Currently, the methods used by producers of official statistics do not facilitate the seasonal and calendar adjustment of daily time series, even though an increasing number of series with daily observations are available. The aim of this paper is the development of a procedure to estimate and adjust for periodically recurring systematic effects and the influence of moving holidays in time series with daily observations. To this end, an iterative STL based seasonal adjustment routine is combined with a RegARIMA model for the estimation of calendar and outlier effects. The procedure is illustrated and validated using the currency in circulation in Germany and a set of simulated time series. A comparison with established methods used for the adjustment of monthly data shows that the procedures estimate similar seasonally adjusted series. Thus, the developed procedure closes a gap by facilitating the seasonal and calendar adjustment of daily time series.
Seasonal adjustment STL Daily time series Seasonality