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st: interpreting marginal effect after logit


From   "Yun Liu" <liuyun3@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: interpreting marginal effect after logit
Date   Wed, 2 May 2007 18:22:22 -0400

Dear Statalisters,

I estimate a logit model and need your help in interpreting the
results. Please see below for part of the output. Both x1 and x2 are
statistically significant. But based on the derivatives, one standard
deviation change in x1 increases the probability by merely 1%
(0.074*0.129). Similarly one standard deviation change in x2 increases
the probability by merely 2% (5.9*0.003). I think the reason is that y
is unbalanced and the predicted y is only 0.148 at sample mean.

Are these marginal effects embarrassingly low? What is the common
practice in presenting such results? Thank you!

.tab y
       y|      Freq.     Percent        Cum.
------------+-----------------------------------
0 |      8,640       83.89       83.89
  1|      1,659       16.11      100.00
------------+-----------------------------------
     Total |     10,299      100.00


. sum x1
   Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
      x1 |     10299    .0956022    .1286858          0   1.252115

.sum x2
   Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
       x2 |     10299    53.20118    5.923979         29         62


.mfx
Marginal effects after logit
     y  = Pr(y) (predict)
        =  .14754039
------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
    x1 |   .0740955      .03099    2.39   0.017    .01335  .134841   .095602
   x2  |   .0034519      .00065    5.35   0.000   .002187  .004717   53.2012
......

Yun
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