Local House Price Dynamics: New Indices and Stylized Facts

We introduce the first publicly available data set of constant‐quality house price indices for counties, ZIP codes and census tracts in the United States, at an annual frequency, over a 40‐year period. Between 1990 and 2015, house price gradients within large cities steepen, documenting a reversal of decades of increasing relative desirability of suburban locations. Real house prices are more likely to be nonstationary near the centers of large cities. Within‐city differences in house price appreciation at the ZIP code level are, on average, about half of between‐city differences, though this ratio varies depending on the time period and city size.     

Local House Price Diffusion

We contribute to the literature on house price diffusion by carrying out our analysis at three levels: CBSA (nationwide), town and census tract (Greater Boston Area). We estimate fixed‐effect models of house price growth on lagged growth (“Persistence”), nearby lagged growth (“Spillovers”) and Fundamentals growth. CBSA‐level Persistence and Spillover Effects are positive and significant. These large ripple/contagion effects likely contributed to the recent national‐level housing downturn. We find evidence of smaller town‐level Persistence and Spillover Effects. Hence, diffusion appears stronger across than within housing markets. Fundamentals and price expectations drive price diffusion, leaving room for bubbles from future price overoptimism.     

Estimating the Lagging Error in Real Estate Price Indices

Real estate indices based on appraisals or sale prices of properties are known for their slow response to market news. These indices can therefore be represented (in logarithm) as the sum of a latent "true" price index and a lagging error. We show that the latent appreciation return and the lagging error can be jointly estimated in a state–space model, which has two key features. First, it employs exogenous variables known to predict asset returns to predict the latent appreciation return. Second, it incorporates known sources of the lagging error, such as the partial adjustment in observed index to the latent appreciation return and the seasonality in reappraisal quality. We find that, after the estimated lagging errors are removed, the appraisal–based National Council of Real Estate Investment Fiduciaries returns become more informative and hence exhibit (i) greater variance, (ii) weaker auto correlation, (iii) higher correlation with the returns of the securitized real estate and (iv) more timely response to market news.     

A Methodology for Constructing Vacant Land Price Indices

Existing estimates of movements in vacant land prices are limited to a few metropolitan areas and infrequent time intervals. This paper develops a new methodology for estimating vacant land price trends for subareas within states and metropolitan areas. It utilizes data from a sales ratio study, a large database available in most states. The methodology uses assessed value to control for "hedonic characteristics" associated with the property and its location. A model is developed to correct assessed value for measurement errors. Statistical results for forty-one Connecticut towns indicate that the model provides a reasonable compromise between data availability and accuracy of price trend estimates.     

On the Relation between Local Amenities and House Price Dynamics

This study explores the extent to which local amenities are related to house price volatility, returns and risk‐adjusted returns across 238 MSAs. We find strong evidence that high amenity areas experience greater price volatility. In regards to returns, high amenity areas experience greater (lower) real returns in appreciating (depreciating) markets. However, high amenity areas experience little to no abnormal risk‐adjusted returns. Results from the study are robust to an endogenous treatment of amenities and land supply elasticity. Overall, we conclude that the desirability of a metropolitan area is a significant channel through which land values drive house price dynamics.     

Estimating the House Foreclosure Discount Corrected for Spatial Price Interdependence and Endogeneity of Marketing Time

Most previous empirical research estimates a greater than 20% discount associated with the sale of foreclosed properties. Under the assumption that the real estate market is somewhat efficient, such a large discount would be counterintuitive. We argue, and empirically show, that the estimated foreclosure coefficients in most of the previous research are upward biased because they do not control for variables such as the physical condition of the property and the relationship between marketing time and price. Accounting for these factors and correcting for two types of spatial price interdependence, our results show that estimates of foreclosure discount reported by previous studies are about one-third higher than the true discount caused by foreclosure per se .     

Measuring House Price Bubbles

Using data for six metropolitan housing markets in three countries, this article provides a comparison of methods used to measure house price bubbles. We use an asset pricing approach to identify bubble periods retrospectively and then compare those results with results produced by six other methods. We also apply the various methods recursively to assess their ability to identify bubbles as they form. In view of the complexity of the asset pricing approach, we conclude that a simple price–rent ratio measure is a reliable method both ex post and in real time. Our results have important policy implications because a reliable signal that a bubble is forming could be used to avoid further house price increases.     

GMM Repeat Sales Price Indices

Illiquid assets are widely spread within the economy but their indices are difficult to measure. This paper proposes a Generalized Method of Moment (GMM) repeat sales regression for estimating illiquid asset price indices. This method has estimators that are arithmetic averages of individual asset returns. This method is able to estimate custom-weighted indices, including equal- and value-weighted indices. It can incorporate hedonic variables to improve estimation accuracy, and it can work with a reweighting technique to mitigate a biased sample problem. Simulations based on artificial markets indicate that the method is more accurate than some alternatives in both efficient and sluggish markets, with and without temporal aggregation. As an application, we use this method to estimate a commercial property price index.     

A Varying Parameters Approach to Constructing House Price Indexes

Conventional housing price index models assume interperiodparameter stability and typically employ either repeat sales or hedonic methodologies. This paper introduces a method of index construction that combines multiple sales observations with single sale transactions while permitting characteristics prices from hedonic regressions to vary over time. A test for interperiod parameter stability is provided. Each period's data are arranged by location and repeat sales are matched by rows. This construction allows greater use of sample information and acknowledges the unique contribution of repeat sales to the estimation process. It also produces intertemporal error correlations that can be beneficially exploited by the seemingly unrelated regressions (SUH) technique. The paper also demonstrates a significance test for error correlation and discusses the treatment of unequal numbers of observations among index periods.     

