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.     

Trading Frictions and House Price Dynamics

We model liquidity in housing markets. The model provides a simple characterization for the joint process of prices, sales, and inventory. We compare the implications of the model to certain properties of housing markets. The model can generate the large price changes and the positive correlation between prices and sales that we see in the data. Unlike the data, prices are negatively autocorrelated and high inventory predicts price appreciation. We investigate several amendments to the model. Informational frictions show promise.     

Pricing the US residential asset through the rent flow: A cross-sectional study

The paper explores how the standard consumption-CAPM fares in pricing housing returns and regional rental income streams in a cross-section of regions. In particular, we estimate the Euler equations associated with the gross housing returns inclusive of price appreciations and rents jointly for several metropolitan areas of the US. The representative agent has a Constant Relative Risk Aversion (CRRA) utility. The rent growth is allowed to depend on the business cycle. When biannual data from 1978 to 2007 is used, the parameter estimates are reasonable, and the model is not rejected. Large standard errors indicate uninformative estimates. The implied price rent ratio time series averages are similar to the data; however the model misses the boom-bust pattern in the prices. The model significantly understates the average and the variance of the price appreciations. Results are robust to allowing housing consumption directly in the utility function or using the Epstein–Zin–Weil utility.     

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.     

Distortions Resulting from Residential Land Use Controls in Metropolitan Areas

Residential land use controls in metropolitan areas are intended to and typically do restrict housing supply and inevitably raise housing prices. This paper estimates the effects of metropolitan area land use controls on housing prices, employing a remarkable data set compiled by Gyourko, Saiz and Summers. We embed the estimates in a four equation model that estimates the effects of the resulting high housing prices on metropolitan population, real incomes and employment.     

The Impact of Property Condition Disclosure Laws on Housing Prices: Evidence from an Event Study Using Propensity Scores

We examine the impact of seller??s Property Condition Disclosure Laws on residential real estate values. A disclosure law may address the information asymmetry in housing transactions shifting risk from buyers and brokers to the sellers and raising housing prices as a result. We combine propensity score techniques from the treatment effects literature with a traditional event study approach. We assemble a unique set of economic and institutional attributes for a quarterly panel of 291 US Metropolitan Statistical Areas (MSAs) across 50 US States spanning 21?years from 1984 to 2004. The study finds that the average sales price of houses in a metropolitan area increases by an additional 3 to 4% over a 4?year period if the state adopts a Property Condition Disclosure Law, which is consistent with approximately a 19 basis point or 6.4% reduction in the risk premium associated with purchasing owner-occupied housing. When we compare the results from parametric and semi-parametric (propensity score) event analyses, we find that the semi-parametric analysis generates moderately larger estimated effects of the law on housing prices.     

The Benefits of Visibility Improvement: New Evidence from the Los Angeles Metropolitan Area

This article examines the impact of a specific aspect of air quality—visibility, or the ability to clearly see distant objects—on housing values. Our analysis is based on a data set constructed by matching residential housing sales data from the Los Angeles Metropolitan Area for the period 1980 through 1995 with visibility and other air pollution data and other characteristics. We find that visibility differences are capitalized into housing values, producing a measurable hedonic price gradient. The time-series design facilitates an estimate of the demand for visibility that we use to calculate the benefits of changes in visual range.     

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.     

A Pricing Model for Residential Homes with Poisson Arrivals and a Sales Deadline

We introduce a pricing model for single-family residences on the real estate market. The model considers purchase offers that arrive according to a Poisson process. The homeowner’s problem is to set a price that will maximize his net profit. The selling agent suggests a price to the homeowner that will maximize her net profit, which consists of her sales commission minus her costs. Our model accounts for a deadline to sell the home, a common feature of the housing market, beyond which fixed and variable penalty costs accrue to both the homeowner and selling agent. We demonstrate the behavior of the model and show under what conditions the owner’s and agent’s incentives are aligned. Our computational results suggest, in most circumstances, that agents should not pressure owners to substantially lower their asking prices in the presence of a deadline.     

Nonlinear Spatial and Temporal Effects of Highway Construction on House Prices

This paper studies the effect of a newly completed highway extension on home prices in the surrounding area. We analyze non-linearities in both the effect of distance from the highway and the effect of time relative to the completion of the road segment. While previous studies of the effects of nearby amenities on property and land values have focused on either cross-sectional spatial or temporal patterns, the joint analysis of the two dimensions has not been thoroughly investigated. We use home sale data from a period of 11 years centered around the completion of a new highway extension in metropolitan Los Angeles. We combine a standard hedonic model with a spline regression technique to allow for non-linear variations of the effect along the temporal and spatial dimensions. Our empirical results show that the maximum home price appreciation caused by the new highway extension occurs at moderate distances from the highway after it is completed. Lower price increases for this period are observed for homes sold closer to the highway or much further away. This price pattern gradually fades away in the years following the construction completion. A similar, although weaker, price pattern is also observed in the first years of the construction period. There is no statistically significant distance dependency in the 2 years in our sample prior to the beginning of the construction. This indicates that the housing market is not fully efficient as the information about the impending construction of the highway is not immediately incorporated into sales prices.     

