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st: Dummy variables for missing values
On Sat, 12 Feb 2005 00:48:28 -0500, Daniel Egan <firstname.lastname@example.org> wrote:
> Hi Quang,
> > My friend has a panel data in the following format:
> > Year Investment
> > 1900 . (Missing value)
> > 1930 .
> > 1960 12
> > 1980 .
> > 1990 28
> > 1991 56
> > 1992 35
> > 1993 45
> > etc.,
> > Could you please tell me how she can use the dummy variables for this
> > exercise (regression)? Also, how she can interprete the coeficients
> > for Investment and the dummy variables?
A better solution to missing data is available with Stata. Do a findit on
mvis. This set of commands imputes multiple datasets, does your regressions
on each of these, and combines them to obtain unbiased estimates and
unbiased standard errors. Imputing the missing values make sense if the
missing values are "missing at random." If this is not the case, then the
assumption can be approximated by including "mechanism" variables, i.e.,
variables that predict patterns of missingness.
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