Three distinct strands can be identified in the literature on seasonality. Economists have long been interested in removing high-frequency "noise" from individual economic time series, or "deseasonalizing the data" in common parlance. The second strand, on which an extensive technical literature...

We consider a dynamic, stochastic equilibrium business cycle model which is augmented to reflect seasonal shifts in preferences, technology, and government purchases. Our estimated parameterization implies implausibly large seasonal variation in the state of technology: rising at an annual rate...

A discussion of how new financial instruments have made accurate seasonal adjustment of monetary data more difficult since 1980.

Empirical tests of the production-smoothing hypothesis have yielded mixed results. In this paper, Donald Allen looks for and finds evidence of seasonal production smoothing in 15 out of 25 manufacturing series and eight out of 10 retail series, using detrended seasonally unadjusted data. The...

An examination of whether one should seasonally adjust data before developing multivariate time series models to provide forecasts.

In aggregate unadjusted data, measured Solow residuals exhibit large seasonal variations. Total Factor Productivity grows rapidly in the fourth quarter at an annual rate of 16 percent and regresses sharply in the first quarter at an annual rate of ?24 percent. This paper considers two potential...

Separating cyclical movement from trend growth at seasonal and business cycle frequencies is important to macroeconomic research. At business cycle frequencies, time trends, first differences and the more recent Hodrick-Prescott (HP) filter are used to separate trends from cycles. At seasonal...

Empirical tests of the production-smoothing hypothesis have yielded mixed results. In this paper, Donald Allen looks for, and finds evidence of, seasonal production smoothing in 15 out of 25 manufacturing series and 8 out of 10 retail series, using detrended seasonally unadjusted data. The...