I think it hardly needs mentioning again, but I guess I will: the legislative process in North Dakota probably makes it even more important that we have some confidence in our revenue forecasts. Our legislators are meeting for three months to determine budgets for the next two years. There is always the possibility of a special session if need arises, but you want that to be the truly exceptional case. Now I am not suggesting that anyone will ever get the numbers spot on, 100% accurate, but we can get closer.
The state released an updated forecast from Moody’s today along with some slides that make little sense (found here). I would go into the details of the forecast but why bother? We have absolutely no insight into the forecast process followed, the assumptions underlying any model relationships, or even a list of variables employed and the time period considered. Seriously, if this were my forecasting class, they would fail.
I continue to think about the tax situation in North Dakota right now, particularly trying to understand what the data are trying to tell us. Obviously I want to avoid a situation of torturing the data until they confess, but that should not stop us from slicing and dicing the data to find something meaningful.
We are getting a new forecast this week for tax revenues in North Dakota. Or so we are told. I’ve written about the problems with these forecasts in the past, but there is a further issue here needing discussion. The simple fact of the matter is a lack of good practice in the overall approach, particularly with how forecast results are disseminated.
I was a guest on the Jay Thomas Show on WDAY radio out of Fargo today. The guest host was Rob Port from the SayAnythingBlog, Forum Communications Op-Ed pages, TV appearances, and probably a bunch of stuff I am forgetting. He might be getting close to the title of “King of All North Dakota Media” at this point. The topic was forecasting. Yes I know. Friday afternoon in the summer and we were talking forecasting. I do not apologize for it, since I am pretty much always thinking about statistical models.