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Abstract:
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Infra-monthly economic time series have become increasingly popular in official statistics in recent years. This evolution has been largely fostered by official statistics’ digital transformation during the last decade, and the COVID-19 pandemic outbreak in 2020 has added fuel to the fire as many data users immediately asked for timely weekly and even daily indicators of economic developments. Many of those indicators display seasonal behavior and, thus, are in need for seasonal adjustment. JDemetra+, the official software for seasonal adjustment of monthly and quarterly data in the European Statistical System and the European System of Central Banks, has been augmented recently with an Airline-type pretreatment model and extended versions of the ARIMA model-based, STL and X-11 seasonal adjustment approaches that are applicable to infra-monthly time series and accessible through the {rjd3highfreq} R package. We provide a comprehensive overview of the implemented methods, including code snippets, and illustrate their capabilities using daily births in France and electricity consumption in Germany recorded at 15-minute intervals.
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