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Re: st: event study ado-file?
Maarten Buis <firstname.lastname@example.org>
Re: st: event study ado-file?
Mon, 18 Feb 2013 16:52:00 +0100
There is no way we can know, as we don't have your dataset.
Anyhow programming a new command that works quicker costs a
non-trivial amount of time too, so it becomes a tricky optimization
problem to find the quickest solution. Actually it is not that tricky;
I would say that in most situations you will loose time when
programming a new command. I program a lot, but if you add all the
time spent programming and subtracted the time gained from quicker
running programs I am sure I lost a considerable amount of time with
that strategy (I had fun while programming, though...).
I would say, just try -statsby- out. If it is too slow you'll notice
that quick enough...
On Mon, Feb 18, 2013 at 4:11 PM, László Sándor <email@example.com> wrote:
> Thanks, Nick, as always.
> So you think -statsby- is fast enough for this. I hoped not to
> preserve my (big) data too much (= ever), and was lazy to check what
> statsby actually does.
> Thanks again!
> On Mon, Feb 18, 2013 at 9:54 AM, Nick Cox <firstname.lastname@example.org> wrote:
>> As you say, this is a standard kind of graph. I would write a do-file
>> separating out the data management from the graphs. I've found
>> -statsby- very useful for confidence intervals and there was an essay
>> to that effect in
>> SJ-10-1 gr0045 . . . . . . . . . . . . . Speaking Stata: The statsby strategy
>> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox
>> Q1/10 SJ 10(1):143--151 (no commands)
>> demonstrates the use of statsby to prepare a reduced
>> dataset for subsequent graphing
>> I am not clear that you need think about this as requiring an ado-file.
>> On Mon, Feb 18, 2013 at 2:31 PM, László Sándor <email@example.com> wrote:
>>> Before I code up my own ado-file, I was wondering if there was
>>> something on this out there (for Stata 12 MP for Windows, if it
>>> I need "standard" graphs of estimates with confidence interval bands
>>> for various periods. I am happy to define periods myself, so this
>>> would be an event study if I shift periods to be around 0 (time of
>>> treatment) and other periods show pre- and post-treatment treatment
>>> effects. Or I could also use this for a chronology of treatments: an
>>> outcome defined for all years (e.g. income in the given year) and
>>> plotting all these treatment effects for treatment occurring at
>>> different times.
>>> E.g. the first graph here, but with CI bands:
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Maarten L. Buis
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