This paper is concerned with the use of spectral analysis to analyze data generated by computer simulation experiments with models of economic systems. An example model serves to illustrate two different applications of spectral analysis. First, spectral analysis is used to construct confidence bands and to test hypotheses for the purpose of comparing the results of the use of two or more alternative economic policies. Second, spectral analysis is employed as a technique for validating an econometric model.

N thi's paper we describe an econometric model of the American tobacco industry for the period 1949 through 1966. The model contains 19 equations and is divided into three major blocks - (1) leaf production, (2) leaf price, and (3) cigarettes. The objective is to explain the behavior of the tobacco industry over an 18-year period. Ultimately, we hope to use the model to perform policy simulation experiments to evaluate the effects of alternative governmental and managerial policies on the behavior of the industry. We begin with a brief description of the industry. Next we discuss the theoretical specification of the model and the statistically estimated equations. We conclude with some example simulation results which provide additional evidence of the validity of the model for explaining the behavior of the tobacco industry over the period 1949 through 1966

T HE model presented in this paper is a system of recursive linear regression equations, the parameters of which are esti-mated from monthly series of data covering the