Seasonally adjusted figures refer to a method in economics and statistics that aims to remove the influence of seasonal fluctuations from data. These figures are commonly used to analyze trends and patterns in economic indicators, such as employment, inflation, or GDP, by taking into account regular seasonal patterns that occur at certain times of the year.
The purpose of the seasonally adjusted figures is to identify the underlying movement or trend within the data, while accounting for any temporary and predictable changes that occur over different seasons. Seasonal fluctuations often occur due to factors like weather conditions, holidays, school schedules, or sales periods, which can have a significant impact on certain industries or economic indicators.
To obtain seasonally adjusted figures, statistical techniques are applied to eliminate the seasonal component from the original data, usually by using various smoothing methods or time series analysis. By doing so, the variations caused by seasonality are removed, enabling a clearer analysis of the data's long-term patterns, trends, or cycles.
Seasonally adjusted figures provide a more accurate representation of the underlying economic conditions, as they enable comparisons across different months or quarters without being distorted by the regular seasonal variations. These adjusted figures are often used by policymakers, economists, businesses, and investors to make informed decisions, forecast future trends, or monitor the overall health of an economy.
