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Article
Publication date: 26 October 2010

Marta Widłak and Emilia Tomczyk

The aim of this paper is to present estimation results of hedonic price models as well as housing price indices for the Warsaw secondary market.

Abstract

Purpose

The aim of this paper is to present estimation results of hedonic price models as well as housing price indices for the Warsaw secondary market.

Design/methodology/approach

Three direct methods of constructing a hedonic price index and four indices that allow for quality adjustment are presented. The paper also discusses theoretical issues related to the estimation and interpretation of hedonic models.

Findings

It is shown that the imputation and the time dummy variable indices are subject to less variation than the characteristic price index. It is also shown that in comparison to the mean and the median, hedonic indices are less variable, which can be interpreted as partial control for quality changes in dwellings sold.

Practical implications

As this research project represents one of the first attempts of hedonic modelling applied to the Polish housing market, its results may be employed by appraisers to gain insight into behaviour of the Warsaw housing market. Practical implications focus on reliable measurement of house price dynamics in Poland. This paper supplies an appropriate methodology for addressing this question and offers empirical solutions.

Originality/value

Employment of hedonic models for construction of quality‐adjusted housing price indices has not yet been explored in Poland. The theoretical and practical aspects of hedonic indices presented in the paper open promising directions for the development of Polish statistics of real estate prices.

Details

Journal of European Real Estate Research, vol. 3 no. 3
Type: Research Article
ISSN: 1753-9269

Keywords

Article
Publication date: 21 February 2019

Gaetano Lisi

The purpose of this paper is to provide an integrated approach that combines the two methods usually used in the real estate appraisals, namely, the income capitalisation…

Abstract

Purpose

The purpose of this paper is to provide an integrated approach that combines the two methods usually used in the real estate appraisals, namely, the income capitalisation method and the hedonic model.

Design/methodology/approach

In order to pull out the link between the income capitalisation approach and the hedonic model, the standard hedonic price function is introduced into the basic model of income capitalisation instead of the house market value. It follows that, from the partial derivative, a direct relation between hedonic prices and discount rate can be obtained. Finally, by using the close relationship between income capitalisation and direct capitalisation, a mathematical relation between hedonic prices and capitalisation rate is also obtained.

Findings

The developed method allows to estimate the capitalisation rate using only hedonic prices. Indeed, selling and hedonic prices incorporate all of the information required to correctly estimate the capitalisation rate. Furthermore, given the close relation among going-in and going-out capitalisation rates and discount rate, the proposed method could also be useful for determining both the going-out capitalisation rate and the discount rate.

Practical implications

Obviously, it is always preferable to estimate the capitalisation rate by just using comparable transactional data. Nevertheless, the method developed in this paper is especially useful when: the rental income data are missing and/or not entirely reliable; the data on rental income and house price are related to different homes; the capitalisation rate, in fact, should compare the rent and value of identical homes. In these cases, therefore, the method can be a valuable alternative to direct estimation.

Originality/value

The large and important literature on real estate economics and real estate appraisal neglects the relationship between hedonic prices and capitalisation rate, thus considering the hedonic model and the income capitalisation approach as two separate and alternative methods. This paper, instead, shows that integration is possible and relatively simple.

Details

Journal of Property Investment & Finance, vol. 37 no. 3
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 30 September 2014

Anthony Owusu-Ansah and Raymond Talinbe Abdulai

The purpose of this paper is to test the accuracy of the explicit time variable (ETV) and the strictly cross-sectional (SCS) hedonic models when constructing house price…

Abstract

Purpose

The purpose of this paper is to test the accuracy of the explicit time variable (ETV) and the strictly cross-sectional (SCS) hedonic models when constructing house price indices in developing markets using Ghana as a case study.

Design/methodology/approach

The quantitative research methodology is adopted where the accuracy of the two hedonic models used in the construction of house price indices is examined using the mean squared error (MSE) and out-of-sample technique. Yearly indices are constructed for each of the models using 60 per cent of the sample data and 40 per cent is used to forecast house prices for each observations based on which the MSEs are calculated.

Findings

The two models produce similar house price trend but the SCS model is more volatile. The ETV model produces the lower MSE, suggesting that it is better to pool data together and includes time dummies (ETV) to estimate indices rather than running separate regressions (SCS) to estimate the index. Using the Morgan–Granger–Newbold test, it is found that indeed the difference between the forecast errors of the two models are statistically significant on a 1 per cent level confirming the accuracy of the ETV model over the SCS model.

Practical implications

This paper has produced convincing results recommending the use of the ETV hedonic model to construct house price indices which is of use to practitioners and academics.

Originality/value

The introduction of financial products like the property derivatives and home equity insurances to the financial market calls for accurate and robust property price indices and the hedonic method is mostly used to construct these indices. While there have been a lot of test conducted as to which variant of the hedonic method to use in developed markets, little is known about the developing markets. This paper contributes to fill these gaps.

