Seeing how that data for those years has yet to be recorded, he cannot possibly compare the forecasted values to the actual values to test the accuracy.
Of course he can. His data comes from a model, so he can produce data for any 'years' he wants to.
It's entirely relevant to the accuracy of the model. You cannot use fictional data to try to understand the causes and variation in a real world variable.
The article doesn't address understanding causes and variation of a real world variable, it address the ability of a model to track the underlying model it was built from. Whether the underlying model was reality or just another model, if anything, ought to make the task easier.
I called out his "calibration" as bullshit.
Your work, as you've described it, is no different than what the article claims does not work.
Care to tell the class what you do for a living and your educational background?
Masters in Computer Science--not that my credentials are relevant to the strength or weakness of my argument.
We've already established that I have reason (both educationally and career-wise) to know WTF I'm talking about
First, your education and career may indicate that you ought to know what you're talking about, but the arguments you put forth show that you don't.
Second, this is perhaps the crux of matter addressed by the article. You, and I assume many other economists, think you know what you're doing, but you don't. You're practicing cargo cult science--going through the motions of statistical analysis without understanding what you're doing or why, and consequently producing garbage models that don't predict anything other than the 10 years of data you tested against.