I have a panel data with N=17 and T=46. The model has a dynamic specification as it includes a lagged dependent variable. It looks something like the equation below:

Code:
Yit=ayit-1+b1D1it+b2D2it+b3xit+eit

Where y is my dependent variable, x a vector of covariates and Ds are dummy variables.

A dynamic model is usually estimated using the GMM method, however as my N is smaller than my T in this case it is not feasible.
Some papers talk about (1) Running a separate regression for each group and averaging the coe‑cient over groups; (2) Combine the data dening a common slope, allowing for xed or random intercepts and estimating pooled regressions (Mairesse & Griliches 1988); (3) Take the data average over group and estimate the aggregate time series regressions (Pesaran, Pierse & Kumar 1989, Lee, Pesaran & Pierse 1990) and (4) Averaging the data over time and estimating cross section regression on group means (Barro 1991).
I have also gone through some earlier posts, but still lack clarity. My issue is
What method can be used to estimate a dynamic model with small N and large T.
Is xtivreg appropriate in this situation?