You should search the Statalist archives. There have many
posts in the last few months on bootstrapping
time series. The consensus seems to be that
naive bootstrapping with time series is a very
bad idea, for precisely the reason you mention,
dependence structure. Special methods have been proposed
to bootstrap time series, but none appears to
have been implemented in Stata. On the other hand,
bootstrapping in terms of selecting or not selecting
panels may not be so crazy, but others may well
comment in more detail and with more authority.
Nick
[email protected]
Carmine Ornaghi
>
> I have an unbalanced panel data of firms (with
> observations between 3 and 10 periods). I use this
> data to estimate a production function using dynamic
> GMM (Arellano and Bond).
>
> Now I want to do some sort of 'bootstrapping. In
> particular, I have the following doubts:
> 1) I think I need to preserve the same time structure.
> What I mean is that I want the random sample to have
> the same number of firms with only 3 observations, 4
> observations, ... 10 observations that the original
> dataset has. In this way they are UNBALANCED in the
> same way
> 2) I have done some experiment with the STATA command
> bsample but I have a problem. The Sargan Test of
> overidentified restriction is easily passed with the
> original dataset but never with all the random samples
> created. Do you know why and how I can give a higher
> probability of entering into the sample to those
> observation that minimize the Sargan Test.
>
> Thanks a lot,
>
> Carmine
>
>
>
>
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