[Prateek Bedi]

Hi,

I have the following doubts with regard to dynamic panel estimation.

1. As per my understanding, a 'predetermined explanatory variable' is one whose current value is influenced by lag of the error term (effectively, the lag of the dependent variable). Is this understanding correct?

2. For a predetermined variable, when we use 'model(fodev)' option, we can start the lag length from 0 i.e. lag(0 X). However, is it necessary that we start the lag length from 0 only for predetermined variables. Can we start it from 1 or 2 or 3 and so on?

3. Can I just ensure reliability of instruments using overall Sargan-Hansen test without paying too much attention to difference-in-Hansen tests?

4. In some cases, the 2-step weighting matrix Sargan-Hansen validates reliability of instruments but 3-step weighting matrix Sargan-Hansen does not. Can the results be still considered valid?

5. If I mention the lag length criteria for an instrument as lag(0 0), what does it imply? I suppose this is the default setting in iv() style instruments.

6. If AR(2) and overall Sargan-Hansen tests are satisfied but the number of instruments is marginally below the number of groups, can the model be considered reliable?

7. Supposing model results are fine and Sargan-Hansen test also validates reliability of instruments, but AR(2) is not satisfied, what options can be tried to ensure AR(2) is satisfied?

8. I understand that when we specify variables in iv() or gmmiv() with model(level) option, it means that we assuming the concerned variables to be exogenous. However, since this implies a strong assumption that these variables are uncorrelated with any of the omitted variables including fixed effects, I wonder whether we have any exogenous variable in a real setting. This is because there shall always be a possibility of an explanatory variable being correlated with some omitted variable(s). In light of this, should we always avoid considering a variable to be exogenous to be on a safer side?

Thanks in anticipation!

[Sebastian Kripfganz]

Immanuel Feld:

It seems that margins was already working as long as you added the force option when your model includes a lagged dependent variable.

With the new version 2.2.6 that is now available on my website, margins (and marginsplot) should work as expected without the force option.

net install xtdpdgmm, from(http://www.kripfganz.de/stata/) replace

Note however that in models with a lagged dependent variable, all marginal effects are calculated treating the lagged dependent variable as fixed. This is appropriate for so-called "short-run effects". For "long-run effects", use the nlcom command (but you need to enter the relevant formula by hand).

Disclaimer: I have not thoroughly checked that margins works correctly under all possible circumstances. Use at your own risk! If you find anything that does not seem right, please let me know.

[Sebastian Kripfganz]

Dear Sebastian,

last year in May you wrote that margins was not supported after xtdpdgmm at that time. Is it supported now?

Best,
Immanuel

Unfortunately, it is still not supported as I did not yet find the time to look into it. It is possible that the support for margins might be straightforward to implement but I want to make sure that I get it right. The xtdpdgmm project is already quite large such that I need to be extra careful with any changes to avoid unintended consequences.

Just for myself, I leave a bookmark to another useful thread on the margins support for community-contributed commands:
https://www.statalist.org/forums/for...ritten-command

[Sebastian Kripfganz]

So, as a rule of thumb, the null hypotheses regarding all sets of instruments in 'Excluding' column and 'Difference' column should be not get rejected i.e. the p-values should ideally be greater than 0.10, Am I right?

Ideally, yes. Kiviet (2020) even promotes the idea that the p-values should be much larger than 0.10 for practical purposes.

[Prateek Bedi]

Ok, Prof. Kripfganz. So, as a rule of thumb, the null hypotheses regarding all sets of instruments in 'Excluding' column and 'Difference' column should be not get rejected i.e. the p-values should ideally be greater than 0.10, Am I right?