st: RE: RE: AW: correlate lag variables

["Nick Cox" <n.j.cox@durham.ac.uk>]

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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