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Re: st: too large standard errors of marginal effects after multinomial logit model


From   Maarten buis <[email protected]>
To   [email protected]
Subject   Re: st: too large standard errors of marginal effects after multinomial logit model
Date   Tue, 30 May 2006 23:17:26 +0100 (BST)

--- [email protected] wrote:
> When I calculate the marginal effects after multinomial logit model
> using the command "mfx compute, predict (outcome(1))", Stata gives me
> very large standard errors and all p values are equal to 1. Dose 
> anyone know the reason of this problem and how to solve it? 

You can try to calculate the marginal effects and their standard error
using the -nlcom- command. If these standard errors are more reasonable
than apperently the numerical procedure -mfx- ran into trouble in your
particular dataset. 

Calculating the marginal effects in a multinomial logit models gets a
bit ugly, and it is getting late here, so for now I will just give you
example code, and if required I will explain a bit about it tomorrow.

HTH,
Maarten 

*-------------- begin example -----------------
sysuse auto, clear
recode rep78 2=1 3=1 4=2 5=3
mlogit rep78 foreign mpg

sum foreign if e(sample)
scalar mfor = r(mean) 
sum mpg if e(sample)
scalar mmpg = r(mean)

local exp2 "exp([2]_cons + [2]foreign*scalar(mfor) + 
[2]mpg*scalar(mmpg))"
local exp3 "exp([3]_cons + [3]foreign*scalar(mfor) + 
[3]mpg*scalar(mmpg))"

local p1 "1/(1 + `exp2' + `exp3')"
local p2 "`exp2'/(1 + `exp2' + `exp3')"
local p3 "`exp3'/(1 + `exp2' + `exp3')"

nlcom (foreign: `p1'*(0-(`p2'*[2]foreign + `p3'*[3]foreign))) /*
    */(mpg: `p1'*(0-(`p2'*[2]mpg + `p3'*[3]mpg))) 

mfx compute, predict (outcome(1)) nodiscrete
*--------------------- end example ------------------



-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z214

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------

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