I felt like doing something quantitative, so this week we look at seasonal adjustment factors. Everybody always talks about SAAR, and you probably know that it stands for “seasonally adjusted annual rate,” but what does this really mean?
Well, suppose it’s March 2017, and you are wondering what total sales will be for the year. The industry sold 1.55 million vehicles that month so, if you multiply by twelve months, you might estimate 18.6 million for the year.
You would be wrong, though, because March is always a strong month. Here are the estimates produced by the simple “times twelve” method, relative to the actual total for 2017, which was 17.2 million.
Using data from Fred for the five years 2013 through 2017, and converting everything to a percentage, you can see how March always overestimates the year’s results. Each year’s dots are a different color, though it doesn’t really matter which is which.
Some months are highly variable, like September. Not a good gauge of anything. Remember to distrust any SAAR figures published in September. April, oddly, is a tight group and bang on the annual rate. April 2018 sales were 1.4 million, so a good guess for the year is 16.8 million.
Taking an average across the five years, we find that March, May, August, and December each overshoot the annual rate by roughly 10%. Finally, we convert these percentages into monthly adjustment factors.
Instead of multiplying last month’s sales by 12, multiply by the monthly factor to predict the year’s total. Of course, we have more data than just a single month. We can also look at cumulative sales since January. For example, do a quarter of the year’s sales occur in the first quarter?
No. It takes a while to make up for the weak January and February, and then the actual historical cumulative pace slowly comes into alignment with the idealized linear cumulative pace. I made that chart, too, but it’s not pretty. That’s enough quantitative stuff for this week.
Virag Consulting 