Modelling Scale Effect in Crosssection Data:The Case of Hedonic Price Regression

An innovative and simple experiment with cross-section data ordering is carried out to exploit a basic and common feature between many economic variables–nonlinear scale dependence. The experiment is tried on hedonic price regression models using two data sets, one for automobiles and the other computers. The key findings are: (a) Hedonic price indices can be significantly biased if they are constructed using models which disregard possible nonlinear scale effects latent in random data samples; (b) Scale-based data ordering offers considerable potential to filter such scale-dependent information from cross-section samples; (c) The filtering can be easily carried out by systematic adoption of dynamic modelling methods.