The data are disseminated annually in a non-seasonally-adjusted format
Time-series data are very useful for economists, policy & decision maker and time-series analysts to identify the important features of economic series such as direction, turning point and consistency between other economic indicator. Sometimes this feature is difficult to observe because of seasonal movements. Thus,if the seasonal effect can be removed, the behaviour of the series would be better viewed. The estimation and removal of the seasonal effects is called seasonal adjustment.
Seasonal adjustment is a process to identify and to remove the regular within-a-year seasonal pattern, which may also include the influences of moving holidays and working/trading days effect in each period. The ultimate objective of the process is to highlight the underlying trends and shot-term movements in the series.
In Malaysia,most of the time series data are affected by seasonally effects. Hence, to eliminate the seasonal effect as well as to seasonally adjust the Malaysia economic time series data, a standard seasonal adjustment package, X-12 ARIMA wasused by Department of Statistics, Malaysia.
Malaysia economic time series data are often affected by major religious festivals such as Eid-ul Fitr of the Muslims, Chinese New Year of the Chinese and Deepavali of the Indians. These festivals' dates are fixed according to the lunar year but vary according to the Gregorian calendar. Therefore, to estimate and remove moving holiday effect from time-series data, a procedure wasdeveloped, namely Seasonal Adjustment for Malaysia (SEAM).
The SEAM method is used to remove seasonal effect for Malaysia's merchandise external trade data. The seasonal adjustment is carried out on monthly total export and total imports. The seasonally adjusted series data for the preceding three years are revised each year when the figures for complete 12 months become available.