Estimating house price appreciation: A comparison of methods

Several parametric and nonparametric methods have been advanced over the years for estimating house price appreciation. This paper compares five of these methods in terms of predictive accuracy, using data from Montgomery County, Pennsylvania. The methods are evaluated on the basis of the mean squared prediction error and the mean absolute prediction error. A statistic developed by Diebold and Mariano is used to determine whether differences in prediction errors are statistically significant. We use the same statistic to determine the effect of sample size on the accuracy of the predictions. In general, parametric methods of estimation produce more accurate estimates of house price appreciation than nonparametric methods. And when the mean absolute prediction error is used as the criterion of accuracy, the repeat sales method produces the most accurate estimate among the parametric methods we tested. Finally, of the five methods we tested, the accuracy of the repeat sales method is least diminished by a reduction in sample size.     

A Time Series Analysis of U.K. Lottery Sales: Long and Short Run Price Elasticities

This paper estimates the long- and short-run elasticities for Lotto. It is particularly concerned with the dynamic response to price variations since, for some goods, this has sometimes been used to infer the presence of addiction. The price elasticity is identified through variation in the expected value of a Lotto ticket induced by rollovers whose high frequency results in surprisingly high variation in the expected value of holding a ticket. Unit root tests are applied to the series in order to identify their time series properties and to avoid a spurious regression problem. The series are found to be stationary. We apply instrumental variables to account for the endogeneity which arises due to correlation between the expected value and the dependent sales variable. The estimated long-run elasticity exceeds the short-run elasticity and this supports the hypothesis that there is an element of addictive behaviour in sales. The Lottery is regulated and the regulator's objective is to maximize sales. Our estimated long-run price elasticity of demand is inconsistent with revenue maximization and we find that greater revenue for the 'good causes' could be raised from the game if a smaller proportion of sales revenue were allocated to them.     

Empirical evidence on the reaction speeds of housing prices and sales to demand shocks

This article studies the co-movement and dynamics between price movements and transactions in the housing market using data for the period 1988–2008 from Finland. While the previous related literature examines the reactions of sales and prices to an interest rate shock only, this study investigates the responses to income and debt shocks as well. The empirical estimations show that the response of prices to demand shocks is substantially slower than that of sales. The estimated reactions of sales substantially differ from those reported in the earlier literature. The reaction patterns can create the kind of strong positive co-movement between price movements and sales volume and the kind of negative correlation between price level and sales that have been found in several housing markets.     

Hedonic price and depreciation indexes for residential housing: A comment

A regression technique for developing residential real estate price indexes using repeat sales on properties has not allowed the separation of depreciation from true price changes. In a recent article Chinloy [2] has proposed a method for achieving this separation. This note shows that his theoretical derivation is incorrect. A corrected model is then used to show the stringent assumptions that are necessary to interpret his empirical results as measuring embodied technological change. The true price effects and the depreciation effects still cannot be separated in such a model.     

河北省房地产价格波动影响因素的实证分析

本文以河北省2004年第1季度至2009年第4季度的房地产平均销售价格及相关数据为样本,运用计量经济学的逐步回归法分析了河北省宏观经济基本层面对房地产价格的影响和作用程度。实证分析发现:人口因素、地区生产总值和货币供应量对房地产价格波动影响较大,其中货币供应量与河北省房地产的价格波动呈现正相关,对房地产价格的影响非常显著。因此,我国的货币政策要逐步关注各地区的房地产价格。     

SMOOTH QUANTILE‐BASED MODELING OF BRAND SALES,PRICE AND PROMOTIONAL EFFECTS FROM RETAIL SCANNER PANELS

Semiparametric quantile regression is employed to flexibly estimate sales response for frequently purchased consumer goods. Using retail store‐level data, we compare the performance of models with and without monotonic smoothing for fit and prediction accuracy. We find that (a) flexible models with monotonicity constraints imposed on price effects dominate both in‐sample and out‐of‐sample comparisons while being robust even at the boundaries of the price distribution when data is sparse; (b) quantile‐based confidence intervals are much more accurate compared to least‐squares‐based intervals; (c) specifications reflecting that managers may not have exact knowledge about future competitive pricing perform extremely well. Copyright © 2013 John Wiley & Sons, Ltd.     

An event time study of the price reaction to large retail trades

This paper analyzes large retail trades using an event study approach. A major finding in studies of this nature is an immediate reversal on the trade subsequent to the large transaction, for both large purchases and large sales. This reversal is inconsistent with the overwhelming majority of previous findings which show a stock price continuation following purchases to the close of trading. We confirm the reversals first using transaction prices, and then show that continuations follow both large purchases and sales when quote data is used. These large trades do not lead to a fundamental change in stock price volatility. We conclude that the transaction price reversal is driven by natural bid-ask bounce around large purchases and large sales.     

