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AW: st: RE: RE: AW: correlate lag variables


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   AW: st: RE: RE: AW: correlate lag variables
Date   Tue, 11 May 2010 13:05:43 +0200

<> 


"...as the two of you have explained."


The credit for this statement should go to Peter and Nick, though, who made
almost identical comments to this effect. My code did not specifically
address this point.



HTH
Martin

-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Julia
Gesendet: Dienstag, 11. Mai 2010 12:51
An: statalist@hsphsun2.harvard.edu
Betreff: Re: st: RE: RE: AW: correlate lag variables

Dear Nick and Martin,

thank you for the usefull comments! Indeed I have a panel data, so the
more lags I include in the correlate command, less data is being used,
as the two of you have explained.

Best regards,

Julia

On Mon, May 10, 2010 at 6:54 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
> Yes; and I conjectured that the loss of 40 obs reflected a use of panel
data. The original poster has yet to respond.
>
> Nick
> n.j.cox@durham.ac.uk
>
> Lachenbruch, Peter
>
> I'm coning into this a little late, but did anyone notice that when you
include lag 2 you have 225 observations and when you include only lag 1, you
have 265.  Setting es=e(sample) after the lag 2 analysis and rerunning the
correlation for lag 1 if es==1 might shed some light on the problem.
>
> Martin Weiss
>
> Try -pwcorr- instead:
>
> *************
> clear*
> set obs 100
> gen y=1
> replace y =.6*y[_n-1]+rnormal() in 2/l
> gen byte time=_n
> tsset time
> corr y L.y L2.y
> pwcorr y L.y
> pwcorr y L.y L2.y
> *************
>
> Julia
>
> I would like to calculate the correlation between a variable and its
> past values. Thus, I use the following command:
>
> . correlate BI L1.BI L2.BI
> (obs=225)
>
>              |           L.      L2.
>              | BI       BI      BI
> -------------+---------------------------
>           BI|
>          --. |   1.0000
>          L1. |   0.0111   1.0000
>          L2. |   0.0647   0.0161   1.0000
>
>
> However, if I only ask the correlation for the first lag, my result
> differs....
>
> . correlate BI L1.BI
> (obs=265)
>
>              |             L.
>              |    BI     BI
> -------------+------------------
>           BI|
>          --. |   1.0000
>          L1. |   0.0174   1.0000
>
>  Why does excluding the second lag affect the correlation between the
> variable and its first lag?
>
> *
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>

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