Glossary:Seasonal adjustment

From Statistics Explained

Seasonal adjustment (or the adjustment of seasonal changes) is a statistical method for removing the effects of recurring seasonal influences which have been observed in the past from an economic time series, thus showing non-seasonal trends more clearly.

The level and direction of the seasonal effects depend on several factors such as the economic activity (e.g. the turnover of hotels typically increases during holidays, while the industrial production index develops more weakly during the summer). Seasonal effects vary between economies and countries (e.g. depending on which industries are particularly important in the economic structure) and between indicators.

Seasonal effects are one of the four main components that determine the development of economic indicators (apart from the general trend, cyclical effects and irregular component) and seasonal adjustment are a central element of time series analysis.

Within the framework of short-term statistics, European Union Member States are encouraged to send seasonally adjusted data and trend-cycle indices. If they do not, Eurostat calculates the seasonal adjustment using the methods TRAMO (time-series regression with ARIMA noise, missing observations, and outliers) and SEATS (signal extraction in ARIMA time-series), jointly called TRAMO/SEATS. Eurostat aggregates Member States data to produce geographical aggregates, for example, for the EU and the euro area.

Statistically, seasonal adjustment takes place after a time series has already been cleared of calendar effects by way of working-day adjustment.

Related methods

• Working-day adjustment
• Time series analysis