Should we Fear the Shadow? House Prices,Shadow Inventory,and the Nascent Housing Recovery

Although a broad-based increase in house prices has been observed over the past year, not everyone is convinced the rise of house prices will persist and lead to a steady recovery of the economy. The main reason for this skepticism is uncertainty about the “shadow inventory”: foreclosed homes held by investors or as REOs, which have not yet hit the market but likely will as market prices rise. The volume of shadow inventory itself in local markets is largely unknown, as is its impact on the housing market. This study quantifies the size of the shadow inventory and investigates the spatial impact of the out-flow of shadow inventory. The scope of our study is a set of housing markets (AZ, CA, and FL) that vary in both their historic housing price volatility as well as institutional factors - such as foreclosure law statutes - that may influence the relationship between the shadow inventory and house price dynamics. To address the endogeneity that characterizes the spatial interaction of house prices and the out-flow of the shadow inventory, we utilize a simultaneous equation system of spatial autoregressions (SESSAR). The model is estimated using measures of the shadow inventory derived from DataQuick’s national transaction history database and county-level house price indices provided by Black Knight. Lastly, because our estimate - as well as all other existing estimates - of the shadow inventory relies upon string matching algorithms to identify entry into and exit out of REO status, we validate the accuracy of our measures of REOs using loss mitigation data from the OCC Mortgage Metrics database.     

The Choice of Methodology for Computing Housing Price Indexes: Comparisons of Temporal Aggregation and Sample Definition

Housing transactions are executed and recorded daily, but are routinely pooled into longer time periods for the measurement and analysis of housing price trends. We utilize an unusually rich data set, covering essentially all arm's length housing sales in Sweden for a dozen years, in an attempt to understand the effect of temporal aggregation upon estimates of housing prices and their volatilities. This rich data set also provides a unique opportunity to compare the results using the conventional weighted repeat sales model (WRS) to those based on a research strategy which incorporates all available information on house sales. The results indicate the clear importance of temporal disaggregation in the estimation of housing prices and volatilities—regardless of the model employed.The appropriately disaggregated model is then used as a benchmark to compare estimates of the course of housing prices produced by the two models during the twelve year period 1981–1993. These results indicate that much of the difference between estimates of price movements can be attributed to the data limitations which are inherent in the repeat sales approach. The results, thus, suggest caution in the interpretation of government-produced price indices or those produced by private firms based on the repeated sales model.     

Selectivity,Quality Adjustment and Mean Reversion in the Measurement of House Values*

This paper develops a model of price formation in the housing market which accounts for the non-random selection of those dwellings sold on the market from the stock of existing houses. The model we develop also accounts for changes in the quality of dwellings themselves and tests for mean reversion in individual house prices. The model is applied to a unique body of data representing all dwellings sold in Sweden's largest metropolitan area during the period 1982–1999. The analysis compares house price indices that account for selectivity, quality change and mean reversion with the conventional repeat sales models used to describe the course of metropolitan housing prices. We find that the repeat sales method yields systematically large biased estimates of the value of the housing stock. Our comparison suggests that the more general approach to the estimation of housing prices or housing wealth yields substantially improved estimates of the course of housing prices and housing wealth.     

Inventories and the automobile market

This article studies the within‐model‐year pricing, production, and inventory management of new automobiles. Using new monthly data on U.S. transaction prices, we document that, for the typical vehicle, prices fall over the model year at a 9.0% annual rate. Concurrently, both sales and inventories are hump shaped. To explain these time series, we formulate an industry model for new automobiles in which inventory and pricing decisions are made simultaneously. The model predicts that automakers' build‐to‐stock inventory management policy substantially influences the time series of prices and sales, accounting for four tenths of the price decline observed over the model year.     

The impact of auctions on residential property prices

This study assesses whether the sale method in residential real estate markets – auction versus private treaty – is a determinant of sale price. Utilising a larger and richer dataset than previous research, we test for a price effect in auction sales in Sydney and Christchurch. When self‐selection biases are corrected for, using two‐stage hedonic regression analysis and a matched sampling procedure, we find no significant difference between prices of properties sold at auction to those sold by private treaty. This conflicts with the conclusions of previous research in the Australian and New Zealand housing markets, which have documented a price premium associated with auction sales.     

Sales and consumer inventory

Temporary price reductions (sales) are common for many goods and naturally result in a large increase in the quantity sold. We explore whether the data support the hypothesis that these increases are, at least partly, due to demand anticipation: at low prices, consumers store for future consumption. This effect, if present, has broad economic implications. We test the predictions of an inventory model using scanner data with two years of household purchases. The results are consistent with an inventory model and suggest that static demand estimates may overestimate price sensitivity.     

The Effect of Short Selling on Bubbles and Crashes in Experimental Spot Asset Markets

A series of experiments illustrate that relaxing short‐selling constraints lowers prices in experimental asset markets, but does not induce prices to track fundamentals. We argue that prices in experimental asset markets are influenced by restrictions on short‐selling capacity and limits on the cash available for purchases. Restrictions on short sales in the form of cash reserve requirements and quantity limits on short positions behave in a similar manner. A simulation model, based on DeLong et al. (1990) , generates average price patterns that are similar to the observed data.     

