  Reference prices have long been studied in applied economics and business
research. One of the classic formulations of the reference price is in terms of
an iterative function of past prices. There are a number of limitations of such
a formulation, however. Such limitations include burdensome computational time
to estimate parameters, an inability to truly account for customer
heterogeneity, and an estimation procedure that implies a misspecified model.
Managerial recommendations based on inferences from such a model can be quite
misleading. We mathematically reformulate the reference price by developing a
closed-form expansion that addresses the aforementioned issues, enabling one to
elicit truly meaningful managerial advice from the model. We estimate our model
on a real world data set to illustrate the efficacy of our approach. Our work
is not only useful from a modeling perspective, but also has important
behavioral and managerial implications, which modelers and non-modelers alike
would find useful.
