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

 From "Nick Cox" To Subject st: RE: RE: AW: correlate lag variables Date Mon, 10 May 2010 17:54:41 +0100

```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

*************
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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```