The May release came out earlier this week and was a real whopper. It was quite high and well outside the 95% confidence interval of the forecast from last month. We need another month, or months, of data to determine the impacts of the tax increase though. This number could be high in anticipation of the higher rate, or it could be pent up demand shifted to March due to bad weather in January or February. Easter also occurred in March this year and, as my forecasting class saw, that increased sales tax collections in Grand Forks in the past so it could be that situation again. It could also be related to tax cuts at the federal level though I am a bit skeptical that it would just start showing up in spending data for March. Like I said though we need to see where it is at over the next few months before determining the longer term trajectory. Here is the updated forecast.
The economic definition of labor force is a bit different from the conventional view. The labor force is employed plus unemployed, who by definition are those without a job but looking for work. I bring this up to avoid any confusion with the variable actually being forecast.
Alright, we got the update from the city and it was not pleasant. Year-to-date collections are down more than 10%, and cities preferred measure (though we do not know why it is preferred) is down 6.87%. The forecast was for $1.35 million in collections and it came in at $1.02 million. So my pessimistic forecast was still too rosy. Based on this the updated forecast for May is revised down to $1.3 million.
Over the past few weeks the conversation about sales tax has been pretty consistent and fairly intense. That is probably as it should be given the overall importance of revenue generation across the state right now. What have I done so far? I think the best thing to date may be the discussion surrounding the rolling twelve month series used by the city. Rather than accuracy it is more about stability. Eleven of twelve months in the series are the same from one month to the next so of course the series is stable. The flaws of this approach can be seen when you look at the recent decline. A good month is totally outweighed by the totality of the previous eleven. It also begs a statistical question: should all these months be given equal weight while in the series and then just disappear? That seems highly suspect.
I testified in front of the state legislature forecast committee at the end of July and gave my feedback on proper process improvement North Dakota could, and should, make. Each of the items I mentioned could be an entire discussion on its own which makes testimony under a time limit a bit of an issue. And then I realized, I have a blog, so I can extend my thoughts as needed. The first point to discuss further is forecast horizon.