SUMMARY
AbstractOrientation: 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.