A Priori Spatial Segmentation of Commercial Property Market using Hedonic Price Modelling

Abstract

Abstract The improvement of property price modelling accuracy using property market segmentation approaches is well documented in the housing market. However, that cannot be said of the commercial property market which is adjudged to be volatile, heterogeneous and thinly traded. This study, therefore, determines if the commercial property market in Malaysia is spatially segmented into submarkets and whether accounting for the submarkets improves the accuracy of price modelling. Using a 11,460 shop-offices transaction dataset, the commercial property submarkets are delineated by using submarket binary dummies in the market-wide model and estimating a separate hedonic model for each submarket. The former method improves the model fit and reduces error by 5.6% and 6.5% respectively. The commercial property submarkets are better delineated by estimating a separate hedonic model for each submarket as it improves the model fit by about 7% and reduces models’ error by more than 10%. This study concludes that the Malaysian commercial property market is spatially segmented into submarkets. Modelling the submarkets improves the accuracy and correctness of price modelling.