Orientation: Residential property is an important segment of the property market in South Africa. Residential property transactions are typically infrequent and relate to a highly differentiated set of items making measurement techniques complex and difficult. Research purpose:The aim of this research was to develop a statistical model to estimate listing prices of apartments in KwaZulu-Natal, South Africa, and build a software application to disseminate the results thereof.Motivation for the study: This study presents a novel alternative to the log linear (ordinary least squares) method of deriving a hedonic price function for residential property where the arithmetic mean is computed as the expected value and not the geometric mean.Research design, approach and method: Using a data set of 1314 residential apartments provided by Private Property (Pty) Ltd, this research derives a hedonic price function for residential property using a generalised linear model based on the gamma distribution and log-link function. Main findings:The results showed that floor area, number of bedrooms, number of bathrooms and a dummy variable for suburb (location) were statistically significant determinants of listing prices.Practical/managerial implications: A software application, called the listing price calculator, was developed to disseminate the results of the model for commercial use by real estate buyers, sellers and agents, bridging the gap between academia and business. Contribution/value-add:This study derives a hedonic price function for residential property using a generalised linear model based on the gamma distribution and log-link function, which is novel in South African research.

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Background and objectiveResidential property is an important component of individual and national wealth where it is capitalised on household balance sheets, informing economic policy formulation (Hill 2013). Goodhart and Hoffman (2008) conducted a study providing evidence of relationships between house prices, credit and broad money. Using vector auto-regression fitted with ordinary Orientation: Residential property markets play an important role in economies, informing policy development and decision-making. However, measuring quality-adjusted growth is difficult because of the heterogeneity of properties. Hedonic regression is frequently used in real estate econometric studies as a quality-adjusted technique to estimate residential property prices for the development of price indices. Log linear models are typically used to derive these hedonic price functions.Research purpose: This article develops hedonic pricing functions using generalised linear models for South African residential property listings over a 5-year period.Motivation for the study: A parametric alternative to the log linear model is investigated to address the limited studies conducted in South Africa. An important feature of this study is the inclusion of different property types and the geographic scope.Research approach/design and method: The data set consisted of 415 200 residential properties from all over South Africa. The data spanned a period from January 2013 to August 2017. Several generalised linear models were developed and compared. Main findings:The gamma generalised linear model provided the best overall fit, generalising well to the unseen validation data. An added benefit of this model is that the estimates were kept on the original scale, avoiding the need for back transformation which is an appealing feature of any model. A dummy locational variable was shown to account for the spatial dependency in the data. Practical/managerial implications:This framework provides property market participants with the ability to quantify the utility derived over the marginal distribution of the physical characteristics of properties. This research presents the groundwork to create a property price index where index number theory could be applied to the counterfactual predicted values obtained from hedonic price models to measure price inflation over time Contribution/value-add: This study analysed the South African residential property market based on an online company's data, purportedly covering the entire market. No real estate hedonic price studies have been identified in South Africa with this level of scope. The gamma generalised linear model is a novel candidate to develop parametric real estate hedonic price functions.

Due to the heterogeneous nature of residential properties, determining selling prices which will reconcile supply and demand is difficult. Establishing realistic listing prices is vitally important for sellers to prevent prolonged time on market. Sellers have several resources available to assist in this endeavour, all of which involve understanding current market dynamics through analysing recent sales and listing data. Property portals which aggregate real estate agencies’ data, hosting it on online platforms, are one such resource, along with individual real estate agencies. Leveraging this data to develop solutions that could aid sellers in listing price decision making is a potential business objective that could not only add value to sellers but create a competitive advantage by increasing traffic to an online real estate platform. Using data provided by a South African online property portal, this paper creates a web application using machine learning to estimate listing prices for different types of homes throughout South Africa. This study compared log linear and gradient boosted models, estimating residential listing prices over a four-year period. The results indicate that although log linear models are suitable to account for spatial dependency in the data through the inclusion of a fixed location effect, the assumption of linear functional form was not satisfied. The gradient boosted models do not impose explicit functional form requirements, making them flexible candidates. Similarly, these models were able to handle the spatial dependency adequately. The gradient boosted models also achieved a lower out of sample error compared to the log linear models. The findings show that over observation periodperiod, larger properties consistently experience a diminishing return at some point over the marginal distribution of physical characteristics. The web application details how sellers are easily able to obtain mean listing price estimates and gauge the growth thereof, by simply inputting their property interest criteria.