Modeling consideration sets and brand choice using artificial neural networks

Brand choice can be viewed as a two-step process. Households first construct a consideration set, which does not necessarily include all available brands, and then make a final choice from this set. In this paper we put forward an econometric model for this two-step process, where we take into account that consideration sets usually are not observed. Our model is an artificial neural network, where the consideration set corresponds with the hidden layer of the network. We discuss representation, parameter estimation and inference. We illustrate our model for the choice between six detergent brands and show that the model improves upon one-step models, in terms of fit and out-of-sample forecasting.