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st: Strange -robust- results with a dummy variable


From   "Liu Yu" <liuyuashley@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Strange -robust- results with a dummy variable
Date   Fri, 21 Jan 2011 16:34:24 -0700

Dear Statalist.

I have got a weird result when I run the following two regressions. (In the
following regressions, y is a daily stock return data from 1990 to 2010, x
is the daily market return data for the same period, and d is a dummy
variable which equals 1 on Nov-10-2001 and 0 otherwise.)

The first is a simple OLS regression: 

. reg y x d

----------------------------------------------------------------------------
--
           y |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
           x |   .0237359     .03177     0.75   0.455    -.0385487
.0860204
           d |  -.0074946    .025867    -0.29   0.772    -.0582064
.0432172
       _cons |   .0007387   .0003825     1.93   0.054    -.0000112
.0014886

The second equals the first regression plus the "robust" option: 

. reg y x d, robust

----------------------------------------------------------------------------
--
             |               Robust
           y |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
           x |   .0237359   .0304741     0.78   0.436    -.0360082
.0834799
           d |  -.0074946    .000539   -13.90   0.000    -.0085514
-.0064378
       _cons |   .0007387   .0003834     1.93   0.054    -.0000131
.0014904
----------------------------------------------------------------------------
--

I am quite surprised by the fact that the standard error of d has decreased
significantly after I use the robust option, and its t-statistics changes
from non-significant to significant. Should I trust the results from the
second regression? Is there something special that I need to pay attention
about the dummy variable and the robust option? 

Thank you all. 

Catherine Liu

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