Count Data Models and the Problem of Zeros in Recreation Demand Analysis

Abstract In this paper we develop a count data model for consumer demand which explicitly allows for a large number of zero observations for the dependent variable, and separation of the participation versus quantity decisions. The advantages of the model over traditional censored and count demand models are brought out, and the appropriate consumer surplus measures are derived. By introducing a random error term into the traditional count model demand function, the appropriate measure of expected consumer surplus for count models is derived. The model is illustrated using a recreational survey of the general population.