Estimating price expectations in the OTC medicine market: An application of dynamic stochastic discrete choice models to scanner panel data

This paper examines the differences in managerial implications of dynamic and reduced-form models when the models are applied to brand choice behavior in the over-the-counter (OTC) back and leg ache medicine market. The models we develop are useful to brand managers and researchers who are interested in dynamic factors that influence choice such as prior experience with brands, future price expectations, and an overall concern for the future. The key findings of our research are that the dynamic model is supported by the data over the single-period model; that past experience with a brand matters in current choice; that consumersʹ price expectations influence their current choices; and that expectations follow a distinct pattern.