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Re: st: RE: RE: AW: correlate lag variables
From
Julia <[email protected]>
To
[email protected]
Subject
Re: st: RE: RE: AW: correlate lag variables
Date
Tue, 11 May 2010 12:51:19 +0200
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 <[email protected]> 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
> [email protected]
>
> 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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