Here is a narrow replication of Table 8.1, 8.2 as in Baltagi (2021) (see printed coefs below in comments, generated with xtabond2 lnc L.(lnc) lnrp lnrpn lnrdi dum3 dum8 dum10-dum29, gmm(L.(lnc), collapse) iv(lnrp lnrpn lndrdi dum3 dum8 dum10-29) noleveleq robust nomata twostep
with pgmm from R package plm.
Code below does not incorporate the IV instruments, ...
The key to obtain similar results is to notice this part in stata code dum3-dum29 in command:
xtset state year
xtabond lnc lnrp lnrpn lnrdi dum3-dum29, lag(1) twostep
Hence, we have to model time dummies manually (i.e. use the packege fastDummies).
Baltagi in Stata drops not only two first periods of time dummies, but also the last one (I've ...
I wrote something in R for my own use, based on the quote from Sherman and Cessie (1997) in StatsStudent's answer.
It implements bootstrap replicates on clustered data with clusters of different sizes.
It makes sure that clusters sampled more than once (due to replacement) are treated as distinct clusters within bootstrap samples (especially important in ...
Fit model with interaction first. Since interaction term is not significant, remove interaction term only and fit again. Then look for main effect whether it is significant or not. If it is, keep it and this will be your final model.
Hope it helps.