Richard,
Does the base category matter? Since the coefficients are difficult to
interpret (i.e. the direction of the effect of var_x on outcome 1 is not
determined solely estimated coefficient of var_x for outcome 1 (Wooldridge,
2002 p. 497-498)) wouldn't you usually compute marginal effects, which do
not depend on the base category?
For example, the sign on _mpg_ changes sign when the base category changes
from 3 to 2, but the marginal effect is the same.
. mlogit rep price mpg, base(3) nolog
----------------------------------------------------------------------------
rep78 | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+--------------------------------------------------------------
1 |
price | -.0006468 .000849 -0.76 0.446 -.0023108
.0010173
mpg | -.0197515 .1959901 -0.10 0.920 -.4038851
.364382
_cons | 1.013502 6.695462 0.15 0.880 -12.10936
14.13637
-------------+--------------------------------------------------------------
<snip>
(Outcome rep78==3 is the comparison group)
. mfx , predict(outcome(1)) var(mpg)
Marginal effects after mlogit
y = Pr(rep78==1) (predict, outcome(1))
= .01570292
----------------------------------------------------------------------------
variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X
---------+------------------------------------------------------------------
mpg | -.0012526 .00287 -0.44 0.662 -.006868 .004363
21.2899
----------------------------------------------------------------------------
. mlogit rep price mpg, base(2) nolog
----------------------------------------------------------------------------
rep78 | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+-------------------------------------------------------------
1 |
price | -.0005451 .0008602 -0.63 0.526 -.0022309
.0011408
mpg | .0330037 .2163959 0.15 0.879 -.3911245
.4571319
_cons | .6890743 7.076853 0.10 0.922 -13.1813
14.55945
-------------+--------------------------------------------------------------
<snip>
(Outcome rep78==2 is the comparison group)
. mfx , predict(outcome(1)) var(mpg)
Marginal effects after mlogit
y = Pr(rep78==1) (predict, outcome(1))
= .01570292
----------------------------------------------------------------------------
variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X
---------+------------------------------------------------------------------
mpg | -.0012526 .00287 -0.44 0.662 -.006868 .004363
21.2899
----------------------------------------------------------------------------
Scott
Wooldridge, Jeffery. "Econometric Analysis of Cross Section and Panel
Data." Cambridge, MA: MIT Press, 2002.
-----Original Message-----
From: [email protected] [mailto:owner-
[email protected]] On Behalf Of Richard. Williams
Sent: Friday, April 15, 2005 11:32 AM
To: [email protected]; [email protected]
Subject: Re: st: RE: mlogit question.
At 09:59 AM 4/15/2005, [email protected] wrote:
yes,
you should use the option basecategory(#) after the command
mlogit depvar [indepvars] [weight] [if exp] [in range] , basecategory(#)
anna
I've always found mlogit's practice of using the most frequent category as
the base category a little annoying. It is easy enough to override, but
it
would be nice to be able to say something like basecategory(last) for when
you want to use the last category as the base but don't happen to remember
what its value is. It would also be nice if you could permanently set it
to go with the first or the last value, as I'm always forgetting to
override the default behavior.
-------------------------------------------
Richard Williams, Associate Professor
OFFICE: (574)631-6668, (574)631-6463
FAX: (574)288-4373
HOME: (574)289-5227
EMAIL: [email protected]
WWW (personal): http://www.nd.edu/~rwilliam
WWW (department): http://www.nd.edu/~soc
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