Price spreads and residential housing market liquidity

Most studies of housing market liquidity have measured liquidity in terms of time on the market (TOM), and have sought to explain TOM in terms of property characteristics and measures of market conditions. This paper departs from past studies of housing market liquidity by examining the spread between the listing and contract prices.We develop theory to explain the price spreads in the residential housing market. The model includes the list price of the home, the cost of the search, the standard deviation of offer prices, and TOM. Empirical tests using 3,597 sales for 25 months show a robust relationship of housing market spreads and these variables. Listing price and cost of search have the predicted positive coefficients, and the standard deviation of price offers is found to be negatively related to the price spread.     

Do the Forward Sales of Real Estate Stabilize Spot Prices?

We examine the effect of forward sale (pre-sale) activities on the volatility of spot prices in the real estate market. The abundance of pre-sales data and major changes in regulatory control on the pre-sale market during the 90's in Hong Kong allow us to undertake empirical tests using Hong Kong's real estate data. Our results show that the volatility of spot prices increased significantly after forward sales were severely dampened by regulatory control measures introduced in 1994, but decreased again when the measures were partly relaxed in 1998. The results contribute to the long lasting debate on whether the introduction of a futures market reduces the volatility of spot prices. Previous studies were mainly conducted in markets with low transaction costs, notably financial markets. By utilizing the unique regulatory changes in the pre-sale market of Hong Kong, we are able to conduct an experiment on the conditional volatility of spot prices in a high information-cost environment, thereby shedding light on the important role of forward housing contracts in providing price expectation information for spot trading.     

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.     

Information, Search, and House Prices: Revisited

Buyers pay different prices for nearly identical homes. One explanation for this is that housing markets are thin, resulting in price bargaining between sellers and buyers. If the relative bargaining power of buyers varies, so will sales prices. One hypothesis is that the relative bargaining strength of buyers coming from outside the local market relative to that of local residents is weak, because distant buyers have high search costs and may know less about the nuances of the local market. Our results, based upon a large number of single-family home transactions from the state of Florida, lend support to this hypothesis. Another related hypothesis is that buyers?? price expectations are anchored to prices they were accustomed to at their previous residence. Hence, if they come from high price markets they will tend to pay more for their new home. This hypothesis is also supported by our results.     

Residential Mortgage Default: The Roles of House Price Volatility, Euphoria and the Borrower’s Put Option

House price volatility; lender and borrower perception of price trends, loan and property features; and the borrower’s put option are integrated in a model of residential mortgage default. These dimensions of the default problem have, to our knowledge, not previously been considered altogether within the same investigation framework. We rely on a sample of individual mortgage loans for 20 counties in Florida, over the period 2001 through 2008, third quarter, with housing price performance obtained from repeat sales analysis of individual transactions. The results from the analysis strongly confirm the significance of the borrower’s put as an operative factor in default. At the same time, the results provide convincing evidence that the experience in Florida is in part driven by lenders and purchasers exhibiting euphoric behavior such that in markets with higher price appreciation there is a willingness to accept recent prior performance as an indicator of future risk. This connection illustrates a familiar moral hazard in the housing market due to the limited information about future prices.     

中国房地产市场价格泡沫与空间传染效应

本文使用对数周期性幂律(Log Period Power Law, LPPL)模型对房地产市场价格泡沫进行测度,运用空间计量模型对我国房地产市场价格泡沫和空间传染效应进行研究。LPPL模型认为由价格泡沫产生并最终破裂的金融市场与地震系统具有很多相似之处,即金融资产的价格呈周期性变化规律,价格持续上涨到临界状态直至反转。本文采用2010年6月至2017年11月间我国100个城市的房地产市场数据对各城市房地产价格泡沫进行测度和物理/经济空间传染效应研究。研究发现,LPPL模型能够对我国100个城市房地产价格泡沫进行甄别且主要存在两种泡沫状态:正向泡沫(房价持续上升)和反转泡沫(房价整体下降却存在反转点)。各个城市(地区)房地产价格具有较强的空间传染性;存在正向泡沫区域的空间传染性相较反转泡沫区域更为明显,在考虑经济空间测度而不是物理空间测度的情况下,各城市间的空间传染性更强。与现有文献不同,我们发现反转泡沫区域的新房价格指数特别是二手房价格指数的上升对周边城市的房地产价格指数存在强烈的正向推高影响。最后,本文发现城市的房地产调控政策在一定程度上抑制了房价传统影响(比如信贷、新房、二手房价等)因素的推高影响,但各城市房地产价格之间的联动变化特征应该引起监管部门的注意。     

Asymmetry in Stock Returns Following Block Trades on the Australian Stock Exchange: A Note

A number of recent US. studies have examined the price impact of large (block) trades using intraday data. A major finding is that the price movement following block trades continues upwards following purchases but reverses following sales. This asymmetry in price behaviour, which suggests that block sellers pay a liquidity premium while block buyers do not, has been described as 'intriguing' and a 'key puzzle'. The purpose of this note is to determine whether the phenomenon exists on the Australian Stock Exchange. Evidence consistent with the 'puzzling' asymmetry is shown to exist when returns are measured from the block trade until the close of trade. Contrary to US. findings, which have shown that prices appear to reverse following both block purchases and sales in transaction time analysis, the asymmetry in price behaviour is also demonstrated to exist in transaction returns for the ASX. All results are found to be robust to a number of research design innovations and data partitions.     

