By using the Seasonal adjustment analysis in Macrobond you can remove the seasonal pattern from a time series. The algorithm used is not as advanced as for instance X-11, but is much faster and easier to use and works well in many cases. The method works by calculating a seasonal factor for each time period and then adjusting all the values in the time series with these factors. The number of factors is equal to the number of observations in a year based on the frequency, monthly factors, however, will be used for all series with higher frequency than a month. There are two variations: additive and multiplicative. The additive method works best if the series is relatively constant over time. The multiplicative method works better if the seasonal factor is proportional to the level of the series, which is often the case when the series shows an exponential pattern.

The following steps are done in order to calculate the factors and the adjusted series:

1. The trend is removed by subtracting or dividing the series with a long moving average. The number of observations in the moving average is the number of observations in a year based on the frequency.
2. Seasonal factors are found by calculating the mean for each time period within the estimation range. The factors are then normalized so that the sum is 0, for the additive method, or 1, for the multiplicative method.
3. The adjusted time series is then created by subtracting or dividing by the factors.

The analysis will produce the adjusted series as a time series and the seasonal factors as a category series.