Predicting House Prices Using Multiple Listings Data

It is often necessary to accurately predict the price of a house between sales. One method of predicting house values is to use data on the characteristics of the area's housing stock to estimate a hedonic regression, using ordinary least squares (OLS) as the statistical technique. The coefficients of this regression are then used to produce the predicted house prices. However, this procedure ignores a potentially large source of information regarding house prices—the correlations existing between the prices of neighboring houses. The purpose of this article is to show how these correlations can be incorporated when estimating regression coefficients and when predicting house prices. The practical difficulties inherent in using a technique called kriging to predict house prices are discussed. The article concludes with an example of the procedure using multiple listings data from Baltimore.     

Hong Kong housing markets: Overview,tenure choice,and housing demand

This paper presents an overview of housing markets and a cross-sectional analysis of housing demand in Hong Kong. Disturbances from political events have produced price upheavals in property prices; long-term inflation and low interest rates provide a strong stimulus for a sustained price surge in the housing market. Household income seems to have relatively little bearing on recent development in the market, especially when demand for housing has become more investment-oriented.With the data from the 1991 Population Census of Hong Kong, we find in the cross-section study that permanent and transitory incomes, rather than current income, provide better estimates in the tenure choice equation. The results also indicate that family size and the number of elderly persons affects ownership. Renter expenditure and tenure choice decisions are linked by using the two-stage estimation procedure of Lee and Trost (1978). No correlation was found between renter expenditure and tenure choice. Further, the two-stage approach does not seem to be superior to the OLS approach in the estimation of the rental expenditure equations.     

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.     

Speculation and price bubbles in the Korean and Japanese real estate markets

This article investigates the possibility of speculation having caused the prices of land and housing to deviate from their given long-run equilibrium levels in Korea and Japan. We modeled speculation by incorporating the expected future price into the demand equation. The existence of growing rational bubbles was tested on Korean and Japanese data using the standard econometric technique for estimating linear rational expectations models. Our analysis of the Korean annual data suggests that a growing rationale bubble existed during the 1974–1989 period, nominal or real. Estimation results of the same model using Japanese annual data also confirmed the existence of a bubble in land price. Contrary to our analysis of land price data, the evidence of the bubble was much less obvious in Korean annual housing price data. We therefore estimated the model using quarterly data and found that the existence of a bubble could not be established in housing prices. This finding was also consistent with the trend of the rent-to-value ratio series in apartment units. Our results need to be taken with caution because our approach suffers from the common econometric problem of possible mis-specification of the model and because of the small size of the sample.     

The Hierarchical Trend Model for Property Valuation and Local Price Indices

This paper presents a hierarchical trend model (HTM) for selling prices of houses, addressing three main problems: the spatial and temporal dependence of selling prices and the dependency of price index changes on housing quality. In this model the general price trend, cluster-level price trends, and specific characteristics play a role. Every cluster, a combination of district and house type, has its own price development. The HTM is used for property valuation and for determining local price indices. Two applications are provided, one for the Breda region, and one for the Amsterdam region, lying respectively south and north in The Netherlands. For houses in these regions the accuracy of the valuation results are presented together with the price index results. Price indices based on the HTM are compared to a standard hedonic index and an index based on weighted median selling prices published by national brokerage organization. It is shown that, especially for small housing market segments the HTM produces price indices which are more accurate, detailed, and up-to-date.     

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.     

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.     

Housing Price Dynamics in Time and Space: Predictability,Liquidity and Investor Returns

It is widely accepted that aggregate housing prices are predictable, but that excess returns to investors are precluded by the transactions costs of buying and selling property. We examine this issue using a unique data set—all private condominium transactions in Singapore during an eleven-year period. We model directly the price discovery process for individual dwellings. Our empirical results clearly reject a random walk in prices, supporting mean reversion in housing prices and diffusion of innovations over space. We find that, when house prices and aggregate returns are computed from models that erroneously assume a random walk and spatial independence, they are strongly autocorrelated. However, when they are calculated from the appropriate model, predictability in prices and in investment returns is completely absent. We show that this is due to the illiquid nature of housing transactions. We also conduct extensive simulations, over different time horizons and with different investment rules, testing whether better information on housing price dynamics leads to superior investment performance.     

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.     

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。