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st: xtabond2

From   Viktor Slavtchev <[email protected]>
To   [email protected]
Subject   st: xtabond2
Date   Tue, 18 Dec 2007 14:12:11 +0100

Dear Statalisters,
I also have some questions regarding the proper implementation of -xtabond2-.
The guidance provided by David Roodman is doubtless wonderful peace of work - it is quite straightforward and makes a lot of things clear.
However, there are several questions I could not answer by myself. Thats why I am asking for your help.
I am trying to estimate dynamic panel model like that:
y[i,t] = y[i,t-1] + w[i,t] + v[i] + e[i,t]
where in the notation of the xtabond2-help y = dependent, w = covariate(s) (apropos, there are some theoretical arguments to suspect 'w' endogenous), v = fixed effect, e = residuals.
I am trying to estimate the model in differences (not levels).
xtabond2 ln_y l1.ln_y ln_w, robust noleveleq gmm(l1.ln_y) gmm(ln_w).
I am not very sure that I understood the xtabond2-syntaxes correctly, so the first question is whether this is the right way to estimated the model.
Second, Arelano-Bond test for serial correlation suggests first order autocorrelation, rejects however second order AC.
Hence, I am asking myself whether the first lags are proper instruments or not and whether I should start with deeper lags. For example:
xtabond2 ln_y l1.ln_y ln_w, robust noleveleq gmm(l1.ln_y) gmm(ln_w, lag(2 .)).
Thanks for any help.
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