河北省房地产价格波动影响因素的实证分析

本文以河北省2004年第1季度至2009年第4季度的房地产平均销售价格及相关数据为样本,运用计量经济学的逐步回归法分析了河北省宏观经济基本层面对房地产价格的影响和作用程度。实证分析发现：人口因素、地区生产总值和货币供应量对房地产价格波动影响较大,其中货币供应量与河北省房地产的价格波动呈现正相关,对房地产价格的影响非常显著。因此,我国的货币政策要逐步关注各地区的房地产价格。     

Abnormal returns, risk, and options in large data sets

Large data sets in finance with millions of observations have become widely available. Such data sets enable the construction of reliable semi-parametric estimates of the risk associated with extreme price movements. Our approach is based on semi-parametric statistical extreme value analysis, and compares favorably with the conventional finance normal distribution based approach. It is shown that the efficiency of the estimator of the extreme returns may benefit from high frequency data. Empirical tail shapes are calculated for the German Mark—US Dollar foreign exchange rate, and we use the semi-parametric tail estimates in combination with the empirical distribution function to evaluate the returns on exotic options.     

Option value and the price of teardown properties

The introduction of uncertainty over the future price of structural capital into a model of teardowns implies a value to delaying the demolition vs. preservation decision, and that the market price of a redeveloped property may increase with its quantity of structural capital. Using data from an active teardown market, we test the model’s prediction that hedonic price function coefficients depend on the expected time between sale and demolition. As predicted, structural variables have significant effects on the sales prices of both teardown and non-teardown properties, and the effects are generally much larger the lower the estimated teardown probability.     

What is the role of the asking price for a house?

This paper considers the role of the asking price in housing transactions both theoretically and empirically. Significant fractions of housing transactions involve sales prices that are either below or above asking price, which might suggest that asking price has limited relevance. However, many housing transactions involve a sales price exactly equal to asking price (a fact that has previously drawn little notice), strongly suggesting that asking price does matter. The paper develops a model where asking price is neither a binding commitment nor a ceiling, yet still directs buyer search and impacts sales price. Using novel survey data, the paper provides empirical evidence consistent with asking price playing a directing role in buyer search. Consistent with theory, this effect is stronger for more atypical houses and in bust markets.     

List price and sales prices of residential properties during booms and busts

This paper investigates the relationship between the list and sale price of residential properties over the housing cycle. In down or normal markets the list price generally exceeds the sales price; however, when the housing market is strong, homes sell for more than their list price. This observation is not consistent with the assumptions made in the standard model of home sellers’ search behavior. We consider alternative models. In one, sellers set list prices based on their expectations of future changes in sales prices and the arrival rate of buyers; however, demand shocks occur. This model partially explains our data from the Belfast, U.K. housing market, but it fails to predict the list to sales price ratio during a sustained housing boom. We next describe a model where sellers’ endogenously select their search mechanism depending on the strength of the housing market. We find support for the conjecture that sellers switch to an auction-like model during housing booms. There also is evidence that during a downturn in the market, sellers’ list prices are sticky.     

Probabilistic forecasting of heterogeneous consumer transaction–sales time series

We present new Bayesian methodology for consumer sales forecasting. Focusing on the multi-step-ahead forecasting of daily sales of many supermarket items, we adapt dynamic count mixture models for forecasting individual customer transactions, and introduce novel dynamic binary cascade models for predicting counts of items per transaction. These transaction–sales models can incorporate time-varying trends, seasonality, price, promotion, random effects and other outlet-specific predictors for individual items. Sequential Bayesian analysis involves fast, parallel filtering on sets of decoupled items, and is adaptable across items that may exhibit widely-varying characteristics. A multi-scale approach enables information to be shared across items with related patterns over time in order to improve prediction, while maintaining the scalability to many items. A motivating case study in many-item, multi-period, multi-step-ahead supermarket sales forecasting provides examples that demonstrate an improved forecast accuracy on multiple metrics, and illustrates the benefits of full probabilistic models for forecast accuracy evaluation and comparison.     

