A LTHOUGH a rigorous discussion of the performance of the broiler industry requires a preliminary in the form of a discussion of behavior of a firm and industry that face a seasonal demand, I am going to forego this preliminary because of a limitation on time. Today I want to concentrate on the problem of quantifying our answers in an economic study.1 Consequently, the purpose of this paper is to illustrate the construction of a simulation model of the broiler industry and to present some of the quantitative answers which such a model was able to provide. There are a number of ways to build a simulation model. Usually, an individual postulates structural relationships (e.g., demand curves, supply curves, etc.), fits these with a regression using observed data, and compares the results generated within such a simulation model with the data used to fit the regression curves. An example of such a procedure is the study of interest rates and financial portfolios by de Leeuw [4]. The study being presented today attempted what I believe is a new approach: the construction of a simulation model in which industry response was the sum of the responses of the firms within the industry.