Sales tax data is a continuing theme for me these days and so I thought we could look at any seasonal patterns in the data. I am going to hold off on the formal statistical tests for right now and we will go with the graphical approach. If there is seasonality in the data the graph should show common movements in the lines for different years. For example, if June is always a slow month for retail sales the collections should drop for most June observations compared to the May observations. I generate this for 2001 to 2017.
It is a lovely mess. What I pull away from this is that for many years the sales tax collections increase throughout the year though that is not at all universal. Also, over time the sales tax collections were going up, though that reversed lately as well. All in all, a fairly cluttered graph that does not really give much insight into any seasonal patterns. Let’s try polar coordinates.
A little bit different but a few things become clearer here. The August to December time frame appears to be the highest collections time of the year. Not a huge surprise with the number of holidays and special shopping days occurring in that time frame but it does give insights into when to start expecting the higher sales volumes as a retailer.
Anyone want to hazard a guess why March of 2013 is so high compared to other years? I know the answer, I am just curious if readers do.