I did a series of posts along these lines ages ago, but as an overall summary, the following post from David Giles covers much the same ground and then some (excerpt):
There are several reasons why we estimate regression models, one of them being to generate forecasts of the dependent variable. I'm certainly not saying that this is the most important or the most interesting use of such models. Personally, I don't think this is the case.
So, why is this post about forecasting? Well, a few comments and questions that I've had from readers of this blog suggest to me that not all students of econometrics are completely clear about certain issues when it comes to using regression models for forecasting.
Let's see if we can clarify some terms that are used in this context, and in the process clear up any misunderstandings…
There are a couple of concepts in this post that I never got around to covering (cointegration and order of integration), and I prefer as a rule to use lags anyway, but this is a pretty good primer on the mechanics of forecasting.