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st: Question on mfx and regress


From   "Joao Pedro W. de Azevedo" <jazevedo@provide.com.br>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Question on mfx and regress
Date   Tue, 6 Apr 2004 14:34:48 +0100

Hello,
Could any one help me understand why the coefficients of the natural log of
a dependent variable are close, but not equivalent to the marginal effect of
the same dependent variable estimated with the eydx option (dlogy/dx).
Assuming the same sample, regressors, etc...

A numerical example use the auto dataset follows below.

Many thanks,

JP



use auto
gen lnprice=ln(price)
regress lnprice  mpg rep78 headroom trunk

----------------------------------------------------------------------------
--
     lnprice |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
         mpg |  -.0356709    .008907    -4.00   0.000    -.0534646
-.0178772
       rep78 |   .1079145   .0436081     2.47   0.016     .0207973
.1950316
    headroom |  -.1041363   .0614146    -1.70   0.095    -.2268261
.0185535
       trunk |   .0227757   .0136441     1.67   0.100    -.0044815
.0500329
       _cons |   9.026498   .3126985    28.87   0.000     8.401811
9.651185
----------------------------------------------------------------------------
--


regress price  mpg rep78 headroom trunk

----------------------------------------------------------------------------
--
       price |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
         mpg |  -252.6424   70.48498    -3.58   0.001    -393.4523
-111.8325
       rep78 |   626.8463   345.0914     1.82   0.074    -62.55297
1316.246
    headroom |  -613.8173    486.003    -1.26   0.211     -1584.72
357.0853
       trunk |   121.0197   107.9722     1.12   0.267    -94.67944
336.7189
       _cons |   9545.797   2474.533     3.86   0.000      4602.35
14489.24
----------------------------------------------------------------------------
--

mfx, eydx

Elasticities after regress
      y  = Fitted values (predict)
         =  6146.0435
----------------------------------------------------------------------------
--
variable |      ey/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+------------------------------------------------------------------
--
     mpg |  -.0411065      .01165   -3.53   0.000  -.063945 -.018268
21.2899
   rep78 |   .1019918      .05638    1.81   0.070  -.008514  .212497
3.4058
headroom |  -.0998719      .07923   -1.26   0.208  -.255169  .055425
3
   trunk |   .0196907       .0176    1.12   0.263  -.014796  .054177
13.9275
----------------------------------------------------------------------------
--



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