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Hello,

I can use your help!

I estimate the following model, with GMM (dynamic panel data)
yit = c + xi + xit-1 + yit-1, like in Arrelano and Bond (1991).

Time period: 1998-2007, yit-1 because of autoregression.

xi leads to problems:

1. When I give xi the same value for each year the error ´near singular matrix´ occurs.
2. When I give xi only an value in one year (the other years ´NA´) the error ´insufficient number of observations´

Is there an other way of structurering my xi-data? Or is there a function that ´tell´ the model xi is stable during the period?

Thanks a lot!

For 2, can you turn NAs to zeros instead? I had the same problem a while ago with my panel and the fix was:
Not sure it would help you much but give it a try and see if it works.

Putting in Zeros rather than NAs will not work.

Your first approach should work. If it isn't, you've probably created a singular matrix somewhere by mistake by including co-linear regressors.

There's a deeper issue here. The DPD transformations (first-difference, orthogonal deviations) will make any non-varying variable identically equal to zero. As in the standard fixed effects estimator, you cannot estimate the coefficients on these variables using this estimator.

Thanks for your reactions!!

So i'm in deep...
Nice.

Do you, or someone else, have a suggestion using what kind of model instead?

Any suggestion help!!!

Thanks, again!

If you have fixed effects, drop the X variables that are fixed within a cross-section.