房价影响因素的实证分析——以青岛市为例

运用SPSS软件,以人口、人均GDP、住房销售面积和房地产开发投资为自变量,采用2000～2009年10年的数据,建立了多元线性回归模型,对青岛市房价这一因变量进行了模拟分析。模型通过各种检验,得出了影响青岛市住房价格最重要的因素是市区人口这一结论,说明青岛市有效的需求增大,是抬高住房价格十分重要的因素,这在一定层面上说明了青岛的住宅市场的价格是比较正常的价格。     

Buyer brokerage: Experimental evidence

This paper offers an experimental investigation of two commission structures for buyer brokerage. One commission structure is the currently used structure in the industry where both the seller’s broker and the buyer’s broker each receive a percentage of the sales price as their compensation from the seller. In an alternative commission structure, while the seller’s broker still receives a percentage of the sales price from the seller, the buyer’s broker is compensated by the buyer and the compensation is inversely related to the sales price. We find that how the buyer’s broker gets compensated has significant implications. While both commission structures yield a similar probability of reaching an agreement, the alternative commission structure yields a lower price and a longer time to reach an agreement. Furthermore, the alternative commission structure achieves a better alignment of the interests of the buyer and the buyer’s broker without affecting the earnings of the players in the transaction. We also find that the improvement in the alignment of interests is more significant for female buyers than for male buyers. Furthermore, a higher listing price by the seller and a higher initial bid price by the buyer each lead to a significant increase in the negotiated price.     

Housing submarkets and the impacts of foreclosures on property prices

The dramatic rise in the number of foreclosed properties since 2006 has come to assume the proportions of a national crisis. It is widely acknowledged that foreclosures hurt neighborhoods by devaluing the nearby properties through various channels. This paper offers a new way of conceptualizing and then estimating the potential effects of foreclosures on property values. Housing stock heterogeneity in the central city old neighborhood allows for the possibility that the impacts of nearby foreclosures may differ across types of housing. This study uses a dataset that covers twenty years of housing values from the City of Worcester (MA), and finds evidence that foreclosures of multi-family houses in close proximity influence the sales price of surrounding single-family properties after controlling for impact from foreclosure of nearby single-family houses. The most preferred estimate suggests that each multi-family foreclosure that occurs between 660 and 1320 feet away from the sale lowers the predicted sales price by approximately 3%. Nearby multi-family spillover impacts also persist over time. In addition, a new approach advocating for an alternative definition of housing submarket suggests that a distant foreclosure within the same submarket also lower sales price of a single-family home by 0.1%.     

The role of the list price in housing markets: Theory and an econometric model

Houses are routinely sold at prices below, but rarely sold at prices above, their list prices. List prices appear to be price ceilings that preclude the possibility of sales at higher prices. This paper presents a theory of sellers' behaviour that explains why there are list prices in housing markets and why list prices are distinct from sellers' reservation prices. The theory forms the basis of an econometric model that has been estimated using data from the Baltimore, MD, area. The estimated model predicts sale and reservation prices conditional on list prices. The predictions of sale prices are considerably more accurate than those obtained from a standard hedonic price regression. The estimated model also explains why sellers may not be willing to reduce their list prices even after their houses have remained unsold for long periods of time.     

Sales by multi‐product retailers

This paper examines the rationale underlying periodic price promotions, or sales, for perishable food products by supermarket retailers. Whereas previous studies explain sales in a single‐product context as arising from informational, storage cost, or demand heterogeneity, this study focuses on the central role of retailers as multi‐product sellers of complementary goods. By offering a larger number of discounted products within a particular category, retailers are able to attract a sufficient number of customers to offset the effect of lower margins on sale items by selling more high‐margin items. The implications that emerge from the resulting mixed‐strategy equilibrium are tested in a product‐level, retail‐scanner data set of fresh fruit sales. Hypotheses regarding the rationale and effectiveness of sales are tested by estimating econometric models that describe (1) the number of sales items per store, (2) the depth of a given sale, and (3) promotion effectiveness on store‐level demand. The results of this econometric analysis support the hypothesis that the breadth and depth of price promotions are complementary marketing tools, thus explaining how EDLP and HI‐LO store formats can exist in the same monopolistically competitive market equilibrium. Copyright © 2006 John Wiley & Sons, Ltd.     

Alternative value estimates of owner-occupied housing: Evidence on sample selection bias and systematic errors

Numerous econometric models have used various estimates of housing value as dependent variables. The three most common measures, in order of descending popularity, have been homeowner estimates, sales price, and assessed value. Each of these measures has limitations. The use of sales price can cause sample selection bias, while owner and tax assessor estimates are subject to measurement error. This study investigates the magnitude of the selection bias associated with sales price samples, and whether the errors in owner and assessor estimates are systematically related to independent variables typically included in estimated equations. Our most important conclusion is that the use of owner estimates may cause bias in the estimated coefficients on many independent variables.     

城市住房价格指数编制方法的拓展设计及实证检验

科学监测城市房价走势,在当前环境下尤为重要。为拓展国际通行方法编制国内单一城市房价指数的适用性,引入样本匹配重复交易法构建房价指数,以提高样本容量与可比性。基于上海数据的实证结果表明,相较于传统重复交易法和特征价格法,样本匹配重复交易法能更准确地反映住房价格变动,结果异常波动性更小,噪声影响程度更低,在克服样本代表性误差和变量缺失误差方面效果更显著,对编制国内城市房价指数具有较好应用价值。