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The paper aims to describe, construct, and compare alternative price indices for real estate in Malta over the period 1980‐2010.

The paper utilises the technique of hedonic regression analysis to construct four hedonic price indices. One of the constructed indices is based the unconstrained hedonic methodology. Two other indices are variants of the constrained hedonic technique, while the fourth consists of an imputed hedonic index. The hedonic indices are then compared to other 12 conventional indices, namely the Laspeyres, Paasche and Fisher indices (constant weight and chain linked) that are constructed by utilizing the mean and median house prices pertaining to 14 different types of houses.

All indices are found to move closely together, growing between six and seven times between 1980 and 2010. The average annual compound growth rate of the 16 indices was found to be 6.5126 percent. The paper also shows how the estimated hedonic coefficients can be used to construct regional price indices for different combinations of housing characteristics.

The paper builds on previous work related to house prices in Malta. Its main contribution is the construction of hedonic indices that are based on advertised prices that span over a relatively long period of 31 years, together with the construction of constant weight and chain linked Laspeyres, Paasche and Fisher indices.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This study aims to estimate the quality-adjusted changes in residential mobile consumer prices by controlling for the changes in the relevant service characteristics and quality, in a case study on Hungary between 2015 and 2021; compare the results with changes measured by the traditionally calculated official telecommunications price index of the Statistical Office; and discuss separating the hedonic price changes from the effect of a specific government intervention that occurred in Hungary, namely, the significant reduction in the value added tax rate (VAT) levied on internet services.

Since the price of commercial mobile offers does not directly reflect the continuous improvements in service characteristics and functionalities over time, the price changes need to be adjusted for changes in quality. The authors use hedonic regression analysis to address this issue.

The results show significant hedonic price changes over the observed seven-year period of over 30%, which turns out to be primarily driven by the significant developments in the comprising service characteristics and not the VAT policy change.

This paper contributes to the literature on hedonic price analyses on complex telecommunications service plans and enhances this methodology by using weights and analysing the content-related features of the mobile packages.

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.

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.

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.

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.

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.

This study aims to show how hedonic methods can be used to compare the performance of the public and private sector housing markets in Costa Rica.

Hedonic price indexes are computed using the adjacent-period method. Average housing quality is measured by comparing hedonic and median price indexes. The relative performance of the public and private sector residential construction is compared by estimating separate hedonic models for each sector. A private sector price is then imputed for each house built in the public sector, and a public sector price is imputed for each house built in the private sector.

The real quality-adjusted price of private housing rose by 12 per cent between 2000 and 2013, whereas the price of private housing rose by 9 per cent. The average quality of private housing rose by 45 per cent, whereas that of public housing fell by 18 per cent. Nevertheless, the hedonic imputation analysis reveals that public housing could not be produced more cheaply in the private sector.

The quality of public housing has declined over time. The hedonic analysis shows that the decline is not because of a lack of competition between construction firms in the public sector. An alternative demand side explanation is provided.

This study applies hedonic methods in novel ways to compare the relative performance of the public and private housing sectors in Costa Rica. The results shed new light on the effectiveness of public sector housing programs.

This paper aims to evaluate the relationships among consumer expertise, hedonic orientation, price consciousness, and consumption using wine as the focal product. While these variables' impact on decision making within this industry have been examined in isolation, this is believed to be the first study marrying these hedonic and non‐hedonic characteristics.

Data were collected from a convenience sample of wine purchasers consisting of faculty, staff and upper level students at a major southwestern university using a 95 item questionnaire. In total, 241 usable surveys were included in the analysis.

The findings indicate support for all five hypothesized relationships. The importance of hedonic orientation as a psychographic characteristic emerges. The relationship between expertise and consumption is moderated by hedonic orientation as is the relationship between expertise and price consciousness. Price consciousness mediates the relationship between expertise and consumption, but only for those consumers who have a high hedonic orientation.

The results may not be generalizable across all consumers given the convenience nature of the sample. Additionally only one product category, wine, is included.

This study examines wine consumers' hedonic orientation and its impact on ultimate consumption. Further, this study is also valuable to the field of consumer behavior through development of a scale to capture the dimensions underlying the construct of hedonic orientation. Previous researchers have established profiles of persons who engage in hedonic consumption, but have not assessed an individual's hedonic orientation.

This paper aims to understand housing demand of urban Indian households in terms of housing and household-level characteristics. Because a house is a bundle of certain characteristics which vary across houses, each characteristic has an implicit price. Finding this implicit price for certain important characteristics is the first objective of this study. The second objective of the paper is to compute the income elasticity and price elasticity of housing demand for these cities.

To achieve comparable estimates, household-level data from India’s National Sample Survey Organisation housing surveys for the years 2002 and 2008-2009 have been used. A hedonic price function is estimated using ordinary least squares (OLS) and Box-Cox functional forms to estimate the implicit prices of housing characteristics. This exercise is attempted for owned and rented houses separately. Demand function required for computing the elasticities, uses the hedonic price index derived from the implicit prices and household characteristics.

The study finds housing demand to be income elastic and price inelastic for the six cities across both the time periods.

Firstly, this study includes housing characteristics such as individual access to drinking water, modern sanitation facility, separate kitchen, condition of the structure, existence of a road with street light and whether the house is in a slum or non-slum area in the hedonic price function. These variables were not used in any of the earlier studies pertaining to India. Secondly, it uses the Box-Cox non-linear form to derive the hedonic price function, a specification not used earlier. Thirdly, this is the first study analysing housing demand across the six largest Indian cities.

The purpose of this paper is to give retailers an insight into consumers' capacity for feeling pleasure associated with specific purchase motivations across different product categories.

A hedonic regression model was estimated from data collected from shoppers in shopping malls that enabled the generation of implicit prices of each constituent purchasing motive.

Hedonic values of consumer motivations vary for different products categories. Convenience items, like bread, allow little scope for self‐congruence, whereas shampoo offers significant scope for pleasurable emotive appeals to boost consumers' status enhancement and social image. This study identified opportunities to create good feelings for the purchase of both bread and shampoos, by engaging shoppers' attention on themes relating to social referents and family values. Shopping items like apparel and specialty items like cosmetics offer prospects of titillating consumer motives of status and self‐image enhancement, respectively, by engaging them with reputable merchandise in reputable settings.

No insight was sought on the hedonic value of consumers' buying motivations of impulse purchases.

Products that are used in public (apparel) or whose consumption outcome is manifest in public (shampoos and cosmetics), have purchase motivations that are susceptible to hedonic appeals. On the other hand, only a few purchase motivations for products like bread, with limited “public face”, have some hedonic value. The results of this study inform retailers on choice of purchase motivations to direct engagement appeals in order to generate emotional excitement. Getting consumers to fantasize on themes relating to relevant purchasing motives could facilitate their purchase choice.

Targeting consumers' preferred urges is an efficient way to stimulate buying intentions.

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.”

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).

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%).

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.

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.

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.