and return profile and a low correlation with other assets. Finally, regarding the masterpiece effect, the conclusion is that highly priced Chinese art does not underperform the market.     

甘肃省房地产价格波动对区域金融稳定的影响研究

本文在对甘肃省房地产价格波动及区域金融稳定概念进行界定的基础上,分析了房地产价格波动对区域金融稳定的影响机制,选取了甘肃省2002年至2011年的相关数据,构建了甘肃省区域金融稳定指标体系,并用熵值法计算出区域金融稳定综合指数,然后建立VAR模型,实证检验了房地产价格波动对区域金融稳定的影响.研究发现：在最优滞后2期内,房地产价格波动对区域金融稳定产生一定的影响,并且二者之间呈现负相关关系,也即房地产价格波动越大,区域金融稳定性就会降低,房地产价格波动越小区域金融稳定状况越好.     

Is It Possible to Construct Derivatives for the Paris Residential Market?

Index-based derivatives markets are fast developing in Europe, the US and Asia. Both valuation based and transactions based indices are used as bases for these derivatives contracts. This paper addresses the issue of revision effects on key index parameters, and their implications for derivatives pricing and questions whether these indices may be suitable for derivatives. More specifically, we address the issue of the robustness of the price level, mean, and volatility estimates for two repeat sales real estate price indices: the classical Weighted Repeat Sales (WRS) method and a Principal Component Analysis (PCA) factorial method, as elaborated in Baroni et al. (J Real Estate Res, 29(2):137–158, 2007). Our work is an extension of Clapham et al. (Real Estate Econ, 34(2):275–302, 2006), with the aim of helping judge the efficiency of such indices in designing real estate derivatives. We use an extensive repeat sales database for the Paris (France) residential market. We describe the dataset used and compute the parameters (index price level, trend and volatility) of the indices produced over the period 1982–2005. We then test the sensitivity of these two indices to revisions due to additional repeat-sales transactions information. Our analysis is conducted on the overall Paris market as well as on sub-markets. Our main conclusion is that even if the revision problem may cause substantial concern for the stability of key parameters that are used as inputs in the pricing of derivatives contracts, the order of magnitude of revision on derivatives pricing is not sufficient to deter market participants when it comes to products such a swap contract or insurance contracts against severe losses. We also show that WRS and PCA react differently to revision. The impact of index revision is non negligible in estimating the index price level for both indices. This result is consistent with existing literature for the US and Swedish markets. Price level revision causes moderate concern when trading products such as index futures or price insurance contracts, but could deter option like products. We show that managing this price level revision risk is similar to delta hedging in standard option pricing theory. We also find that although revision impact on index trend can be important, the WRS method seems more robust than PCA. However, the trend revision impact order of magnitude for contracts such as total return swaps is low. Finally, revision influence on volatility estimates seems to have a modest impact on derivatives, and according to the robustness of the volatility estimate, the PCA factorial index seems to fare relatively better than the WRS index. Hence, our findings show that the factorial index could better sustain volatility based derivatives. We also show that whatever the index, managing this volatility revision risk is similar to vega hedging in option pricing theory.

House Price Index Construction in the Nascent Housing Market: The Case of China

Most existing house price index construction methods are developed mainly based on transaction data from the secondary housing market, and are not necessarily suitable for the nascent housing markets where a predominant portion of housing transactions are new units. Using the booming market in China as an example, we evaluate and compare the performances of three most common house price measurement methods in the newly-built housing sector, including the simple average method without quality adjustment, the matching approach with the repeat sales modeling framework, and the hedonic modeling approach. Our analyses suggest that the simple average method fails to account for the substantial complex-level quality changes over time of sales during our sample period, and the matching model fails to control for the effect of developers’ pricing behaviors when adopted in the newly-built sector, hence both are downward biased. Based on this finding, we apply a hedonic method, which allows us to control for both quality changes over time of sales and developers’ pricing behaviors, to 35 major newly-built housing markets and provide the first multi-city constant-quality house price index in China. The new index reveals that the current Chinese housing market is facing a greater risk of mispricing than reported by the existing official metrics.     

