Hedonic House Price Research Articles

Estimation of a Hedonic House Price Model with Bargaining: Evidence from the Italian Housing Market

This empirical paper tests the role of bargaining in the formation process of housing prices in Italy. Housing markets are “thin”, local and decentralized, and thus buyers and sellers may have some market power. Hence, the selling price is influenced both by the characteristics of the product as well as by the bargaining power of the buyers and sellers. Furthermore, the bargaining power of the seller (buyer) can also be viewed as the cost of incomplete information imposed on the buyer (seller). The empirical results derived from multiple regression analysis support our theoretical assumptions. In fact, the variables created as proxies of bargaining power of the parties, and incorporated into the hedonic price function, are statistically significant and help to improve the performance of the hedonic model, thus reducing the differences between predicted and observed selling prices.

Forecasting House Prices in Germany

Die Finanz- und Wirtschaftskrise hat erneut gezeigt, dass Preisfluktuationen am Immobilienmarkt nicht nur einen substanziellen Einfluss auf die Finanzmarktstabilitat sondern auch auf die gesamtwirtschaftliche Aktivitat ausuben. Demnach ist es aus makrookonomischer Sicht wichtig, Immobilienpreisentwicklungen fruhzeitig erkennen und akkurat prognostizieren zu konnen. Ziel dieser Arbeit ist es, Preisentwicklungen fur Deutschland in verschieden Segmenten des Immobilienmarktes am aktuellen Rand zu erfassen und fur die kurze Frist von bis zu sechs Monaten zu prognostizieren. Basierend auf monatlich verfugbaren Immobilieninseraten auf der Internetplattform von ImmobilienScout24 werden dazu in einem ersten Schritt hedonische Preisindizes gebildet. In einem zweiten Schritt wird die Entwicklung dieser Preisindizes prognostiziert. Beginnend mit einem einfachen AR(p)-Prozess wird der Informationsgehalt verschiedener zusatzlicher Indikatoren mit Hilfe von VAR und ARDL-Modellen untersucht. Wahrend sich der durchschnittliche quadratische Schatzfehler in den einzelnen Modellen im Vergleich zum AR-Modell nur geringfugig verringert, zeigt sich, dass mit Hilfe von geeigneten Prognosekombinationen die Prognosegute signifikant verbessert werden kann.

Hedonic house prices and spatial quantile regression

Despite its long history, hedonic pricing for housing valuation remains an active research area, and applications of new estimation methods continually push research frontiers. However, housing studies regarding Chinese cities are limited because of the short history of China’s free housing market. Such studies may, nonetheless, provide new insights given the nation’s current transitional stage of economic development. Therefore, this research makes use of publicly accessible sources to construct a new micro-dataset for an emerging Chinese city, Changsha, and it incorporates quantile regression with spatial econometric modeling to examine how implicit prices of housing characteristics may vary across the conditional distribution of house prices. Substantial variations are found, and the intuitions and implications are discussed. Additionally, the spatial dependence exhibits a U-shape pattern. The dependence is strong in the upper and lower parts of the response distribution, but it is little in the medium range.

Spatially explicit inverse modeling for urban planning

Urban modeling methods have traditionally followed a forward modeling approach. That is, they use data from today’s situation to forecast or simulate future states of an urban system. In this paper, we propose an inverse modeling approach by which we shift our attention from solely forecasting or simulating future states of an urban system to steering it to a desired state in the future via key variables characterizing the system in the present. We first present a theoretical framework for the use of the inverse approach in urban planning. We test the power of the proposed method using a hedonic house price model in a metropolitan area in Switzerland to investigate the negative effects of densification on house prices. The model is calibrated by mixed geographically weighted regression in order to account for spatial variability of both key variables and model outputs. We show how devaluation of house prices caused by densification can be compensated by different levels of socioeconomic, locational as well as structural variables. We illustrate and discuss how trade-offs between variables may lead to more feasible results from an urban planning perspective. We conclude that the proposed method might be valuable for urban planners for developing implementable spatial plans based on future visions. In particular, the fact that other model specifications than hedonic house price model can also be employed to formulate an inverse model application, allows planners to address other type of problems or externalities from urbanization processes such as urban sprawls, environmental pollution or land uses change.

Hedonic House Prices and Spatial Quantile Regression

Despite its long history, hedonic pricing for housing valuation remains an active research area, and applications of new estimation methods continually push research frontiers. However, housing studies regarding Chinese cities are limited due to the short history of China’s free housing market. Such studies may, nonetheless, provide new insights given the nation’s current transitional stage of economic development. Therefore, in this research, we utilize publicly accessible sources to construct a new dataset for an emerging Chinese city – Changsha, and incorporate quantile regression and spatial econometric modeling to examine how implicit prices of housing characteristics may vary across the conditional distribution of house prices. Substantial variation exists across quantiles, suggesting that ordinary regression is insufficient on its own. Quantile estimates of a spatial-lag model show considerable spatial dependence in the upper and lower parts of the distribution but little dependence in the medium range. Several other interesting patterns are also found, and their intuitions and implications are discussed.