Details

International Journal of Housing Markets and Analysis, vol. 7 no. 4
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 29 March 2013

Robert Davis, Bodo Lang and Neil Gautam

It is assumed that consumers consume games to experience hedonic and utilitarian value. However, there is no conceptual model or empirical evidence that supports this…

2851

Abstract

Purpose

It is assumed that consumers consume games to experience hedonic and utilitarian value. However, there is no conceptual model or empirical evidence that supports this hypothesis in the game context or clarifies whether these consumption values have dual mediated or individual effects. Therefore, the purpose of this research is to model the relationship between hedonic and utilitarian consumption and game purchase and usage.

Design/methodology/approach

This research question is answered through two studies. In Study One, qualitative interviews with 18 gamers were implemented to explore the relationship between hedonic and utilitarian consumption and, game purchase and usage behaviour. In Study Two, we surveyed 493 consumers and conducted confirmatory factor analysis and structural equation modelling across four game types to model this relationship.

Findings

The paper concludes that hedonic rather than utilitarian consumption positively impacts purchase and usage. Support was also found for the utilitarian‐hedonic dual mediation model (UHDM). Therefore, utilitarian consumption has an indirect causal effect on game purchase or usage through hedonic consumption.

Practical implications

Game development for consumers online, on wireless devices and on consoles should place greater emphasis on the practical implications of hedonic consumption. Attention could be focused on perceived enjoyment, self‐concept, self‐congruity and self‐efficacy as the primary drivers of use and purchase. Practical solutions should also be developed to develop the UHDM effect.

Originality/value

This is the first paper in the game context to explore and model the relationship between hedonic, utilitarian consumption and the UHDM effect on game purchase and usage. This paper is also unique because it provides results across four game groups: all games (ALL), Sports/Simulation/Driving (SSD), Role Playing Game/Massively Multiplayer Online Role‐Playing Game Strategy (RPG), and Action/Adventure/Fighting (AAF).

Details

Internet Research, vol. 23 no. 2
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 5 February 2018

Marcelo Cajias and Sebastian Ertl

The purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically…

Abstract

Purpose

The purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically weighted regression (GWR) and the generalized additive model (GAM).

Design/methodology/approach

The authors assess the asymptotic properties of linear, spatial and non-linear hedonic models based on a very large data set in Germany. The employed functional form is based on the OLS, GWR and the GAM, while the estimation methodology was chosen to be iterative in forecasting, the fitted rents for each quarter based on their 1-quarter-prior functional form. The performance accuracy is measured by traditional indicators such as the error variance and the mean squared (percentage) error.

Findings

The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. There exists a strong out-of-sample discrepancy between the GWR and the GAM models, whereas the simplicity of the OLS approach is not substantially outperformed by the GAM approach.

Practical implications

For policymakers, a more accurate knowledge on market dynamics via hedonic models leads to a more precise market control and to a better understanding of the local factors affecting current and future rents. For institutional researchers, instead, the findings are essential and might be used as a guide when valuing residential portfolios and forecasting cashflows. Even though this study analyses residential real estate, the results should be of interest to all forms of real estate investments.

Originality/value

Sample size is essential when deriving the asymptotic properties of hedonic models. Whit this study covering more than 570,000 observations, this study constitutes – to the authors’ knowledge – one of the largest data sets used for spatial real estate analysis.

Details

Journal of Property Investment & Finance, vol. 36 no. 1
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 1 January 2021

Gaetano Lisi

The aim of this education briefing is to comment upon how basic hedonic pricing models for the valuation of property can be expanded and developed. In this case, the…

Abstract

Purpose

The aim of this education briefing is to comment upon how basic hedonic pricing models for the valuation of property can be expanded and developed. In this case, the briefing illustrates the use of the new economic approach to the analysis of housing markets, namely the search-and-matching models.

Design/methodology/approach

This education briefing discusses the connection of two important economic theories: the hedonic price theory and the search-and-matching theory.

Findings

This education briefing gives an example of a (non-linear) form of the hedonic price function.

Practical implications

In cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets and this education briefing demonstrates a theoretical model that can be used to provide a theoretical groundwork for the use of a concave hedonic price function in empirical estimates.

Originality/value

This education briefing shows how basic hedonic pricing models can be enhanced by a search-and-matching approach to determine property values.

Details

Journal of Property Investment & Finance, vol. 40 no. 1
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 10 June 2021

Abhijat Arun Abhyankar and Harish Kumar Singla

The purpose of this study is to compare the predictive performance of the hedonic multivariate regression model with the probabilistic neural network (PNN)-based general…

Abstract

Purpose

The purpose of this study is to compare the predictive performance of the hedonic multivariate regression model with the probabilistic neural network (PNN)-based general regression neural network (GRNN) model of housing prices in “Pune-India.”

Design/methodology/approach

Data on 211 properties across “Pune city-India” is collected. The price per square feet is considered as a dependent variable whereas distances from important landmarks such as railway station, fort, university, airport, hospital, temple, parks, solid waste site and stadium are considered as independent variables along with a dummy for amenities. The data is analyzed using a hedonic type multivariate regression model and GRNN. The GRNN divides the entire data set into two sets, namely, training set and testing set and establishes a functional relationship between the dependent and target variables based on the probability density function of the training data (Alomair and Garrouch, 2016).

