Seasonal Adjustment of Daily Time Series

Ollech Daniel ()
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Ollech Daniel: Statistics Department, Deutsche Bundesbank, Wilhelm-Epstein-Strasse 14, 60431Frankfurt am Main, Germany

Journal of Time Series Econometrics, 2021, vol. 13, issue 2, 235-264

Abstract: 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 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 a set of daily time series with different seasonal characteristics as well as simulated data. The developed procedure closes a gap by facilitating the seasonal and calendar adjustment of daily time series.

Keywords: daily data; multiple seasonality; STL; ARIMA (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1515/jtse-2020-0028

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