Sorting out access and neighbourhood factors in hedonic price modelling

This paper investigates the analytical potential of factor analysis for sorting out neighbourhood and access factors in hedonic modelling using a simulation procedure that combines GIS technology and spatial statistics. An application to the housing market of the Quebec Urban Community (575,000 in population; study based on some 2,400 cottages transacted from 1993 to 1997) illustrates the relevance of this approach. In the first place, accessibility from each home to selected activity places is computed on the basis of minimum travelling time using the TransCAD transportation‐oriented GIS software. The spatial autocorrelation issue is then addressed and a general modelling procedure developed. Following a five‐step approach, property specifics are first introduced in the model; proximity and neighbourhood attributes are then successively added on. Finally, factor analyses are performed on each set of access and census variables, thereby reducing to six principal components an array of 49 individual attributes. Substituting the resulting factors for the initial descriptors leads to high model performances, controlled collinearity and stable hedonic prices, although remaining spatial autocorrelation is still detected in the residuals.