Canadian Inter-City House Price Differentials

The purpose of this paper is to identify the sources of intercity house price differentials in Canada. The results indicate that demand factors are important explanatory variables; a 1% increase in the income of households raises house prices by 1.11%; higher rates of anticipated inflation result in higher house prices as households increase their demand for real assets such as housing during inflationary periods; and finally, the fraction of households that are non-family households is positively associated with house prices. These results are in agreement with those of other countries.     

The Influence of Reference Group House Size on House Price

This article examines the effect of a change in housing consumption of various reference groups on predicted own house price. I employ a spatial autoregressive model and find that an increase in average house size of the eight nearest neighbors and the largest houses in the district has a negative effect on predicted house price, whereas the effect of an increase in average house size of the further neighbors (9th through 16th neighbors) and the smallest houses in the district on predicted house price is positive. This suggests that the “envy effect” dominates with respect to the nearest and largest neighbors, whereas the “basking in the reflected glory” effect dominates with respect to the further smallest neighbors.     

A Note on the Bias in House Price Capitalization Models

Recent research efforts concerning the capitalization of low-rate, seller-supplied financing have employed hedonic pricing models that may produce biased estimates of the capitalization process. The bias results when properties sold with owner financing are included in the researcher's sample. This note discusses the nature of the bias and suggests a possible solution.     

The Economic Implications of House Price Capitalization: A Synthesis

In this article, I synthesize an emerging literature that explores the conditions under which public and private investments and intergovernmental transfers are capitalized into local house prices and the broader economic implications of such capitalization. The main insights are: (1) house price capitalization is more pronounced in locations with strict regulatory and geographical supply constraints; (2) capitalization can induce the provision of durable local public goods and club goods; and (3) capitalization effects—which are habitually ignored by policy‐makers—have important adverse consequences for a wide range of policies such as intergovernmental aid and the mortgage interest deduction.     

基于ESDA方法与空间计量模型的房价溢出效应分析

一个地区房价的波动可以通过时间滞后传递到其他地区,从而产生房价溢出效应。本文以我国31个省际区域2005～2014年的数据为样本,运用探索性空间数据分析（ESDA）对31个省的房价空间分布格局及演变态势进行分析。然后运用空间计量模型分析我国省际房价变动的影响因素,并从地理因素和经济因素两个方面研究房价溢出效应。研究结果表明：中国31个省域间的房价存在明显的空间相关性;地区的城市化率、城镇就业人员平均货币工资、二、三产业产值占GDP比重对房价有显著的影响,房价存在显著的空间溢出效应,经济距离对地区房价影响比地理距离的影响更显著。     

Hedging House Price Risk in China

The increasing risk associated with China's housing prices is globally recognized. However, hedging this risk is challenging because of a lack of financial derivatives on China's housing assets. We suggest that the short sale of futures contracts for construction raw materials, i.e., iron ore or/and steel, can act as useful tools to hedge the systematic risk of China's new home price. We first present evidence that there is a strong and stable correlation between changes in China's housing prices and global steel/iron ore prices. Using a hedging strategy model, we then show that, during the sample period between 2009 and 2015, 20.6% of the total unpredicted variance in Chinese housing prices can be hedged by shorting rebar and iron ore futures. We further examine this strategy with an event study based on the announcement of the “home‐purchase restriction” policy in April, 2010. The cumulative abnormal returns show that both steel and iron ore prices reacted significantly to this negative shock, and therefore the proposed strategy could substantially help investors offset losses in the housing market. We finally provide some evidences that this strategy can also help investors in specific regional housing markets, or the resale housing markets.     

Alternative Housing Price Indices: An Evaluation

This paper reports on research in which eleven alternative housing price indices are constructed for two Vancouver neighbourhoods for the period from 1957 to 1979. Three criteria for good indices are presented, and the eleven indices, as well as several government and industry indices are evaluated in accordance with those criteria. It is determined that, almost surprisingly, an index based on mean sales values performs well, as do several of the hedonic price equation based indices. Several policy implications of the analysis are then discussed.     

On Choosing Among House Price Index Methodologies

This paper compares housing price indices estimated using three models with several sets of property transaction data. The commonly used hedonic price model suffers from potential specification bias and inefficiency, while the weighted repeat-sales model presents potentially more serious bias and inefficiency problems. A hybrid model combining hedonic and repeat-sales equations avoids most of these sources of bias and inefficiency. This paper evaluates the performance of each type of model using a particularly rich local housing market database. The results, though ambiguous, appear to confirm the problems with the repeat sales model but suggest that systematic differences between repeat-transacting and single-transacting properties lead to bias in the hedonic and hybrid models as well.     

House Price Indexes: Issues and Results

AREUEA is pleased to acknowledge the support of the National Association of REALTORS for this special issue on house prices. We are particularly grateful to John Tuccillo, Senior Vice President and Chief Economist at NAR, for recognizing the importance of this emerging research area. The editors also acknowledge the support of their colleges at The Ohio State University and of the Homer Hoyt Institute.