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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>>
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