You don't give a very clear idea
of your data structure. I guess that you
have panel data, something like
. tsset country year
and a series of variables for different
industries, say
industry1-industry10
What you want in question 1 can be got in
various ways. Here is one:
The first value for each panel is 1 if
the investment value is not missing and 0 otherwise:
. by id : gen nrun = !mi(industry1) if _n == 1
Subsequent values are always 0 if the investment
value is missing and 1 greater than the previous
otherwise.
. by id : replace nrun =
cond(mi(industry1), 0, nrun[_n-1] + 1) if _n > 1
Another way of doing it is to use -tsspell- from SSC.
Install that by
. ssc inst tsspell
Then for say -industry1- the definition of a spell is
just a sequence of non-missing values of -industry1-.
. tsspell, c(industry1 < .)
The variable _seq created by -tsspell- is what
you want. Spells automatically are determined
separately by panel.
If different industries have different patterns
of missing values, you would need something
more like this:
forval i = 1/10 {
tsspell, c(industry`i' < .) spell(_spell`i') seq(_seq`i') end(_end`i')
}
After which you might want to -drop- some of the created variables.
Nick
[email protected]
Oleksandr Shepotylo
>
> I am using perpetual inventory method to calculate
> capital stock but my
> dataset has a lot of missing data on investment. I have two questions:
>
> 1. For any given country and industry, I want to create
> an index that
> will tell me how many
> non-missing numbers in a row I have prior to any year t.
> For example, I have investment data for country i and
> industry j starting
> from 1965 to 1975 then missing in 1976-1977 and continuing in
> 1978-2001. The
> index should start from 1 in 1965 till 11 in 1975. then it equals 0 in
> 1976-1977 and starts from 1 again in 1978.
>
> 2. Less important, but still interesting. How to impute
> missing data if
> the gap- like in previous example- is less or equal to 2?
> Imputation can be
> based on average growth in capital stock for last 3 years.
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