Findings

While comparing the performance of the hedonic multivariate regression model and PNN-based GRNN, the study finds that the output variable (i.e. price) has been accurately predicted by the GRNN model. All the 42 observations of the testing set are correctly classified giving an accuracy rate of 100%. According to Cortez (2015), a value close to 100% indicates that the model can correctly classify the test data set. Further, the root mean square error (RMSE) value for the final testing for the GRNN model is 0.089 compared to 0.146 for the hedonic multivariate regression model. A lesser value of RMSE indicates that the model contains smaller errors and is a better fit. Therefore, it is concluded that GRNN is a better model to predict the housing price functions. The distance from the solid waste site has the highest degree of variable senstivity impact on the housing prices (22.59%) followed by distance from university (17.78%) and fort (17.73%).

Research limitations/implications

The study being a “case” is restricted to a particular geographic location hence, the findings of the study cannot be generalized. Further, as the objective of the study is restricted to just to compare the predictive performance of two models, it is felt appropriate to restrict the scope of work by focusing only on “location specific hedonic factors,” as determinants of housing prices.

Practical implications

The study opens up a new dimension for scholars working in the field of housing prices/valuation. Authors do not rule out the use of traditional statistical techniques such as ordinary least square regression but strongly recommend that it is high time scholars use advanced statistical methods to develop the domain. The application of GRNN, artificial intelligence or other techniques such as auto regressive integrated moving average and vector auto regression modeling helps analyze the data in a much more sophisticated manner and help come up with more robust and conclusive evidence.

Originality/value

To the best of the author’s knowledge, it is the first case study that compares the predictive performance of the hedonic multivariate regression model with the PNN-based GRNN model for housing prices in India.

Details

International Journal of Housing Markets and Analysis, vol. 15 no. 2
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 29 March 2013

Anthony Owusu‐Ansah

The purpose of this paper is to examine if temporal aggregation matters in the construction of house price indices and to test the accuracy of alternative index…

Abstract

Purpose

The purpose of this paper is to examine if temporal aggregation matters in the construction of house price indices and to test the accuracy of alternative index construction methods.

Design/methodology/approach

Five index construction models based on the hedonic, repeat‐sales and hybrid methods are examined. The accuracy of the alternative index construction methods are examined using the mean squared error and out‐of‐sample technique. Monthly, quarterly, semi‐yearly and yearly indices are constructed for each of the methods and six null hypotheses are tested to examine the temporal aggregation effect.

Findings

Overall, the hedonic is the best method to use. While running separate regressions to estimate the index is best at the broader level of time aggregation like the annual, pooling data together and including time dummies to estimate the index is the best at the lower level of time aggregation. The repeat‐sales method is the least preferred method. The results also show that it is important to limit time to the lowest level of temporal aggregation when construction property price indices.

Practical implications

This paper provides alternative method, the mean squared error method based on an out‐of‐sample technique to evaluate the accuracy of alternative index construction methods.

Originality/value

The introduction of financial products like the property derivatives and home equity insurances to the financial market calls for accurate and robust property price indices. However, the index method and level of temporal aggregation to use still remain unresolved in the index construction literature. This paper contributes to fill these gaps.

Details

Property Management, vol. 31 no. 2
Type: Research Article
ISSN: 0263-7472

Keywords

Article
Publication date: 5 October 2010

Chihiro Shimizu, Hideoki Takatsuji, Hiroya Ono and Kiyohiko G. Nishimura

An 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…

Abstract

Purpose

An 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/approach

The 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).

Findings

Results 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 implications

Following 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/value

In 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.

Details

International Journal of Housing Markets and Analysis, vol. 3 no. 4
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 11 September 2020

Raphael Mutisya Kieti and Walter Ogolla

This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model

Abstract

Purpose

This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model that can accurately estimate the value of apartments.

Design/methodology/approach

The research employed a case study design that was limited to transaction sales and attribute data of apartments in Nyali estate, Mombasa County in Kenya. A sample of 120 sales of apartments obtained from registered real estate firms was analyzed using quantitative methods.

Findings

According to the study results, the hedonic valuation model developed comprises four critical determinants of apartment value, namely, number of parking lots, presence of swimming pool, age of apartment and provision of balcony. The hedonic model was tested and found to be accurate and reliable in estimating apartment value.

Research limitations/implications

The model will improve accuracy, reliability and efficiency in valuation. The application of the model in the valuation of apartments is, however, limited to the case study area where the data are obtained. The scope of application of the model may be improved by increasing the sample size to include apartment sales data from other estates in Mombasa County.

Originality/value

Previous studies that have used the HPM technique in analysis of apartment values have focused on the “explanatory” and “contributory” power of attributes on apartment values, rather than the development and use of the model to measure value. The present study is the first to develop a HPM equation for property value estimation in the apartment real estate sector in Kenya.

Details

Property Management, vol. 39 no. 1
Type: Research Article
ISSN: 0263-7472

Keywords

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