Why isn’t the calculation of R2 the same for areg and xtreg, fe?
|
Title
|
|
R-squared: areg versus xtreg, fe
|
|
Author
|
William Gould, StataCorp
|
|
Date
|
September 1996
|
The coefficient estimates and standard errors are the same. The calculation
of the R2 is different. In the
areg procedure, you
are estimating coefficients for each of your covariates plus each dummy
variable for your groups. In the
xtreg, fe procedure
the R2 reported is obtained by only fitting a mean deviated model
where the effects of the groups (all of the dummy variables) are assumed to
be fixed quantities. So, all of the effects for the groups are simply
subtracted out of the model, and no attempt is made to quantify their overall
effect on the fit of the model.
Regardless of which approach you take, the SSE (sum-of-squares error) is the
same. In the areg approach, the SST (sum-of-squares total) is given
by
SST = sum(y2) − (1/n) * (sum(y))2
In the xtreg, fe approach, the R2 reported is not the
R2 that is calculated from the regression for areg but
the regression for the mean detrended dataset. As such, the SST for the
xtreg, fe approach is less than the SST for the areg approach.
The two calculations differ by
n
Σ
i=1
|
|
1
Ti
|
( |
Σ
t=1
|
yit |
) |
2 |
|
− CF |
where the CF is the correction factor
| ( |
n
Σ
i=1
|
|
Σ
t=1
|
yit |
) |
2 |
|
| |
n
Σ
i=1
|
|
Ti
|
|
Since the SSE is the same, the R2=1−SSE/SST is very
different. The difference is real in that we are making different
assumptions with the two approaches. In the xtreg, fe approach, the
effects of the groups are fixed and unestimated quantities are subtracted
out of the model before the fit is performed. In the areg approach,
the group effects are estimated and affect the total sum of squares of the
model under consideration.
|
FAQs
What's new?
Statistics
Data management
Graphics
Programming Stata
Mata
Resources
Internet capabilities
Stata for Windows
Stata for Unix
Stata for Mac
Technical support
|