Seasonal adjustment is a statistical technique used to remove the effects of seasonal variations in time series data. Many economic and financial indicators, such as employment rates, retail sales, and production figures, often exhibit regular patterns that recur in a predictable manner at specific times of the year, such as holidays or harvest seasons. These seasonal variations can distort the underlying trends in the data. By applying seasonal adjustment, analysts aim to produce a clearer view of the underlying trends by isolating and removing these predictable seasonal influences.
New to topics? Read the docs here!