DSGEs don't define priors!

I cannot think of a more difficult problem than forcing economic data to confirm economic models. Most economists have effecting ceded this and given into some effective mantle of bayesianism.

Hence the rise of DSGEs and their use as a means of forming a prior to a Bayesian VAR model.

Rather than to use MLE which is known to be unwieldy when fitting nonlinearly constrained VARs, economists now use the underlying model the DSGE to define a prior. (And so do the finance types, eg Ang-Piazzessi and the largely useless machinery-in the context of data fitting- of affine models for no arbitrage restrictions). 

Now let us be clear a DSGE can in no way define a prior. As an equation it can at best define a manifold in parameter space. This can be the max likelihood surface or the effective mode of this distribution but it cannot tell you the metric or any more about the actual prior distribution.

So how do economists even begin to think of using DSGEs to form priors for their VARs?

Go figure.

I will post links to books/papers on topic later on. I am certain that in no way can it truly make complete sense to anyone. (unless we can determine in more detail--flesh out---the notion of informative and noninformative "directions" in parameter spaces....even this will be challenging in that it will be easier to have informative/noninformative subspaces rather than manifolds!).