Search results
1 – 10 of over 11000The 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…
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
Keywords
Usha L. Pappu, Peter T.L. Popkowski Leszczyc, Ravi Pappu and Neal M. Ashkanasy
This research aims to examine the conditions under which individuals’ olfaction is actively engaged in purchase decisions. Consequently, it introduces the concept of need for…
Abstract
Purpose
This research aims to examine the conditions under which individuals’ olfaction is actively engaged in purchase decisions. Consequently, it introduces the concept of need for smell (NFS) to measure differential motivation for the extraction and use of odor information in buying contexts. A ten-item NFS scale was developed that consists of hedonic and utilitarian dimensions.
Design/methodology/approach
The scale’s dimensionality and construct validity were examined in five studies. The moderating role of NFS and the mediating role of emotions in the relationship between odor perception and consumer responses were examined. The data were analyzed using confirmatory factor analyses and customized PROCESS models.
Findings
The results show that NFS is a two-dimensional construct. The results further support the scale’s internal structure as well as its reliability, convergent, discriminant and nomological validity. NFS moderates the relationship between odor perception and consumer responses, and emotions mediate this relationship. While hedonic NFS strengthens the impact of odor perception on consumer responses, utilitarian NFS weakens this effect.
Research limitations/implications
The present research extends Krishna’s sensory marketing framework, De Luca and Botelho’s scent research framework and Herz et al.’s scent benefits framework, by introducing the concept of NFS into these frameworks. The study demonstrates the relevance and functionality of NFS construct and NFS scale. The study extends the consumer scent research by introducing NFS and illustrating the interplay of odor perception and NFS on consumer responses to scent stimuli.
Practical implications
The NFS scale used in this study adds to the genre of individual difference scales such as need for cognition and need for touch. Given its smell-specific focus, it has applications in a range of consumption contexts. Using NFS, marketers could effectively identify low and high hedonic and utilitarian NFS consumers and position product or ambient scents to serve these segments better. The NFS scale also has implications for the areas of product and service design and development, consumer information search, brand judgments and choice preferences in both scented and non-scented environments.
Originality/value
This work is one of the first attempts, to the best of the authors’ knowledge, to explain motivational differences in active engagement of olfaction, especially in purchase decisions. As a critical step in exploring olfactory information processing, the study demonstrates the relevance and functionality of NFS construct and NFS scale. The study extends the consumer scent research by introducing NFS and illustrating the interplay of odor perception and NFS on consumer responses to scent stimuli.
Details
Keywords
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 weighted…
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
Keywords
This paper aims to explore the in-sample explanatory and out-of-sample forecasting accuracy of the generalized additive model for location, scale and shape (GAMLSS) model in…
Abstract
Purpose
This paper aims to explore the in-sample explanatory and out-of-sample forecasting accuracy of the generalized additive model for location, scale and shape (GAMLSS) model in contrast to the GAM method in Munich’s residential market.
Design/methodology/approach
The paper explores the in-sample explanatory results via comparison of coefficients and a graphical analysis of non-linear effects. The out-of-sample forecasting accuracy focusses on 50 loops of three models excluding 10 per cent of the observations randomly. Afterwards, it obtains the predicted functional forms and predicts the remaining 10 per cent. The forecasting performance is measured via error variance, root mean squared error, mean absolute error and the mean percentage error.
Findings
The results show that the complexity of asking rents in Munich is more accurately captured by the GAMLSS approach than the GAM as shown by an outperformance in the in-sample explanatory accuracy. The results further show that the theoretical and empirical complexities do pay off in view of the increased out-of-sample forecasting power of the GAMLSS approach.
Research limitations/implications
The computational requirements necessary to estimate GAMLSS models in terms of number of cores and RAM are high and might constitute one of the limiting factors for (institutional) researchers. Moreover, large and detailed knowledge on statistical inference and programming is necessary.
Practical implications
The usage of the GAMLSS approach would lead policymakers to better understand the local factors affecting rents. Institutional researchers, instead, would clearly aim at calibrating the forecasting accuracy of the model to better forecast rents in investment strategies. Finally, future researchers are encouraged to exploit the large potential of the GAMLSS framework and its modelling flexibility.
Originality/value
The GAMLSS approach is widely recognised and used by international institutions such as the World Health Organisation, the International Monetary Fund and the European Commission. This is the first study to the best of the author’s knowledge to assess the properties of the GAMLSS approach in applied real estate research from a statistical asymptotic perspective by using a unique data basis with more than 38,000 observations.
Details
Keywords
Joseph Falzon and David Lanzon
The paper aims to describe, construct, and compare alternative price indices for real estate in Malta over the period 1980‐2010.
