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.
For the last few days I focused on state level tax data. The release of a new forecast and the general state of the forecast process promises many more posts to come on this topic. I thought for today I would turn toward a more local number. Grand Forks had its largest month for sales tax collections in its recorded history. What does this look like?
Continue reading Some local flavor, Grand Forks Sales Tax Data
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.
This is something that JT and I talk about quite often relating sports and economics. The public subsidies for sporting arenas are difficult to make up in the best of circumstances, and are equally (if not more difficult) to quantify. Our sports facility management class actually attempts to address some of these issues.
Continue reading The Economist | Subsidising professional sports: If you fund it, they may come