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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