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...

Studies have documented that average stock returns for small, low-stock-price firms are higher in January than for the rest of the year. Two explanations have received a great deal of attention: the tax-loss selling hypothesis and the gamesmanship hypothesis. This paper documents that...

A reevaluation of the evidence of seasonality in prices, finding that seasonal price movements have become more prominent in the relatively stable inflation environment that has prevailed since 1982, and that the amount of seasonality differs greatly by item, making it difficult to generalize...

Optimal linear regulator methods are used to represent a class of models of endogenous equilibrium seasonality that has so far received little attention. Seasonal structure is built into these models in either of two equivalent ways: periodically varying the coefficient matrices of a formerly...

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...

Seasonal adjustment usually relies on statistical models of seasonality that treat seasonal fluctuations as noise corrupting the `true' data. But seasonality in economic series often stems from economic behavior such as Christmas-time spending. Such economic seasonality invalidates the...

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