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From |
"Wallace, John" <[email protected]> |

To |
<[email protected]> |

Subject |
st: RE: re: missing dummy variable |

Date |
Wed, 10 Oct 2007 13:30:14 -0700 |

```
Agreed - although I have occasions in the data I work with where the
grand mean itself is of interest, and the variation of the coefficients
from that mean is useful (hence my interest in -xi3- ). The problem is
the missing coefficient for one of the indicators.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Kit Baum
Sent: Wednesday, October 10, 2007 11:51 AM
To: [email protected]
Subject: st: re: missing dummy variable
John said
reg mpg foreign domestic, noconst hascons
xi3: regress mpg e.foreign
xi3: regress mpg e.make
*------------------ end example ---------------
Its clear that the information in the first two regressions is
equivalent, but the display would be better still if it was a
combination of both! If the _cons from the second regression was
combined with the explicit listing of both indicators in the first.
When the list of indicator variables gets long (as in the third
regression) , and especially when there are interactions, the task of
interpreting the dropped variables (and especially significance in the
t-test relative to the grand mean) becomes non-trivial (to me at least).
For the regression on make,
xi: reg mpg i.make
will produce a constant term which _is_ the coefficient on the
omitted make.
Note that xi3 DOES NOT do that! Its constant term is the grand mean,
and it is a pain in the rear to compute the missing coefficient from
that (it is the constant minus the sum of all the others, but -
lincom- doesn't do wildcards). I don't think -xi3- is at all helpful
in this regard.
Kit
Kit Baum, Boston College Economics and DIW Berlin
http://ideas.repec.org/e/pba1.html
An Introduction to Modern Econometrics Using Stata:
http://www.stata-press.com/books/imeus.html
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```

**References**:**st: re: missing dummy variable***From:*Kit Baum <[email protected]>

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