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 variablesâ€“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.
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