Hello Everyone,

I am working on a problem in which I am assessing the risk of credit default in relation to different policies in different sectors of a nation. I gathered and created data monthly from 2000 to 2020, thus T=240 in my example, and there are only eleven sectors, so N=11. All my independent variables are exogenous. And I have found an autocorrelation in my dependent variable, particularly with AR (1). With such dynamic panel data, I was more tempted to employ a dynamic approach such as GMM Estimator (xtabond2). Still, with more investigation, I discovered that this method is inconsistent with such a big T and is more often utilized in scenarios when N>T. I'd want some advice on how to approach such situations. I even found some great advice from this helpful community, like,

xtregar and xtscc with fixed effect model.

My question is can I add a lag variable of my dependent variable in the last two methods? If yes, how is it valid?

And my last inquiry will be other than monthly can I utilize dynamic techniques such as GMM Estimator (xtabond2) if I desire to solve my issue on an annual basis, where T=20 and N=11? As T will be much smaller, I have my doubts as it does not meet the N>T criterion. Please point me on the right path.