A functional connectivity approach for modeling cross-sectional dependence with an application to the estimation of hedonic housing prices in Paris

This paper proposes a functional connectivity approach, inspired by brain imaging literature, to model cross-sectional dependence. Using a varying parameter framework, the model allows correlation patterns to arise from complex economic or social relations rather than being simply functions of economic or geographic distances between locations. It nests the conventional spatial and factor model approaches as special cases. A Bayesian Markov Chain Monte Carlo method implements this approach. A small scale Monte Carlo study is conducted to evaluate the performance of this approach in finite samples, which outperforms both a spatial model and a factor model. We apply the functional connectivity approach to estimate a hedonic housing price model for Paris using housing transactions over the period 1990–2003. It allows us to get more information about complex spatial connections and appears more suitable to capture the cross-sectional dependence than the conventional methods.

Prices, Expectations and the Changing Housing Market: a Commentary and Discussion

The last decade of housing price fluctuation, crises of housing affordability and the turmoil of housing foreclosures brought housing, and housing markets, closer to centre stage in the debates over the future of the global economy. As part of the renewed interest in housing some recent papers have questioned whether we have an adequate model for understanding housing prices and housing market behaviour more broadly. Specifically, is the expected utility model of housing market behaviour, and the associated hedonic housing price model, still relevant in an increasingly uncertain housing market? Certainly the recent rapid escalation in housing prices and the behaviour of agents in the housing market has further stimulated rethinking of our models of housing markets. Analysts are asking about the future behaviour of and in housing markets, and how the housing market will function in the post housing market bubble decade. It is a useful time to take another look at how the housing market behaves and what underpins housing prices. Even to ask the question: do we need a new model of housing market behaviour?

Urban villages and housing values in China

The presence of urban villages is a unique product of China's urbanization. In this article, we explore the effects of urban villages on the formal housing market. For this purpose, we develop a hedonic housing price model to investigate whether the proximity to urban villages affects the selling price of urban housing units. Controlling for the structure and other characteristics of urban housing units, we find that housing prices are lower the closer the buildings are from urban villages. We then carry out a survey of households living nearby and explore how they are affected by urban villages. The results indicate that there are both positive and negative effects associated with these villages.

The Comparison of Hedonic Housing Price Models in the Busan Housing Market using Spatial Econometrics Methodology

The Comparison of Hedonic Housing Price Models in the Busan Housing Market using Spatial Econometrics Methodology

Values of environmental landscape amenities during the 2000–2006 real estate boom and subsequent 2008 recession

This research suggests that consumers' marginal willingness to pay for environmental landscape attributes, such as water view, developed open space and forest-land open space, decreased during the 2008 recession compared to the 2000–2006 real estate boom. Estimates were obtained from a spatial hedonic housing price model after controlling for household location patterns and structural differences between the periods. Because the decline in amenity values was probably due to a temporary deterioration in economic conditions, the amenity values will probably rebound with economic recovery. Thus, development decisions based on the lower estimated amenity values measured during a temporary deterioration in economic conditions may be determined suboptimal post-economic recovery.

The Impact of the Presence of a Natural Gas Pipeline on Residential Property Values

A recent LNG terminal building boom has, in turn, produced a natural gas pipeline building boom. Some property owners have expressed concern that a pipeline would reduce the values of nearby properties. This study uses the hedonic housing price approach to estimate the impacts of pipeline. The study finds that proximity to a natural gas pipeline has no statistically or economically significant impact on residential property values. These results are consistent with previous published research and suggest that the positive amenity potential associated with pipeline proximity exceed and perceived costs associated with potential safety or environmental risks.

Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris

This paper proposes maximum likelihood estimators for panel seemingly unrelated regressions with both spatial lag and spatial error components. We study the general case where spatial effects are incorporated via spatial errors terms and via a spatial lag dependent variable and where the heterogeneity in the panel is incorporated via an error component specification. We generalize the approach of Wang and Kockelman (2007) and propose joint and conditional Lagrange multiplier tests for spatial autocorrelation and random effects for this spatial SUR panel model. The small sample performance of the proposed estimators and tests are examined using Monte Carlo experiments. An empirical application to hedonic housing prices in Paris illustrate these methods. The proposed specification uses a system of three SUR equations corresponding to three types of flats within 80 districts of Paris over the period 1990–2003. We test for spatial effects and heterogeneity and find reasonable estimates of the shadow prices for housing characteristics.

A Game-Theoretic Approach to Hedonic Housing Prices

A Game-Theoretic Approach to Hedonic Housing Prices

On nonparametric estimation of a hedonic price function

AbstractRecently, 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.

