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Well, as the output shows there is only one observation (and this is
what you ask for). You cannot estimate a standard error from one
observation.

To be more precise, since the within-imputation variance cannot be
calculated (because there is only one observation) and therefore
returns missing, the total variance is also missing. This follows from
the simple fact that T = W + (1+1/M)B, where T is the total variance,
W is the mean of the within imputation variance, M is the number of
imputations and B is the between-imputation variance.

If you (for whatever reasons) are interested in the between-imputation
variance I suggest merely using -summarize- or the like, as -mi- will
probably not help here.

Best
Daniel

-- 
I have multiply-imputed data: the "SWIID" data, downloaded from
http://myweb.uiowa.edu/fsolt/swiid/swiid.html. The data consist of
country-year observations (173 countries, annually 1960 onwards). For
each observation, there are 100 multiply-imputed estimates of
"gini_net" (Gini coefficient of income inequality).

[...]

I would like to derive MI estimates of gini_net for a particular year,
say Denmark in 1989.
[...]

The "Std. Err." estimate is missing -- why?

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