The Modelling and Seasonal Adjustment of Weekly Observations - (Now published in 'Journal of Business and Economic Statistics', 15 (1997), pp.354-368.)

Andrew Harvey, Siem Jan Koopman and Marco Riani

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: A number of important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recording day changes from year to year. In addtion certain festivals, most notably Easter, take place at different times according to the year. This paper presents a general solution to problems of this kind by setting up a structural time series model which allows the seasonal pattern to evolve over time and enables trend extraction and seasonal adjustment to be carried out by means of state space filtering and smoothing algorithms. The method is illustrated with a Bank of England series on the money supply.

Keywords: Structural time series model; seasonal adjustment; trend extraction; filtering and smoothin algorithms; money supply. (search for similar items in EconPapers)
Date: 1995-08
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:284

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