Hi everyone,

I'm using GMM to evaluate a structural framework. To explore heterogeneity in the results, I ran the model on different (disjoint) subsets of my original sample. Now as I understand it, commands such as suest are not suitable for post estimation using GMM, so I cannot test coefficients from two distinct GMM estimations (or can I?).

So to be able to test the coefficients I figured the easiest way would be to include interaction terms. Luckily, after solving the structural model as far as possible, it only consists of one equation, so the easiest way for me to include interaction terms would be to interact my only equation with the heterogeneity variable (which takes on three values corresponding to the terciles of its distribution), something like

Code:
gmm (i.tercile#(equation1)), instruments(XXX)


However, this returns an error message: "could not evaluate equation 1", which from my experience really does not say anything.

Here is the minimal example to replicate the error message:

Code:
gmm (residual - {FB}*saturday_HT_after), instruments(saturday_HT_after, noconstant) vce(cluster vid)
gmm (i.baseline#(residual - {FB}*saturday_HT_after)), instruments(saturday_HT_after, noconstant) vce(cluster vid)
The first command runs through, the second does not, but returns the error message mentioned above. Simply using
Code:
 gmm (baseline#(residual- {FB}*saturday_HT_after)), instruments(saturday_HT_after, noconstant) vce(cluster vid)
does not work either.

Can anyone tell me if I'm overlooking something obvious or if there is an easier way to test coefficients from split sample GMM analysis?

Thanks!