1. Background
Seasonal adjustment is the estimation and removal of effects on a time
series that are a result of the time of year, such as the calendar month
or Easter. Accounting for these effects makes it possible to analyse the
underlying trend in the data.
A common example is retail sales, which peak as a result of the
Christmas shopping period. However, this rapid increase in sales does
not indicate a sustained upwards trend. Seasonal adjustment removes the
effect estimated to be as a result only of Christmas, leaving the actual
story in the data to be assessed.
If a data series is seasonal but is not adjusted to account for this, it
is not valid to compare the current time period to the previous one.
The purpose of this…