THE MODELING AND SEASONAL ADJUSTMENT OF WEEKLY OBSERVATIONS

Several important economic time series an recorded on a particular day every week. Seasonal adjustment of such series is difficult because t he number of weeks varies between 52 and 53 and the position of the re cording day changes from year to year. In addition certain festivals, most notably Easter, take place at different times according to the ye ar. This article presents a solution to problems of this kind by setti ng up a structural time series model that allows the seasonal pattern to evolve over time and enables trend extraction and seasonal adjustme nt to be carried out by means of state-space filtering and smoothing a lgorithms. The method is illustrated with a Bank of England series on the money supply.