With the debt ceiling issue shelved (temporarily, I mean three months is no time at all) most eyes turn towards tax policy now. There are enough games played regarding language right now, “Tax reform” v. “Tax relief” v. “Tax cuts”, that it would seem we are in for an extended debate, or a really long argument. With leadership apparently content to draft plans outside of the committee process there seems to be little chance to quell discontent from within their own party.
A caller to my last radio appearance did not understand my issue with the North Dakota Legacy. For readers unfamiliar, this fund takes thirty percent of collections from oil and gas taxes and has some limitations on its use as far as spending purposes, such as no more than 15 percent of principal expended during a biennium and so on.
Paul Ryan is pressing hard for tax changes to be permanent rather than temporary (see a representative article here). From a traditional economic perspective he is probably right to do so if he wants policy to have maximum impact on the economy, regardless of your preferred performance metric. There exists no shortage of empirical research on this topic and I include a link here to a research note that seems typical (and more importantly is not paywalled).
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.