Dear statalist users,
I was just wondering how to interpret the mfx function, because I fail to find anotated output. In particular, how do I interpret the output when my independent variables is in logarithm form? And:
- Is the "y = fitted values (predict) " the predicted value for the dependent at the mean of the sample?
- what does the X stand for?
- how do I do to compute the elasiticites?
mfx
Marginal effects after regress
y = Fitted values (predict)
= 6.6559795
------------------------------------------------------------------------------
variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X
---------+--------------------------------------------------------------------
dtempwin | .2421058 .24952 0.97 0.332 -.246949 .73116 .050837
dtempspr | .4376307 .2409 1.82 0.069 -.034528 .90979 .023661
dtempsum | -.1514247 .89739 -0.17 0.866 -1.91027 1.60742 .024777
dtempfal | -.6262103 .94935 -0.66 0.509 -2.48691 1.23448 .019205
dpreci~n | -1.346017 .57004 -2.36 0.018 -2.46327 -.228766 -.899125
dpreci~r | .9487695 .42794 2.22 0.027 .110019 1.78752 -.116792
dpreci~m | -.675565 .24334 -2.78 0.006 -1.15251 -.19862 3.35233
dpreci~l | .5008795 .16544 3.03 0.002 .176633 .825126 4.32255
dtempw~2 | .0233782 .09772 0.24 0.811 -.168145 .214902 2.35825
dtemp~r2 | .2214721 .12956 1.71 0.087 -.032469 .475414 3.88076
dtemp~m2 | .5369094 .39422 1.36 0.173 -.235748 1.30957 3.32566
dtempf~2 | -.6301785 .59813 -1.05 0.292 -1.80249 .542135 1.22008
dprec~n2 | .0058086 .00205 2.83 0.005 .001792 .009825 1452.24
dprec~r2 | -.0038283 .00196 -1.95 0.051 -.007677 .00002 801.534
dprec~m2 | .0033669 .00113 2.99 0.003 .001158 .005576 7734.41
dprec~l2 | -.0011596 .00033 -3.53 0.000 -.001803 -.000516 10793.5
soil1 | -2.832005 1.72421 -1.64 0.100 -6.2114 .547394 .013659
soil2 | 41.66267 16.865 2.47 0.013 8.60754 74.7178 .0086
ln_area | -.3286273 .05804 -5.66 0.000 -.442382 -.214873 .79798
rec_di~B | -.4837681 .29385 -1.65 0.100 -1.0597 .092168 .070454
rec_di~Y | -.990503 .64856 -1.53 0.127 -2.26167 .280661 .05256
------------------------------------------------------------------------------
Thanks a lot,
Laura
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