House price depreciation rates and level of maintenance

My objective in this paper is to estimate different depreciation rates of house prices depending on the level of maintenance of the property and the location of the property. I do this by supplementing transaction price data with owner information about level of maintenance. The result indicates that the level of maintenance has a substantial impact on the price level. Since maintenance offsets some of the physical deterioration of the property, the depreciation rate will be lowered by maintenance, ceteris paribus. To be able to estimate maintenance effects on depreciation rates, I isolated the interaction effect between the level of maintenance and the age of the property to allow for the fact that maintenance has an impact on the effective age of the property. In this study, I separate maintenance into indoor and outdoor maintenance levels (or absence of maintenance).My results show that the depreciation rates are significantly different for a maintained property and for a property that is not maintained. The price difference between a 40-year-old property (built in 1960) and maintained both indoors and outdoors and a property of the same age that is not maintained is about 13% (−10% compared to −23% in total age effect). The absence of outdoor maintenance has more impact on price depreciation rates.     

Changes in the distribution of house prices over time: Structural characteristics,neighborhood, or coefficients?

Quantile hedonic house price function estimates imply that appreciation rates were higher between 1995 and 2005 for high-priced homes in Chicago. Decompositions of temporal changes in the house price distribution suggest that the types of homes sold and their location do not account for the change in the price distribution. Rather, higher appreciation rates for high-priced homes are explained by differences in the quantile regression coefficients over time.     

Changes in the distribution of house prices over time: Structural characteristics,neighborhood, or coefficients?

Quantile hedonic house price function estimates imply that appreciation rates were higher between 1995 and 2005 for high-priced homes in Chicago. Decompositions of temporal changes in the house price distribution suggest that the types of homes sold and their location do not account for the change in the price distribution. Rather, higher appreciation rates for high-priced homes are explained by differences in the quantile regression coefficients over time.     

HEDONIC PRICE INDEXES FOR RESIDENTIAL HOUSING: A SURVEY,EVALUATION AND TAXONOMY

Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. I consider here some developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason I attempt to impose some structure on the literature by developing a taxonomy of hedonic indexes, and then show how existing indexes fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field. In particular, greater use needs to be made of spatial econometric and nonparametric methods to exploit the increased availability of geospatial data. The main criticisms of the hedonic approach are evaluated and compared with those of the repeat‐sales and stratified median methods. The overall conclusion is that the advantages of the hedonic approach outweigh its disadvantages.     

Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle

Standard housing price indexes rely on strong constant-quality assumptions and often conflict. Hedonic price indexes overcome limitations of median price and repeat-sales indexes but their implementation has been limited by a lack of data. This paper constructs hedonic indexes at the zip code level for the Los Angeles and San Diego metropolitan areas using considerably more detailed data than previously available. Our sample was collected by a mortgage technology firm, and consists of almost 1.1 million transactions during the boom-bust cycle since 2000. Our hedonic regressions include new spatial models that capture correlations within submarkets (using zip codes as proxies) and allow temporal asymmetry. Compared to a repeat-sales price index constructed from the same data, the hedonic indexes indicate that the market peaked about 11 months later in Los Angeles and about 2 months earlier in San Diego, show less pre-peak appreciation and post-peak depreciation in low-tier housing and more pre-peak appreciation in high-tier housing. We also find that the intensity of the cycle varies greatly across zip codes and price-tiers in a pattern consistent with foreclosure activity.     

On nonparametric estimation of a hedonic price function

Recently, using mixed data on Canadian housing, Parmeter, Henderson, and Kumbhakar (Journal of Applied Econometrics 2007; 22 : 695–699) found that a nonparametric approach for estimating a hedonic house price function is superior to formerly suggested parametric and semiparametric specifications. We carefully reanalyze these specifications for this dataset by applying a recent nonparametric specification test and simulation‐based prediction comparisons. For the case at issue our results suggest that a previously proposed parametric specification does not have to be rejected and we illustrate how nonparametric methods provide valuable insights during all modeling steps. Copyright © 2010 John Wiley & Sons, Ltd.     

