Depreciation, Maintenance, and Housing Prices

This paper investigates the effect of homeowner maintenance and improvements on the depreciation rate for housing and on house price indexes. We examine three specifications of a hedonic house price model: one that includes a variable for age, as a proxy for depreciation, and an age–maintenance interaction variable; one that considers depreciation but ignores maintenance; and one that ignores both depreciation and maintenance. The remarks of the listing agent as to the property's condition is our proxy for the level of maintenance characterizing the home. In our sample, we find that poorly maintained homes depreciate at a much faster rate than do homes with average maintenance, and that well-maintained homes depreciate somewhat more slowly. Omitting maintenance from the variable specification has little impact on hedonic house price indexes constructed with our data, but failing to consider dwelling age imparts a significant and growing downward bias to the indexes. Monte Carlo simulations investigating various data specifications support our empirical findings.     

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.     

Why elementary price index number formulas differ: Evidence on price dispersion

Most countries use either the Dutot or Jevons index number formula for the compilation of their consumer price index at the elementary level of aggregation. The difference between the formulas is shown to be accounted for by changes in price dispersion. In turn, some of this difference is shown to be explained by product heterogeneity. Scanner data on television sets (TVs) are used to calculate Dutot and Jevons indexes. The difference between them is successfully explained in terms of changes in price dispersion and much reduced using an hedonic, heterogeneity-controlled Dutot index.     

TESTS OF THE STANDARD URBAN MODEL: A Micro (Trade-Off) Alternative

Three methods of testing the validity of the monocentric model (the negative house price gradient, the wasteful commuting approach, and the hypothesis of a trade-off between housing expenditures and commuting costs) are evaluated. The negative house price gradient is not supported by several recent hedonic models. "Wasteful" commuting is a poor test because it persists even a policentric world and may be more the result of the weakness of journey-to-work minimization as a key determinant of residence and/or workplace location. This study uses the commuting information presented in the 1985 American Housing Survey in eight large metropolitan areas to show that the trade-off hypothesis fails badly. Heterogeneous Preference for housing, commuting and indeed for all goods and services, combined with a wide variety of workplaces and choice of residential locations at highly, variable rents and house prices may be the major reason why the trade-off is not generally observed.     

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.     

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.     

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.     

The house price determination process: Rational expectations with a spatial context

Applying the rational expectations hypothesis, this essay models the current value of a house as the conditional expectation of the discounted stream of housing services accruing to the owner of the house. The value of housing services is determined by neighborhood effects as well as the physical attributes of the property itself. In the existing hedonic literature, future transactions have not been utilized to describe neighborhood effects. The rational expectations asset pricing model in this study accounts for expected future neighborhood effects as well as observed current neighborhood effects. The reduced form of the rational expectations model is a spatial autoregressive (SAR) model with two spatial lags. After employing the generalized method of moments (GMM) in estimating the spatial asset pricing model, I find that both expected future transactions and prior transactions in the neighborhood are significant. The inclusion of expected future transaction prices in the neighborhood takes into account the influence of expected changes in the community and factors these potential changes into the current house price. This is consistent with forward-looking households. The forward-looking model generates superior out-of-sample prediction performance relative to both the conventional hedonic model without considering neighborhood effects or the standard spatial hedonic model including only past transactions.     

The Auction Price of Apartments in Moscow: Hedonic Estimation in Disequilibrium1

The purpose of this paper is to see how economic factors determine prices in the previously communist countries undergoing privatization. This does not concern the auctions of big state enterprises where the prices are found to be rigged. In this paper we estimate hedonic price functions based on a unique data set on auction prices of apartments in Moscow. We collected the data ourselves by attending the auctions and gathered data on the characteristics. We estimated the hedonic equations using a disequilibrium approach because no equilibrium prices were observed for large number of apartments that were withdrawn from the auction. We found that, as the privatization of residential housing was carried out, the hedonic price equations fit the data remarkably well.     

