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I am trying to estimate a model using first difference GMM estimator with the xtabond2 command and I was trying to understand whether my logic was consistent.

I have a panel of 130 countries and 18 years. My model looks something like this

enter image description here

Where z and q are two interacted variables and X are the other controls.

Given the potential endogeneity of the autoregressive parameter and the z and q variables I am estimating this via Roodman (2009) xtabond2 command, but I am not sure if I am instrumenting properly my interacted variable.

the code looks something like this. Please do note that in the STATA sintax I also add year fixed effects.

xtabond2 y l.y z##q x i.Year, ///
gmm(y l.y z#q q z x, lag(2 .) collapse) iv(i.Year) noleveleq small noconstant robust

What I am not sure about is how I should instrument my interacted term. Am I correct to think that I should also instrument - gmm() - the interacted (z#q) term? the idea is that z#q might be endogenous to y, hence I think I need separate instrument for it.

Moreover when I use the # and ## operator in xtabond2 STATA issues an error message stating:

factor variables may not contain noninteger values

So I am not sure how to go about this problem: do I need to create a separate variable with the interaction and include that separately or there is another way of going about this?

I thank you in advance for your reply

Best

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migrated from stackoverflow.com Oct 10 at 13:08

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