鄂尔多斯市房地产市场价格策略研究

近年来,中国房地产业发展迅速,带动了其他行业的发展,在解决我国居民住房问题,经济发展方面起到了重大的作用。房地产市场营销越来越重要了,而在市场营销中的价格策略显得尤为重要。房地产的价格主要是由土地成本、开发、管理费用等构成,同时受自然、政治、经济、社会因素和市场供求关系的影响。鄂尔多斯作为内蒙古快速发展的城市之一,其房地产的价格策略中还存在着制定价格时缺少市场调查,定价以企业为中心,定价策略单一,难以适应市场要求等一些不足。我们要运用合理的价格策略和方法,对存在的不足进行完善,使房地产企业在制定价格时能够应对市场的需求选择合理的定价策略和方法,让房地产企业在实现自己利润的同时,也能满足消费者的需求。     

Prices and returns on paintings: An exercise on how to price the priceless

Art is priceless, but paintings, and other objects, have been sold on markets since the time of the Roman Empire. In this paper, we describe a method for constructing a price index for paintings and compare this index to the indices of various financial markets. In particular, we discuss whether the price of art is related to financial markets, whether the art market is weakly efficient, and whether it is more or less risky than financial markets.     

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.     

Frequency of Transaction and House Price Modeling

This article examines the characteristics and price behavior of repeatedly transacted properties. Using data from four U.S. counties, we estimate hedonic price models of properties grouped by transaction frequency, and compare estimated standard deviations and estimated appreciation rates by group.For each of four counties studied, we find that estimated house price appreciation is systematically higher among properties that transact more frequently. One possible explanation for this result is that purchasers make property improvements that are not adequately reflected in the available data.We also find that estimated standard deviations of the disturbance term show a marked decrease as the frequency of transaction increases. Since frequently transacting properties are not found to be systematically more homogeneous than seldomly transacting properties, we do not attribute this to any increase in homogeneity for frequently transacting properties, but rather to the length of time elapsed between transactions of properties.The findings of this article suggest that repeat-sales price models may need to be adjusted to account for cross-sectional variation in transaction probabilities---that is, the selectivity of the subsample of properties that transacted (or transacted repeatedly) during any finite study period.     

Alternative Methods of Increasing the Precision of Weighted Repeat Sales House Prices Indices

Weighted repeat sales house price indices have become one of the primary indicators used to identify housing market conditions and to estimate the amount of equity homeowners have gained through house price appreciation. The primary reason for the acceptance of this methodology is that it derives a location specific (typically, census division, state or metropolitan area) average change in house prices from repeated observations of individual house prices. It is this repeat attribute that allows repeat sales price indices to claim that it is a preferable index which does a better job of holding quality constant. The amount of time between the two observed prices for a single property is determined by when the home transacts. Some homes transact twice in a period of months and others do not transact for decades. It is likely that individual house price appreciation rates vary from the mean appreciation rate, as estimated by the index, in a systematic fashion. In general, the longer the time between transactions the more variance there is in individual house price appreciation. This paper extends this concept to include new dimensions. For instance, houses that appreciate faster than the mean, as estimated by the index for that location, may experience a different variation structure than homes that appreciate slower. This process can be viewed as an asymmetric treatment of the variance of house price appreciation around the estimated index. In addition, the variance of expensive and affordable homes may also be different and time varying. This paper finds evidence that adding the dimensions of price tiers and asymmetry to the variance estimate has merit and does affect the estimated index as well as homeowner equity estimates. Homeowner equity estimates are especially sensitive to these added dimensions because they depend on both the revised index and the estimated variances, which are specific to each dimension considered—time between transaction, asymmetry, and price tier.     

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.     

Estimating price trends for residential property: A comparison of repeat sales and assessed value methods

The repeat sales methodology for estimating residential price indices is based on actual appreciation of individual properties. On the other hand, the repeat sales method wastes data, typically discarding a large percentage of all sales. This article explores two issues related to the subsample of repeat sales. First, are paired sales representative of the entire population of properties that sold? Second, is there evidence that sample selectivity biases the price trend estimates? Evidence from five metropolitan areas supports a negative answer to the first question and the second question. It appears that a “lemon” or “starter home” effect causes repeat residential sales to be a biased subsample of all transactions. Cumulative price trends for the repeat subsamples can differ from the full samples over periods ranging from two to ten quarters. While short-term price trends can differ widely, there are no systematic differences among the samples over long periods of time (e.g., three years or more).     