Structural and temporal changes in the housing market and hedonic housing price indices

PurposeAn economic indicator faces two requirements. It should be reported in a timely manner and should not be significantly altered afterward to avoid erroneous messages. At the same time, it should reflect changing market conditions constantly and appropriately. These requirements are particularly challenging for housing price indices, since housing markets are subject to large temporal/seasonal changes and occasional structural changes. The purpose of this paper is to estimate a hedonic price index of condominiums of Tokyo, taking account of seasonal sample selection biases and structural changes in a way it enables us to report the index in a manner which is timely and not subject to change after reporting.Design/methodology/approachThe paper proposes an overlapping‐period hedonic model (OPHM), in which a hedonic price index is calculated every month based on data in the “window” of a year ending this month (this month and previous 11 months). It also estimates standard hedonic housing price indexes under alternative assumptions: no structural change (“structurally restricted”: restricted hedonic model) and different structure for every month (“structurally unrestricted”: unrestricted hedonic model).FindingsResults suggest that the structure of the housing market, including seasonality, changes over time, and these changes occur continuously over time. It is also demonstrated that structurally restricted indices that do not account for structural changes involve a large time lag compared with indices that do account for structural changes during periods with significant price fluctuations.Social implicationsFollowing the financial crisis triggered by the US housing market, housing price index guidelines are currently being developed, with the United Nations, International Monetary Fund, and Organization for Economic Co‐operation and Development leading the way. These guidelines recommend that indices be estimated based on the hedonic method. We believe that the hedonic method proposed here will serve as a reference for countries that develop hedonic method‐based housing price indices in future.Originality/valueIn the many studies involving conventional housing price indices, whether those using the repeat‐sales method or hedonic method, there are few that have analyzed the problem of market structural changes. This paper is the first to construct a large database and systematically estimate the effect that changes in market structure have on housing price indices.

An Application of Spatial Econometrics in Relation to Hedonic House Price Modeling

This paper applies spatial econometrics in relation to hedonichouse price modeling. Some basic spatial model alternatives areused for a battery of relevant tests. Geographically-weightedregression, semiparametric analysis, and the mixed spatialDurbin model are also applied. The purpose is to detect missingspatial variables, misspecified functional form, and spatialheterogeneity in estimated parameters. Such misspecificationshave been shown to give spurious results in relation to somefrequently used directional based tests. Significant modelimprovement is achieved, so the paper should be of generalinterest as an example of practical econometric modeling withinthe field.

Maximum Likelihood Estimation and Lagrange Multiplier Tests for Panel Seemingly Unrelated Regressions with Spatial Lag and Spatial Errors: An Application to Hedonic Housing Prices in Paris

This paper proposes maximum likelihood estimators for panel seemingly unrelated regressions with both spatial lag and spatial error components. We study the general case where spatial effects are incorporated via spatial errors terms and via a spatial lag dependent variable and where the heterogeneity in the panel is incorporated via an error component specification. We generalize the approach of Wang and Kockelman (2007) and propose joint and conditional Lagrange Multiplier tests for spatial autocorrelation and random effects for this spatial SUR panel model. The small sample performance of the proposed estimators and tests are examined using Monte Carlo experiments. An empirical application to hedonic housing prices in Paris illustrates these methods. The proposed specification uses a system of three SUR equations corresponding to three types of flats within 80 districts of Paris over the period 1990-2003. We test for spatial effects and heterogeneity and find reasonable estimates of the shadow prices for housing characteristics.

Mixed environmental quality indexes for hedonic housing price models: an alternative with area-to-point kriging with external drift

(a) When environmental variables are included in hedonic house price models, the locations where a property transaction has been taken place are more than those equipped with an environmental monitoring station. (b) When environmental variables are numerous, an environmental quality index (EQI) is needed. The solution is to interpolate (kriging) environmental variables and, subsequently, elaborate an EQI, because of the lower prediction variance. (c) Environmental informations can be both objective and subjective. The potential mismatch between the spatial support for both the objective informations and the subjective ones is solved by using a kriging strategy (area-to-point kriging) that forces scarce objective environmental informations to be coherent with dense subjective ones. These options for elaborating EQIs are compared in Madrid City (Spain).

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.

The impact of hazardous waste on property values: The effect of lead pollution

This paper examines the impact of lead pollution on property values in Anniston, Alabama, one of the most polluted cities in the US. A hedonic house price analysis allows us to examine the extent of capitalization of lead contamination's effect on property values there, as well as property value losses due to the presence of an Army Depot. We estimated that lead cleanup would provide an increased property value of $1,140 per household and found that living 1 km closer to the polluting sites reduces property values by approximately 2%, a figure consistent with previous research regarding the connection between environmental disamenities and property values.