I don't see your point...
In your case ndigits is 0 and therefore:
unique = region * 10 + sector
This is enough to produce unique values for each region/sector
combination.
(1,2) and (2,1) must be treated as different and they do...
On Thu, 2013-11-21 at 15:57 +0100, Pindar wrote:
Yes, nice, but one has to check that 'region' and
'sector' do not
share a common cluster ID like in
<hansl>
region = randgen(i,1,10)
sector = randgen(i,1,5)
<hansl>
Since combinations like (1,2) and (2,1) are treated as being
different.
Hence, with a primary data manipulation 'sector = randgen(i,1,5) +100'
things should be fine.
21.11.2013 15:13, Riccardo (Jack) Lucchetti:
> On Thu, 21 Nov 2013, Giuseppe Vittucci wrote:
>
> > Hi,
> >
> > I have firm level data and two categorical variables (region and
> > sector).
> > I need to define another variable which is an index identifying
> > the
> > unique combinations region-sector each firm belongs to, so I can
> > use it
> > in computing cluster-robust s.e.
> >
> > One way to do this is to use the command "values" for region and
> > sector
> > and then use a nested loop, but this seems quite
> > time-consuming...
> >
> > Is there a simpler way in gretl to do it?
>
> You mean, like this?
>
> <hansl>
> nulldata 1024
>
> # simulated data
> region = randgen(i,1,20)
> sector = randgen(i,10,99)
> # ----------------------------------------------
> scalar ndigits = floor(log10(max(sector)))
> series unique = region * 10^(ndigits+1) + sector
> </hansl>
>
>
> -------------------------------------------------------
> Riccardo (Jack) Lucchetti
> Dipartimento di Scienze Economiche e Sociali (DiSES)
>
> Università Politecnica delle Marche
> (formerly known as Università di Ancona)
>
> r.lucchetti(a)univpm.it
>
http://www2.econ.univpm.it/servizi/hpp/lucchetti
> -------------------------------------------------------
>
>
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