Seasonal adjustment

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Seasonal adjustment is a statistical method for time series analysis.

The investigation of economic time series is problematic because the data of a time series are influenced by seasonal fluctuations. This component of the time series is known as the seasonal component S_t. It influences also the real trend. Actually the purpose of the time series is describing this trend. Therefore the statistical science has developed the method of seasonal adjustment to remove the seasonal fluctuations from the time series. The seasonal adjustment identifies the seasonal component S_t and removes it from the time series. The time series is then free of that interfering component. The statistical science has developed several procedures of seasonal adjustment. Important for these procedures is the decomposing of time series.

One famous example is the rate of unemployment which is also presented by a time series. Particularly this rate depends on seasonal influences. This is why it is important to free the unemployment rate of it's seasonal component. As soon as the seasonal influence is removed from this time series the real trend of the unemployment rate is visible. Seasonal adjustment is mostly used in the official statistics implemented by statistical software.

For example the Federal Statistical Office of Germany has developed the application software BV4.1 for decomposing and seasonally adjustment which bases on the statistical method berlin procedure.