Dear All,
reading the Example 2, -areg postestimation- entry, Stata .pdf manual,
should be
instead, as per the following toy-example:
reading the Example 2, -areg postestimation- entry, Stata .pdf manual,
The squared residuals...
The squared fitted values...
Code:
. use https://www.stata-press.com/data/r18/auto2, clear
(1978 automobile data)
. areg mpg weight gear_ratio, absorb(rep78)
Linear regression, absorbing indicators Number of obs = 69
Absorbed variable: rep78 No. of categories = 5
F(2, 62) = 41.64
Prob > F = 0.0000
R-squared = 0.6734
Adj R-squared = 0.6418
Root MSE = 3.5109
------------------------------------------------------------------------------
mpg | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
weight | -.0051031 .0009206 -5.54 0.000 -.0069433 -.003263
gear_ratio | .901478 1.565552 0.58 0.567 -2.228015 4.030971
_cons | 34.05889 7.056383 4.83 0.000 19.95338 48.1644
------------------------------------------------------------------------------
F test of absorbed indicators: F(4, 62) = 1.117 Prob > F = 0.356
. predict fitted, xb
. g sq_fitted=fitted^2
. areg mpg fitted sq_fitted, absorb(rep78)
Linear regression, absorbing indicators Number of obs = 69
Absorbed variable: rep78 No. of categories = 5
F(2, 62) = 46.50
Prob > F = 0.0000
R-squared = 0.6939
Adj R-squared = 0.6643
Root MSE = 3.3990
------------------------------------------------------------------------------
mpg | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
fitted | -.9305602 .9537856 -0.98 0.333 -2.83715 .9760302
sq_fitted | .0462785 .0227219 2.04 0.046 .0008582 .0916989
_cons | 19.24899 9.725618 1.98 0.052 -.1922457 38.69022
------------------------------------------------------------------------------
F test of absorbed indicators: F(4, 62) = 1.278 Prob > F = 0.288
.

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