Residential property values in a multinodal urban area: New evidence on the implicit price of location

The monocentric model predicts a housing price gradient from the central business district, and it follows that the extension of this model to account for modern multinodal metropolitan areas would predict housing price gradients from multiple employment centers. Empirical analysis using hedonic regression techniques for the estimation of price gradients in a multinodal context is limited. This study extends prior work by exploring nonlinear housing price gradients in a multinodal urban area with an unusually robust database of housing sales transactions, and using a geographic information system for spatial analysis. The results confirm the importance of non-CBD employment centers, a strong if asymmetric CBD price gradient, and significant nonlinear gradients from such other urban amenities as major retail sites and highways.     

Three New Real Estate Price Indices for Geneva,Switzerland

This paper develops constant-quality price indices for three categories of real estate-apartment buildings, vacant land, and condominiums—for the city of Geneva, Switzerland. We use both the hedonic and repeat sales models to estimate the price level and, in turn, the rate of price change. The general pattern of each series suggests that real estate prices in Geneva were fairly stable throughout the 1970s, increased sharply during the 1980s, but gave back some of these gains in the early 1990s. Interestingly, the sharp rise in prices in the second half of the 1980s is very similar to that found in some regions of the United States. We also consider the problem, implicit in the repeat sales method, of revisions in previously estimated price indices as additional data become available in later years.     

The Effect of Tick Size on Price Clustering and Trading Volume

Proposals have been made for some stock exchanges to reduce the size of their trading tick in order to lower transactions costs and, as a result, attract more trading volume and firm listings. We investigate the impact of tick size on price clustering and trading volume when the minimum price change varies with price level. Controlling the firm specific variables, we find that a smaller trading tick tends to exacerbate price clustering. Furthermore, a reduction in tick size is more likely to increase trading volume if the shares are heavily traded. These results suggest that previous studies on other stock markets may have overstated the benefits of a smaller trading tick to traders.     

Anonymity,Stealth Trading,and the Information Content of Broker Identity

This paper examines whether the identity of a broker involved in transactions contains information. Using a sample of transactions from the Australian Stock Exchange—where broker identity is transparent—we provide evidence that consecutive buyer‐/seller‐initiated transactions by the same broker have a relatively high permanent price impact. This implies that broker identity conveys information to market participants, and that markets in which broker identity is disclosed are likely to be more efficient. We also find that medium‐sized trades by the same broker convey greater information than large and small trades, which is consistent with stealth trading by informed investors.     

Asymmetric Information and the Predictability of Real Estate Returns

This article examines the relation between systematic price changes and the heterogeneity of investors information sets in real estate asset markets. The empirical implications rely on a theoretical economy in which information asymmetry alters the dynamic relation between returns and trading volume. We employ a filter-rule methodology to determine predictability in returns and augment the return-based conditioning set with trading volume. The additional conditioning information is necessary since the model is underspecified when predictability is based on returns alone. Our results provide new insight into the coexistence of informational and noninformational exchange in the speculative markets for real estate assets. Specifically, we find that the predictability of real estate returns is generally more indicative of portfolio rebalancing effects than an adverse-selection problem. These results are unique in addressing the time-variation in information asymmetry.     

Empirical tests of real estate market efficiency

Recent empirical research using real estate data has supported the weak and semi-strong forms of the efficient markets hypothesis. Previous studies have not included an estimate of expected appreciation into the tests of market efficiency, thus raising a question about the reliability of the results. We first use a market model to test for market efficiency with results similar to those reported by others. We next use a dynamic multiple indicator, multiple cause (DYMIMIC) model, which extracts a vector of expected appreciation from the price data, to test market efficiency. This approach produces superior results and a stronger conclusion about the efficiency of housing markets. The results indicate limited adjustment delays which can be explained by the existence of high transactions and search costs.     

Valuation in US Commercial Real Estate

We consider a log‐linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REIT returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due to the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices are better modelled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level.     

Constructing Commercial Indices: A Semiparametric Adaptive Estimator Approach

Constant-quality commercial indices generated by ordinary least squares may suffer an efficiency loss due to leptokurtosis caused by outliers in transactions data. When the subsequent nonnormality occurs, substantial improvement in index precision is obtained by estimating the hedonic model using a semiparametric adaptive estimator technique. When this method was applied to 1,846 office transactions that occurred in the Phoenix metropolitan area from January 1997 through June 2004, a substantial standard error reduction of approximately 9% was realized relative to ordinary least squares estimates. The difference in average returns between the semiparametric method and ordinary least squares was about 0.25% in each period, which represents a substantial increase in commercial property index precision. JEL Classification C4 R0