Seasonally Adjusted Annual Rate (SAAR)
What Does Seasonally Adjusted Annual Rate (SAAR) Mean?
Let us suppose that you have an ice cream factory. Your factory is running on full capacity and making a good profit from the sale of ice cream. Your financial year starts on October 1st and ends on September 30th of each year. From September to March you carry out repairs and expansion work in your factory. There are no sales in this half of the year because it is the winter and old stock is used tomeet the seasonally lowdemand. It is now that you concentrate on expansion to meet the expected increase in demand in the months to come and also develop new products to counter the competition. You used your capital on the expansion and there is nothing left for your working capital requirements. You go to a bank to get a loan to meet these needs. The bank asks you to provide your latest half yearly financial statements. What can you show? Your current half year does not contain any sales because it is the winter season. Do you ask the bank to wait 6 months or do you do something else? This is where Seasonally Adjusted Annual Rate (SAAR) comes to your aid.
It is a rate adjustment used for economic or business data that attempts to remove the data’s seasonal variations. Most data will be affected by the time of the year. This seasonal adjustment of data means that more accurate relative comparisons can be drawn from month to month all year round.
The SAAR is calculated by dividing the unadjusted annual rate for the month by its seasonal factor and creating an adjusted annual rate for the month. These adjustments are more often used when economic data is released to the public. The ice cream industry tends to be very seasonal; demand for ice cream in summer increases and in winter decreases. By using seasonally adjusted sale rates, the sales in the summer can be accurately compared with the sales in the winter. Unlike the many trends and cyclical components, seasonal components occur with similar magnitude during the same time period each year. Seasonal components of a series are often considered to be unimportant 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.
For example, if December's sales are typically 130% of the normal monthly value (based on historical data), then each December's sales would be seasonally adjusted by dividing by 1.3. Similarly, if January's sales are typically only 90% of normal, then each January's sales would be seasonally adjusted by dividing by 0.9. Thus, December's value would be adjusted downward while January's would be adjusted upward, correcting for the anticipated seasonal effect. Depending on how they were estimated from the data, the seasonal indices might remain the same from one year to the next, or they might vary slowly over time.
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