Managing hedonic housing price indexes: The French experience

Despite their theoretical advantages, hedonic housing price indexes are not so commonly computed by statistical agencies or real estate professionals. Many published indexes still rely on mean or median prices, or favor repeat-sales methods, which require less information about the attributes of the housing units and less econometric expertise on the part of the index compilers, but may be less accurate and robust. In France as in other countries where housing sales have to be recorded in front of a notary, data on transaction prices and characteristics of dwellings are available. Such data have been centralized since 1994, and quarterly hedonic housing price indexes have been computed for more than 10 years. This paper describes the institutional setting of housing transactions in France, and the collaboration between the notaries and the national statistical agency (INSEE). The former are responsible for data collection and regular computation, whereas the latter takes scientific responsibility for the method. The detailed information on the individual properties transacted remains proprietary data, but disaggregated indexes are publicly and freely available. This organization and assignment of roles has proven effective and might be extended to countries with similar institutional settings.     

A house price index based on the SPAR method

Within the European Union there has been a push to provide European governments and the European Central Bank with the statistics they need for monitoring the owner-occupied sector. This paper reports on the results of a project to develop a house price index for the Netherlands. From January 2008, Kadaster, the Dutch land registry office, and Statistics Netherlands began jointly publishing house price index numbers for the whole country and for some specific dwelling types and regions. A number of special institutional features of the situation in the Netherlands contributed to the choice of index construction method. The indexes are computed using the Sale Price Appraisal Ratio (SPAR) method, which utilizes the ratios of transaction prices and previous appraisal values. We describe the SPAR method, compare it with repeat sales methods and assess the reliability of the official Dutch appraisal values. Empirical results for January 1995–March 2009 are presented. The SPAR method performs well compared to repeat sales, and the results reported will be of interest to other countries that have, or could instigate, institutional arrangements similar to those in the Netherlands.     

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.     

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.     

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.     

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.     

A two-step approach to account for unobserved spatial heterogeneity

A two-step approach to account for unobserved spatial heterogeneity. Spatial Economic Analysis. Empirical analysis in economics often faces the difficulty that the data are correlated and heterogeneous in some unknown form. Spatial econometric models have been widely used to account for dependence structures, but the problem of directly dealing with unobserved spatial heterogeneity has been largely unexplored. The problem can be serious particularly if we have no prior information justified by economic theory. In this paper we propose a two-step procedure to identify endogenously spatial regimes in the first step and to account for spatial dependence in the second step. This procedure is applied to hedonic house price analysis.     

School Quality and Real House Prices: Inter- and Intrametropolitan Effects

This study focuses on explaining variations in real constant-quality house prices in jurisdictions located in multiple MSAs. Using a hedonic house price framework, we test competing theories of house price determination. Using two variants of the random coefficients model, we find that public school quality has a very large impact on real constant-quality house prices. Our results suggest that capitalization of school quality differences occurs on a per lot basis rather than per square foot of land. Also important to the explanation of variations in house prices are variables derived from urban theory, such as distance to the CBD, and from the amenity literature, such as a community's crime rate, arts, and recreational opportunities     

Reducing revisions in hedonic house price indices by the use of nowcasts

National Statistical Institutes (NSIs) must balance between timeliness and accuracy of the indicators they publish. Because some of the house sales transactions are reported several months after they occur, many countries that include Israel, publish provisional house price indices (HPIs) that are subject to large revisions as further transactions are reported. This happens because the late-reported transactions behave differently from the transactions reported on time. In this paper, we propose a novel methodology to minimize the size of the revisions, with illustrations from Israel, but the method can be applied to other countries with appropriate modifications. The proposed methodology consists of nowcasting three types of variables at a subdistrict level and adding them as input data to an extended hedonic model used for the computation of the HPI: (1) the average characteristics of the late-reported transactions such as the average number of rooms and the area size of the sold apartments; (2) the average price of the late-reported transactions; and (3) the number of late-reported transactions. The three variables are nowcasted based on models fitted to data from previous months. Evaluation of our methodology shows more than 50% reduction in the magnitude of the revisions.     

Intraurban variation in the price of housing

Theoretical models of spatial consumer behavior assume the existence of a housing price surface that increases with accessibility. It is often hypothesized that inadequate accessibility measures are responsible for the failure of most empirical studies to support this premise. A general accessibility measure consisting of a double power series in cartesian coordinates is developed and shown to represent a general formulation of traditional accessibility measures. This formulation is incorporated in a hedonic price regression model, and the model is estimated using census tract data for the city of Milwaukee. The hedonic prices are then used to construct intraurban housing price indexes. The results of this study provide strong support for the existence of the presumed price surface. A comparison of this new hedonic price model with traditional models suggests that the double power series formulation is a superior representation of accessibility.     

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.