The authors develop a dynamic approach to measuring the evolution of comparative brand premium, an important component of brand equity. A comparative brand premium is defined as the pairwise price difference between two products being identical in every respect but brand. The model is based on hedonic regressions and grounded in economic theory. In constrast to existing approaches, the authors explicitly take into account and model the dynamics of the brand premia. By exploiting the premias intertemporal dependence structure, the Bayesian estimation method produces more accurate estimators of the time paths of the brand premia than other methods. In addition, the authors present a novel yet straightforward way to construct confidence bands that cover the entire time series of brand premia with high probability. The data required for estimation are readily available, cheap, and observable on the market under investigation. The authors apply the dynamic hedonic regression to a large and detailed data set about laser printers gathered on a monthly basis over a four-year period. It transpires that, in general, the estimated brand premia change only gradually from period to period. Nevertheless the method can diagnose sudden downturns of a comparative brand premium. The authors dynamic hedonic regression approach facilitates the practical evaluation of brand management.
brand equity price premium hedonic regression Bayesian estimation dynamic linear model