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It is the covariance of the coefficients. It is a little difficult to diagnose without looking at the full specification and data and thinking a lot more than I am doing at present, though I think you are right about overidentification. I will note that in the second (non-singular) parameterization,...

Oh, I just realized that I should add that "supF" doesn't quite describe the test as Bai-Perron use SupF as part of two different test procedures: . The supF we are discussing above is the supF for m vs. 0. . There is a second supF for sequential l+1 vs. l. Note that there are different cr...

Yes, it is the supF statistic. Mostly yes to the second. I actually went and looked at my notes and the code more carefully and need to update my answer somewhat. . First, the results are based on the unpublished tabular results from Bai-Perron 2003 (dated Feb. 2003) which, I am pretty certain were ...

Yes.
We use the value for 10 as that is the best available. So they are really just illustrative at that point. We considered using the Bai-Perron 2003 response surface regressions but there are issues with implementing those as well.

viewtopic.php?f=4&t=19470&p=62455&hilit=principal+components#p62496

Note also for those reading this entire discussion, EViews now offers a variety of data-based methods of selecting the number of components.

Hi T, The White diagonal in GMM panel is generally employed when we assume no correlation between residuals across equations, and no correlation between residuals across observations (even within cross-sections). It is a very strong assumption, but doesn't require independence. So under these assump...

We were able to verify from another workfile. Fix has been applied and patch has been released. Thanks.

The output fields are present in EViews 10

Could you post your workfile.

They didn't show up. Could you try to include again? Or send to support@eviews.com

Sorry. Never saw this one until now. One can look at the summed effect of all of the shocks on the variable in question, which can be decomposed into shocks from each source. The former is the total effect of all of the stochastic components, which can be compared to the effect from the specified st...

I'd like to run, if possible. I can't replicate for a test workfile with the forclen properly set to be after the estimation sample end.
Absent that, if you can tell me the estimation sample and the workfile sample and the forecast length.

Is there any chance you can post the workfile at the point where you try to run this and get the error?

Sorry for the inconvenience. We will take a look.

Thanks for the suggestion. This is a matter of interface only since you can easily use the user-defined shocks in impulse responses to simulate an exogenous variable shock. What exactly would you want to be able to do? How much control over the shocks do you want?