Modelling and estimation of social interaction effects in new product diffusion

Abstract

We present a new product choice model in which individual agents are assumed to interact with each other across spatial hierarchies under random Gaussian laws. A restricted form that allows estimation of the model and inference on the random interaction structure on available data is then derived. This is essentially a random coefficients model which we estimate on repeated cross-sectional data for the adoption of video cassette recorders in Britain. It is argued that the random coefficient approach, based on economic and social-theoretic arguments allows for more accurate inference on the structure of social interactions, and thus may provide a useful way to help alleviate the inferential problem caused by the identification issues stated in the literature. This very same problem has for long been at the core of the debate between alternative economic and marketing theories of new product diffusion.