AbstractIncreasing attention has focused in recent years on the use of spectral analytic techniques for the analysis of economic time series data. Sovereign, Nolan and Mandel [26] have recently outlined the basic concepts underlying such analysis and presented examples relating to the management science area including inventory demand, transportation simulation and stock market price behavior. The purpose of this paper is to supplement and extend their tutorial with a discussion of some of the problems involved with the application and interpretation of spectral statistics, emphasizing the problems of stationarity and detrending and data windows. Additionally, the scope of the examples is broadened to include applications in the area of monetary economics.The first part of this paper presents a brief discussion of the objectives of spectral analysis. Since this paper attempts to extend the work of Sovereign, Nolan and Mandel, only a heuristic discussion of spectral techniques of analysis is presented. This is followed by a more detailed description of the problem of stationarity and the effects of detrending upon the interpretation of spectral results. Then we consider the problem of estimating a continuous curve with finite information and the implications of both of these problems by presenting several applied examples in the area of monetary economics. The concluding section of this paper briefly summarizes some additional considerations in harmonic analysis of economic time series data and notes some potential directions for future research.