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Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
Deutsche Bundesbank Discussion Paper No. 24/2023
Verlag: 
Deutsche Bundesbank, Frankfurt a. M.
Zusammenfassung: 
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. 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 data on economic developments. Such infra-monthly data often display seasonal behavior that calls for adjustment. For that reason, JDemetra+, the official software for harmonized seasonal adjustment of monthly and quarterly data in the European Statistical System and the European System of Central Banks, has been augmented recently with a regARIMA-esque pretreatment model and extended versions of the ARIMA model-based, STL and X-11 seasonal adjustment approaches that are tailored to the specifics of infra-monthly data and accessible through an ecosystem of R packages. This ecosystem also provides easy access to structural time series modeling. We give a comprehensive overview of the packages' current developmental stage and illustrate selected capabilities, including code snippets, using daily births in France, hourly electricity consumption in Germany, and weekly initial claims for unemployment insurance in the United States.
Schlagwörter: 
extended Airline model
high-frequency data
official statistics
signalextraction
unobserved-components decomposition
JEL: 
C01
C02
C14
C18
C22
C40
C50
ISBN: 
978-3-95729-955-0
Dokumentart: 
Working Paper
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