Abstract
Purpose
The paper aims to describe, construct, and compare alternative price indices for real estate in Malta over the period 1980‐2010.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
Details
Keywords
Porfirio Guevara, Robert Hill and Michael Scholz
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.
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Social implications
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.
Originality/value
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.
Details
Keywords
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
Keywords
Walid Marrouch and Nagham Sayour
This study aims to examine the impact of local air pollution on housing prices in Lebanon.
Abstract
Purpose
This study aims to examine the impact of local air pollution on housing prices in Lebanon.
Design/methodology/approach
The authors apply a hedonic pricing approach using a unique data set from Lebanon. To account for non-linearities in pricing, the authors use three different functional regression forms for the hedonic model approach. The authors also deal with potential omitted variable bias by estimating a hedonic frontier specification.
Findings
The authors find that, in all specifications, air pollution negatively and significantly affects housing prices. The estimated marginal willingness to pay for a one microgram per cubic meter change in particulate matter (PM10) concentration ranges between 2.88% and 3.18% of mean housing prices. The authors also provide evidence of a negative pricing gradient away from the city center, landing support for the monocentric urban development hypothesis.
Research limitations/implications
Given the lack of a data set linking household socioeconomic characteristics with housing data, the authors only consider the first-stage hedonic model.
Practical implications
The proposed hedonic pricing regression approximates a housing pricing equation that can be used by policymakers.
Social implications
The findings suggest that pollution is a significant factor in household behavior in Lebanon.
Originality/value
This paper adds to the scant literature studying the effects of air pollution on housing prices in developing countries. To the best of the authors’ knowledge, this is the first paper to study the impact of pollution on housing prices in a country in the Middle East and North Africa Region.
Details
Keywords
Funlola Famuyiwa and Gabriel Kayode Babawale
– The purpose of this study is to examine the relationship and pricing effects of physical infrastructure on house rents using the hedonic technique.
Abstract
Purpose
The purpose of this study is to examine the relationship and pricing effects of physical infrastructure on house rents using the hedonic technique.
Design/methodology/approach
Primary data are derived through a questionnaire survey and secondary data from existing literature. Sampling data on 211 detached residential buildings with a range of physical infrastructure attributes within Lekki Phase 1 area of Lagos are analysed with the hedonic regression technique.
Findings
Results reveal significant impacts and a range of price premium estimates of physical infrastructure on house rents in the study area.
Originality/value
The study suggests a nouvelle and contextualized approach for sustainable infrastructure delivery, improvement and maintenance. Appropriate pricing will help to guide and support physical infrastructure development and sustainability. When tailored in line with market support, achievable pricing can be attained in setting land-based user charges and tariffs for cost recovery on projected developments and reform. Results from empirical market evidence also provide demand and viability indicators that offer invaluable blueprints, by which governments, policy/decision makers, investors, town-planning authorities and other stakeholders can take sustainable decisions based on priority, in the face of budgetary constraints – a significant characteristic of the Nigerian economy.
Details
Keywords
The paper aims to adopt the hedonic price approach to quantify the brand equity of information and communication technology (ICT) products, narrowed down to laptop computers…
Abstract
Purpose
The paper aims to adopt the hedonic price approach to quantify the brand equity of information and communication technology (ICT) products, narrowed down to laptop computers, laser printers, liquid crystal display computer screens, and mobile phones.
Design/methodology/approach
The hedonic price model features the list price as the dependent variable of the regression, whilst the measurable attributes of the product and brand dummies are on the right‐hand side. Additionally, the model can be adjusted to measure brand effects on profit margins as well.
Findings
In most of the price and log price models, brand dummies are significant, and positively linked to the consumers' willingness to pay. Nevertheless, amongst the four ICT products in this study, only the laptop brands show positive values. Negative but significant brand dummies suggest that brands are undoubtedly important; however, other features exhibit higher value to consumers.
Research limitations/implications
As is the case with other financial approaches to valuing brands, the results do not explain how to exploit those values; rather, it identifies the brand's position as measured against other brands.
Practical implications
Negative brand premiums imply that brand loyalty is not strong in the market, and that the opportunity exists for a new brand's penetration. The construction of brand premium rankings should prove beneficial to firms who wish to evaluate their current position against other competitors. Regarding the products' features, the results suggest that consumers generally focus their decision to purchase a particular brand on its basic or core features.
Originality/value
The paper proposes another approach to assessing brand equity, namely, in terms of both price and profit margin premiums. Though imperfect, the hedonic methodology is relatively simple and relies on available secondary data.
Details