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Re: st: residuals when no variation in Y
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: residuals when no variation in Y
Date
Mon, 16 Jan 2012 08:57:51 +0000
The non-zero residuals arise because the data for the first panel
differ from the averaged relationship over all panels. Your -areg-
command doesn't mean that there is a separate regression for each
panel.
To make this clear:
predict predict
scatter y predict time if panel == 1, c(. l) sort lc(red) mc(red) || ///
scatter y predict time if panel == 2, c(. l) sort lc(blue) mc(blue)
The predictions are the same for both panels.
Nick
On Mon, Jan 16, 2012 at 2:14 AM, Raymond Lim <[email protected]> wrote:
> I have 2 panels with 4 time periods. For panel A, Y=0 in every period.
> For panel B, Y has variation. I regress Y on a linear time trend.
>
> If I regress with just panel A, I get no results as expected. If I do
> a fixed effect regression with both panels, then calculate the
> residuals, panel A's residuals are non-zero. Where are these residuals
> coming from if there is no within-variation in the Y variable?
>
> CODE TO ILLUSTRATE:
> clear all
> input panel y time
> 1 0 2001
> 1 0 2002
> 1 0 2003
> 1 0 2004
> 2 4 2001
> 2 8 2002
> 2 7 2003
> 2 3 2004
> end
>
> reg y time if panel==1
> areg y time, a(panel)
> predict resid, resid
> list, sepby(panel)
>
>
>
> OUTPUT IN THE END
> . list, sepby(panel)
>
> +--------------------------+
> | panel y time resid |
> |--------------------------|
> 1. | 1 0 2001 -.3 |
> 2. | 1 0 2002 -.1 |
> 3. | 1 0 2003 .1 |
> 4. | 1 0 2004 .3 |
> |--------------------------|
> 5. | 2 4 2001 -1.8 |
> 6. | 2 8 2002 2.4 |
> 7. | 2 7 2003 1.6 |
> 8. | 2 3 2004 -2.2 |
> +--------------------------+
> *
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*
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