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Re: st: xtlogit: panel data transformation's recast to double makes model incomputable


From   Nick Cox <[email protected]>
To   "[email protected]" <[email protected]>
Subject   Re: st: xtlogit: panel data transformation's recast to double makes model incomputable
Date   Wed, 3 Apr 2013 10:46:49 +0100

I think you are missing my point. Time series have some kind of
dependence structure, unless they happen to be white noise. Ignoring
that dependence won't make it disappear. Your various models all
appear to be implying that there is no dependence other than implied
by the panel structure, that is to say that prices at successive dates
for the same panel are mutually independent, which seems a very strong
assumption to me.

A tiny point of presentation, yet another covered in the FAQ. Left
ticks around command names such as `tsset` have no special effects on
Statalist; the convention recommended is exemplified by -tsset-.

Nick

On 3 April 2013 10:13, Tom <[email protected]> wrote:
> Hi Nick,
>
> They are time series. `tsset` returns:
>
> panel variable:  ticker_id (unbalanced)
> time variable:  date, 101 to 532
> delta:  1 unit
>
> Each group has its own continuous time frame, ranging from 101 to 532
> (the first 100 dates have been dropped because they were required to
> create lagged variables).
>
> The only issue that I could possible see arising from time series is
> that the dates are not "synchronised" inbetween groups. With this I
> mean that t == 200 is a different point in time for id == 1 than t ==
> 200 for the group with id == 2.
>
> But I don't think time series are the issue because clogit is not
> using them (it only uses the panel id variable), and it is returning
> exactly the same results as xtlogit.
>
> I was hoping that something obvious would arise from the many log
> files I submitted a couple of posts back :)
>
> Tom
>
>
> On Wed, Apr 3, 2013 at 10:04 AM, Nick Cox <[email protected]> wrote:
>> As if there weren't enough problems, what is the assumption here about
>> time series structure? I may have missed something in a complicated
>> thread, but the original data look like time series to me.
>
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