As applied researchers in business and economics, faced with the task of predicting market response, we seldom know the functional form of the response. Perhaps market response is a nonlinear monotonic, or even nonmonotonic, function of explanatory variables. Perhaps it is determined by interactions of explanatory variables. When we try to represent complex market relationships within the context of a linear model, using appropriate transformations of explanatory and response variables, we learn how hard the work of statistics can be. Finding reasonable models is a challenge, and justifying our choice of models to our peers can be even more of a challenge.
Alternative specifications abound.
Some perform quite well, if we are to believe the results of simulation studies. We review these studies and discuss implications. Thomas W. Miller has experience in business and academia. He holds graduate degrees in psychology and statistics from the University of Minnesota and in business and economics from the University of Oregon. For ten years, Tom worked in the computer industry, where he held technical, sales, and marketing positions.