EViews.com

...in a VAR".

Is there any view to expanding this in the near future? Even EViews.com admits:

"Since VARs frequently require estimation of a large number of parameters, over-parameterization of VAR models is often a problem—with too few observations to estimate the parameters of the model.

One approach for solving this problem is shrinkage... Bayesian VAR (BVAR) methods... are one popular approach for achieving shrinkage.

So it might be useful! I noted from http://forums.eviews.com/viewtopic.php?f=23&p=17062 that in the BVAR add-in, there is no max. number of endogenous variables - the only constraint is actually the size of the input box (which still doesn't actually hold more than 30 variables, depending on how long your variable names are!).

Very best wishes, and thanks as always for your time.

The comment on BVARs is meant to imply that a large number of lags can blow out the number of parameters. Not the number of variables. I'll see if we can increase it though.