COUNT DATA MODELS AND THE PROBLEM OF ZEROS IN RECREATION DEMAND ANALYSIS

In this paper we develop a count data model for consumer demand which explicitly allows for a large number of zero observations for the depe ndent variable, and separation of the participation versus quantity de cisions. The advantages of the model over traditional censored and cou nt demand models are brought out, and the appropriate consumer surplus measures are derived. By introducing a random error term into the tra ditional count model demand function, the appropriate measure of expec ted consumer surplus for count models is derived. The model is illustr ated using a recreational survey of the general population.