It's both an answer and a question.
It's a question because I was surprised Dr Cox did not include -mvis- as
an option. It's an answer because multiple imputation is a common way of
dealing with missing values. Obviously applying it to a panel data with so
many missing values will itself be a statistical challenge.
Tim
"Nick Cox" <[email protected]>
Sent by: [email protected]
05/09/2005 22:15
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RE: st: RE: Panel Data Problem
Is that a question or an answer?
I'll in turn give an answer that is
really a question.
As one gets into more and more elaborate imputation
of missing data, what then is the status
of any model later fitted to the data?
I am reminded of those stories of naive
students rediscovering the very relationships
used to fill in the gaps in scrappy data by
economists working for international organisations.
Nick
[email protected]
[email protected]
> What about -mvis- for multiple imputation?
Nick Cox
> You have a lot of missing data here.
> If -ipolate- helps little, it seems
> unlikely that any other method will
> help more.
>
> You might get marginal improvements
> by interpolating in log price, then
> exponentiating. That is, a zeroth
> approximation in most economies
> would be that prices are increasing
> multiplicatively.
Mazhar Islam
> > I have a panel data of daily price of a commodity in
> > different locations of a city over 7 -year period.
> > Unfortunately about 40 % data is missing from both
> > right and left (dependent variable) side of the model.
> > How should I go about it? I tried Stata's ipolate
> > command to fill up the missing observations but did
> > not help much. When I ran xtreg with random effect
> > option (re) a number of records are dropped. I want to
> > capture as many panels as I can. Any help is greatly
> > appreciated.
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