You have first to consider the possibility
that your data do _not_ lend themselves
to linear interpolation. If, for example,
investment varies irregularly, as seems
plausible given that is a response to both
macroeconomic and microeconomic factors, then
gaps in a very peaky time series will be difficult to
interpolate accurately.
That said, so long as all your data are
positive, interpolating on the logarithms and
exponentiating the result is a sure
mathematical way of avoiding negative predictions.
Real economists will be able to add more. My
economics education stopped with A-level (British
high school leaving qualification) Economics
in 1969.
Nick
[email protected]
joe J.
> I have a panel (unbalanced) dataset of manufacturing plants
> for several
> years. Investment series is missing for a lot of plants. I tried the
> statacode -ipolate-, which uses linear interpolation and
> extrapolation
> procedures. But these have resulted in many negative values.
> Is there any
> way one could restrict -ipolate- from extrapolating negative
> values or are
> there superior methods to replace missing values?
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