House Price Dynamics in Mumbai, 1989–1995

The objective of this paper is to study the importance of price index methodology to analyzing intra-metropolitan house price variations in Mumbai. Two hedonic regression-based approaches – cross section and explicit time variable – are compared. The results indicate conclusively that the former is better than the latter. This paper also contributes to the literature on intra-metropolitan house price variations by explaining them based on urban development, population and employment patterns in Mumbai.     

Semiparametric hedonic price models: assessing the effects of agricultural nonpoint source pollution

In the area of environmental analysis using hedonic price models, we investigate the performance of various nonparametric and semiparametric specifications. The proposed model specifications are made up of two parts: a linear component for house characteristics and a non‐(semi)parametric component representing the nonlinear influence of environmental indicators on house prices. We adopt a general‐to‐specific search procedure, based on recent specification tests comparing the proposed specifications with a fully nonparametric benchmark model, to select the best model specification. An application of these semiparametric models to rural districts indicates that pollution resulting from intensive livestock farming has a significant nonlinear impact on house prices. Copyright © 2008 John Wiley & Sons, Ltd.     

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。     

COMMERCIAL PROPERTY PRICE INDEXES AND THE SYSTEM OF NATIONAL ACCOUNTS

This paper studies the problems associated with the construction of price indexes for commercial properties that could be used in the System of National Accounts (SNA). Property price indexes are required for the stocks of commercial properties in the Balance Sheets of the country. Related service price indexes for the land and structure input components of a commercial property are required in the Production Accounts of the country if the Multifactor Productivity of the Commercial Property Industry is calculated as part of the SNA. The paper reviews existing methods for constructing an overall Commercial Property Price Index (CPPI) and concludes that most methods are biased (due to their neglect of depreciation) and more importantly, not able to provide separate land and structure subindexes. A class of hedonic regression models that is not subject to these problems is discussed.     

Hedonic price and depreciation indexes for residential housing: A longitudinal approach

An equilibrium price relation is derived for price changes in durable goods capable of generating a hedonic, or quality-corrected, price index, and an index of depreciation. The structure proposed is applicable particularly to housing markets, where longitudinal, or repeat-sale data are readily available from assessment or real estate sources. The separation permits not only the construction of a true price index, but also allows tests of various functional forms for depreciation, notably the geometric function. As an application of the proposed structure, estimates are presented for single-family dwellings in surburban London, Ontario, 1967–1975.     

A mixed index approach to identifying hedonic price models

Recent literature suggests identifying house price hedonic regressions by using instrumental variables, spatial statistics, the borders approach, panel data, and other techniques. We present an empirical application of a mixed index model, first proposed by Bowden [Bowden, R.J., 1992. Competitive selection and market data: the mixed-index problem. The Review of Economic Studies 59(3):625–633.] to identify hedonic price regressions. We compare the performance of the mixed index model to a traditional hedonic model and to a hedonic model that includes characteristics of the buyer of each house. We find the mixed index model outperforms the other models based on bootstrap distributions of predicted housing values, prediction variance, and predicted policy effects. The mixed index model distributions are less skewed and kurtotic than the other models, suggesting it more closely satisfies the classical linear regression assumption of normally distributed errors. Compared to the mixed index model, the traditional hedonic overstates the importance of lot size and school quality to house price and understates the importance of environmental quality.     

Residential Hedonic Models: A Rational Expectations Approach to Age Effects

This paper develops a rational expectations framework for interpreting the coefficient on age in a standard hedonic model. The model demonstrates that there are two components to the age coefficient: a pure cross-sectional depreciation component and a demand-side component that changes over time. We also show that a constant quality price index with age constant can be estimated by using any repeat sales database that contains the year of construction (or property age). When Fairfax County data are fitted to the model, the time series of age coefficients is non-stationary: they change from negative in the early 1980s to positive in the late 1980s; we infer that the demand-side component dominated in the latter period.     

Measuring environmental effects on property values without hedonic regressions

The effect of environmental nuisances on property values has been frequently studied using hedonic regressions, yet that method has extensive data and estimation requirements. The technique developed in this paper uses repeat sales on houses to substantially reduce these requirements. The technique adjusts for depreciation between sales and allows for nonzero error covariance terms when a house has been sold more than twice. The effect of highway noise on property values is studied using this method, and the results are statistically equivalent to the results of an extensive hedonic study for the same area.     

