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Seasonal Adjustment

Acronym: 
SA
Seasonal adjustment is an important step of the official statistics business architecture and harmonisation of practices has proved to be key element of quality of the output.

Seasonal adjustment is an important step of the official statistics business architecture and harmonisation of practices has proved to be key element of quality of the output. In this spirit, since the 90s, Eurostat has been playing a role in the promotion, development and maintenance of a software solution (Demetra family) freely available for seasonal adjustment in line with established best practices.

In 2008, ESS (European Statistical System) guidelines on SA have been endorsed by the CMFB and the SPC as a framework for seasonal adjustment. ESS guidelines cover all the key steps of the seasonal and calendar adjustment process and represent an important step towards the harmonisation of seasonal and calendar adjustment practices within the ESS and in Eurostat.

The SA Expert Group (the Eurostat-ECB high level group of experts from NSIs and NCBs which has produced the ESS Guidelines for seasonal adjustment) is promoting the development of a flexible software solution for SA to be used within the ESS. The group has drawn its attention on the object oriented technologies used by the R&D Unit of the Department of Statistics of the National Bank of Belgium to develop a series of prototype tools for SA. This has been considered as an adequate framework for the cooperative development of a new generation of sustainable SA tools, enabling the implementation of the ESS guidelines.

JDemetra+ is a family of modules on seasonal adjustment, which are based on the two leading algorithms in that domain (TRAMO&SEATS@ / X-12-ARIMA). TRAMO&SEATS@ (TRAMO \"Time series Regression with ARIMA noise, Missing values and Outliers\", and SEATS, \"Signal Extraction in ARIMA Time Series\", developed by Agustín Maravall and Victor Gómez) and X-12-ARIMA (developed by David Findley and Brian Monsell) are two different methods to seasonally adjust a time series. Both methods can be divided into two main parts: a pre-adjustment step, which removes the \"deterministic\" component of the series by means of a regression model with Arima noises and the decomposition part itself. The two methods use a very similar approach in the first part of the processing but they differ completely in the decomposition part. Their comparison is often difficult, even for the modelling step. More especially, their diagnostics focus on different aspects and their outputs take completely different forms.

JDEMETRA+

by Eurostat and National Bank of Belgium

In case of any problems or questions, please contact the ESS Seasonal Adjustment helpdesk via

http://ec.europa.eu/eurostat/cros/content/ess-seasonal-adjustment-helpdesk

For info about the next ESTP course on DEMETRA+ and JDEMETRA+ for beginners and advanced users that will be held at Eurostat please consult here

Since the 2 of February 2015, users interested in performing seasonal adjustement according to the ESS guidelines are encouraged to use JDEMETRA+.

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