Ops, sorry, there's a mistake in the last line.
It should be:
matrix m_sum = sumc(m_x)
2015-12-18 21:59 GMT+01:00 Artur Bala <artur.bala.tn(a)gmail.com>:
Hi Giulia,
Not sure that the following script is the best shortcut but I think it
does work. It supposes that there's a variable in your dataset which
identifies the companies - named here as 'company'.
Best,
Artur
# create a list with all variables, x1 to x20, to check for any missing
values
list xlist = x1
loop foreach i x2..x20
list xlist = xlist $i
endloop
# create a series, as a dummy to mark 'valid' observations; it takes 1 by
default
series validity=1
# check for NA: test_empty=0 if there's at least one missing value
throughout 'xlist'
series test_empty = ok(xlist)
# loop through each company
loop for i=1..1577
smpl company=$i --restrict --replace
# check if there's at least one missing value
scalar test_sc = sum(test_empty)
# if so then validity=0 for all the years for the respective company
if test_sc <5
series validity=0
endif
endloop
# finally restrict sample to 'valid' observations only
smpl validity=1 --restrict --replace
# and compute summary statistics - mean & median
summary xlist
# compute the sum for each variable
matrix m_x = {xlist}
matrix m_sum = sumc(xlist)
smpl full
2015-12-16 9:24 GMT+01:00 Giulia Taveggia <taveggia(a)csilmilano.com>:
> Dear all,
>
>
>
> I handle a panel dataset consisting of 1577 companies, 5 years and 20
> variables. I would like to know how restrict the dataset excluding missing
> values (ex. If one company have a missing value for one year it should be
> excluded by all other years). After doing this operation, I would like to
> compute the mean, the median and the sum for each variable. Could you
> please write down the right script for these actions?
>
>
>
> Thank you very much,
>
> Best Regards
>
> Giulia
>
>
>
> *Giulia Taveggia*
>
>
>
> Researcher, Country Analysis and Forecasts Unit
>
>
>
> CSIL Centre for Industrial Studies
>
> Corso Monforte 15 - 20122 Milano - Italy Tel +39 02780497- Fax +39 02
> 780703
>
>
>
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