Seasonal adjustment

Welcome! We are here to help you with your understanding of seasonal adjustment and how it works in practice. We've got information ranging from seasonal adjustment methods, to improving your analysis by the use of trend estimates, and to a list of solid quality references that cover the theory. We've even got a blog which is updated regularly to talk about relevant issues.

What is seasonal adjustment?

Seasonal adjustment is an important statistical method with three main purposes:

  1. Aid in short term forecasting

  2. Allow comparability in the time series from month to month

  3. Compare movements in different series once individual seasonality has been removed
The aim of seasonal adjustment is to estimate and remove the systematic calendar related component of a time series. By using appropriate seasonal adjustment methods the seasonally adjusted estimates help users and analysts perform useful and relevant analysis and forecasting.

In practice, seasonal adjustment is a widely applied procedure and there are many different statistical methods to do this. Typically, national statistics institutes will calculate seasonally adjusted estimates on a regular basis and publish these estimates as output for key social and economic indicators.

The links below provide more detail on seasonal adjustment issues faced by international and national statistics institutes: