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.
A closer look at recent sales tax data seems a logical follow-up to the long run view from last time. There are two things to note from this graph: 1) the negative trend is still clearly evident, and 2) the reduction in volatility from the twelve month rolling is clear.
The January sales tax collections data came out recently and I want to take a longer view of the data here. This typically means messier graphs because the time scale gets compressed. I will put up a post with a shorter timeline tomorrow. Why the longer timeline? I think it is necessary if we are going to try and interpret or understand the numbers we are currently seeing.
One of the most interesting stories of the aftermath of the tax legislation is the race to pay property taxes this year in many states so they still qualify for deductions. Clearly this is a big issue for those living in high tax states. The images are amazing when you think about it. When was the last time you saw a line of people to pay their taxes well before the due date?
The state of debate in the country regarding taxes being what it is I thought I would make a few posts on the topic over the next few days. There are many issues with the legislation being discussed (intentionally not using the word debated right now). The issues and implications for North Dakota will need to wait for another post, but it will be forthcoming.