Seasonal adjustment is a statistical method for removing the seasonal component of a time series that is used when analyzing non-seasonal trends. It is normal to report seasonally adjusted data for unemployment rates to reveal the underlying trends in labor markets. [1]
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The investigation of many economic time series becomes problematic due to seasonal fluctuations. Series are made up of four components:
Unlike the trend and cyclical components, seasonal components, theoretically, happen with similar magnitude during the same time period each year. The seasonal component of a series are often considered to be uninteresting in their own right and to cause the interpretation of a series to be ambiguous. By removing the seasonal component, it is easier to focus on other components.[2]
Different statistical research groups have developed different methods of seasonal adjustment e.g. X-12-ARIMA developed by the United States Census Bureau; TRAMO/SEATS developed by the Bank of Spain; STAMP developed by a group led by S. J. Koopman. Each group provides software supporting their methods and some versions are also included as part of larger products, some are commercially available e.g. SAS includes X-12-ARIMA, Oxmetrics includes STAMP. A recent move by public organisations to harmonise seasonal adjustment practices has resulted in the developement of Demetra+, developed by Eurostat and National Bank of Belgium which currently includes both X-12-ARIMA and TRAMO/SEATS.
One famous example is the rate of unemployment which is also presented by a time series. This rate depends particularly on seasonal influences, which is why it is important to free the unemployment rate of its 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 like Demetra+.
When seasonal adjustment is not done with monthly data, year-on-year changes are utilised in an attempt to avoid contamination with seasonality.
Due the various Seasonal Adjustment practices by different institutions, a group was created by Eurostat and the European Central Bank to promote standard processes. In 2009 a small group composed of experts from European Union Statistical Institions and Central Banks produced the ESS Guidelines on Seasonal Adjustment which is being implemented in all the European Union statistical institutions. It is also being adopted voluntarily by other public statistical institutions outside the European Union.