Mean Reversion and Momentum: Another Look at the Price-Volume Correlation in the Real Estate Market

Based on behavioral finance and economics literature, we construct a theoretical framework in which consumers of newly constructed housing units perceive prices to follow a stochastic mean reversion pattern. Given this belief and the high carrying cost maintained by real estate developers, potential buyers opt to either exercise immediately or defer the purchase. We simulate the model within a real option framework by which we show that the optimal time to wait before exercising a purchase is positively related to the price level; hence, a negative (positive) correlation between transaction volume and price level (yield) emerges. Observing data on housing prices and new construction sales in Israel for the years 1998–2007, we apply an adaptive expectation regression model to test consumers’ belief in both mean reversion and momentum price patterns. The empirical evidence shows that while consumers’ demand pattern is simultaneously consistent with the belief in both momentum and mean reversion processes, the effect of the latter generally dominates. Moreover, while the data does not allow for testing the volume and price-level correlation, it does provide support to the positive volume-price yield correlation.     

Understanding Housing Market Volatility

The Campbell–Shiller present value formula implies a factor structure for the price–rent ratio of housing market. Using a dynamic factor model, we decompose the price–rent ratios of 23 major housing markets into a national factor and independent local factors, and we link these factors to the economic fundamentals of the housing markets. We find that a large fraction of housing market volatility is local and that the national factor has become more important than local factors in driving housing market volatility since 1999, consistent with the findings in Del Negro and Otrok (2007). The local volatilities mostly are due to time variations of idiosyncratic housing market risk premia, not local growth. At the aggregate level, the growth and interest rate factors jointly account for less than half of the total variation in the price–rent ratio. The rest is due to the aggregate housing market risk premium and a pricing error. We find evidence that the pricing error is related to money illusion, especially at the onset of the recent housing market bubble. The rapid rise in housing prices prior to the 2008 financial crisis was accompanied by both a large increase in the pricing error and a large decrease in the housing market risk premium.     

Ownership Duration in the Residential Housing Market: The Influence of Structure,Tenure, Household and Neighborhood Factors

Turnover rates are important as determinants of the level of activity in housing related industries, in effecting housing market adjustments, and in revealing prices in illiquid, highly segmented, informationally inefficient housing markets. This study examines the relative influence of structure features, tenure, household characteristics and neighborhood factors on ownership turnover rates. The study exploits a Chicago database of just under 50,000 paired sales of attached housing units, with at least one of the sales occurring between 1992 and June of 2002. Within the framework of a Cox proportional hazard model, we focus on a number of factors affecting turnover rates, including whether the housing unit is owner-occupied or rented at the time of sale, price at the time of sale, unit size, age, location in a tax increment financing district, housing density, structure size, year of sale, and neighborhood within Chicago (by Community Area). Finding strong spatial segmentation in turnover (hazard) rates, we further examine the capacity of four sets of Census-derived variables to explain the spatial variation. The household characteristics offer decidedly the strongest power in explaining the segmentation. Results from the hazard model, combined with results from the analysis of spatial variation suggest a household life cycle model of variation in turnover rates.     

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.     

人口年龄结构与住宅价格调控

在人12老龄化背景下．当人12总量和年龄结构发生质的变化时,将对住宅价格产生深远影响。本文在人口学研究基础上。有效结合住宅销售价格指数．通过逐步回归的方法获得购房适龄人口数量与住宅价格的关系模型,同时创新性地纳入莱宾斯坦人口发展五阶段理论,通过Logarithmic曲线模型进行量化分析。结论显示,在假定条件下．随着未来适龄购房人口的减少,国内住房价格将在2018年出现拐点并逐步回落,并在2030年前后降至2000年水平（剔除通胀因素）,之后将处于长期低迷状态。因此当前在遏制住房价格过快上涨的同时,应从更长远的视角构建调控思路。     

Housing prices and the optimal time-on-the-market decision

This paper provides a model for housing prices based on a seller solving the optimal time-on-the market problem. Given the seller’s optimal time-on-the market, analytical expressions are provided for both the expected time-on-the-market and the sales price. These expressions facilitate the computation of comparative statics. Consistent with economic intuition, we show that (i) both the expected time-on-the market and sales price decrease as interest rates increase, (ii) the expected time-on-the market increases and the expected sales price decreases as offer activity declines, and (iii) the expected time-on-the market and expected sales price both increase as the list price increases.