The effect of land use regulation on housing and land prices

This paper investigates the effects of land use regulation restrictiveness on house and vacant land prices. In contrast to prior studies, the index of restrictiveness is treated as an endogenous variable and estimated effects are allowed to vary by market setting. Using data on more than 100 Florida cities, greater regulation restrictiveness is found to increase house price and decrease land price. Evidence is also provided showing that more restrictiveness increases the size of newly constructed homes.     

房价和地价相互关系的实证分析——基于上海等地数据的检验

房价与地价之间的关系问题一直是争议较大的热点,理论界有两种截然不同的观点：一种是成本论,从供给角度来看,地价决定房价;一种是需求论,从需求角度来看,地价上涨是由于房屋需求增加。本文基于长三角地区较有代表的四座城市数据对此问题进行分析。     

Convenient links for the estimation of hedonic price indexes: the case of unique,infrequently traded assets

Hedonic methods are a prominent approach in the construction of quality‐adjusted price indexes. This paper shows that the process of computing such indexes is substantially simplified if arithmetic (geometric) price indexes are computed based on exponential (log‐linear) hedonic functions estimated by the Poisson pseudo‐maximum likelihood (ordinary least squares) method. A Monte Carlo simulation study based on housing data illustrates the convenience of the links identified and the very attractive properties of the Poisson estimator in the hedonic framework.     

The housing bubble and a new approach to accounting for housing in a CPI

Over the course of the recent house price bubble in the United States, the price of homes rose rapidly from 1999 Q4 to 2005 Q4 (11.3% annually as measured by the Case-Shiller index, and 8.4% annually as measured by the Federal Housing Financing Agency) but slowly as measured by owner equivalent rents (3.4%), so measured core inflation remained relatively docile during this period, since only rents are used to measure inflation for housing services in the United States. Over the last several decades, the US Bureau of Labor Statistics (BLS) has experimented with both rental equivalence and user cost approaches for accounting for owner occupied housing (OOH) services in the CPI. We explain the basics of these approaches, and outline the BLS experiences with using them. This assessment leads us to conclude that the time has come to try a new approach: the opportunity cost approach. We argue this approach has advantages over both the conventional rental equivalence and user cost approaches, though it embeds components of the measures for both those approaches and builds solidly on the research of Verbrugge and others at the BLS. Also, we take up empirical issues that must be faced regardless of which of the approaches discussed is adopted. We explain how the repeat-sales and various hedonic regression methods can be placed in a common framework, thereby facilitating understanding of the properties of and the tradeoffs between the methods. We also consider measurement complications that arise because the land and structure components of properties depreciate at different rates.     

Hedonic markets and sorting equilibria: Bid-function envelopes for public services and neighborhood amenities

Hedonic regressions with house value as the dependent variable are widely used to study public services and neighborhood amenities. This paper builds on the theory of household bidding and sorting across communities to derive bid-function envelopes, which provide a form for these regressions. This approach allows for household heterogeneity and multiple amenities, yields estimates of the price elasticity of amenity demand directly from the hedonic without a Rosen two-step procedure, and provides tests of hypotheses about sorting. An application to Cleveland area data from 2000 yields price elasticities for school quality and neighborhood ethnic composition and supports the sorting hypotheses.     

Measuring a boom and bust: The Sydney housing market 2001–2006

The Sydney housing market peaked in 2003. The period 2001–2006 is, therefore, of particular interest since it captures a boom and bust in the housing market. We compute hedonic, repeat-sales and median price indexes for five regions in Sydney over this period. While the three approaches are in broad agreement regarding the timing of the turning point in the housing market, some important differences also emerge. In particular, we find evidence of sample selection bias in our hedonic and repeat-sales data sets (with the former focusing more on better quality dwellings and the latter more on lower quality dwellings). These sample selection biases could in turn cause bias (in opposite directions) in our hedonic and repeat-sales indexes. Median indexes may likewise be biased as a result of an apparent decline in the average quality of dwellings sold in the latter part of the sample. We also find evidence of convergence in prices across regions during the boom and divergence in the subsequent bust.