Hi James
As far as I can see the marginal effects can be calculated in the same
way as for the multinomial logit model in this case (see e.g. Greene,
2003, pp. 722, for the formula). In the case of the 'female' variable
an alternative approach is to simply calculate the difference in the
probability of choosing a car of a particular nationality assuming the
respondents are female/male, i.e. marginal effect = prob(assuming
female) - prob(assuming male). The program below demonstrates the two
approaches using the choice.dta dataset.
Hope this helps.
Arne
use http://www.stata-press.com/data/r9/choice.dta
gen usa = (car == 1)
gen japan = (car == 2)
gen europe = (car == 3)
gen female = (sex == 0)
gen femJap = female*japan
gen femEur = female*europe
gen incJap = income*japan
gen incEur = income*europe
qui clogit choice japan europe femJap femEur incJap incEur dealer, group(id)
/* Predicted probabilities by nationality */
predict double prob
sort id, stable
by id: egen double prob_USA = sum(prob*usa)
by id: egen double prob_Jap = sum(prob*japan)
by id: egen double prob_Eur = sum(prob*europe)
/* Individual-specific marginal effects for variable female */
gen double meff_fem = prob_USA*(-_b[femJap]*prob_Jap -
_b[femEur]*prob_Eur) if usa == 1
replace meff_fem = prob_Jap*(_b[femJap] - _b[femJap]*prob_Jap -
_b[femEur]*prob_Eur) if japan == 1
replace meff_fem = prob_Eur*(_b[femEur] - _b[femJap]*prob_Jap -
_b[femEur]*prob_Eur) if europe == 1
/* Average marginal effects for variable female */
sum meff_fem if usa == 1
sum meff_fem if japan == 1
sum meff_fem if europe == 1
/* Alternative individual-specific marginal effects for variable female */
/* Predicted probabilities by nationality, all respondents assumed male */
replace femJap = 0
replace femEur = 0
predict double mprob
/* Predicted probabilities by nationality, all respondents assumed female */
replace femJap = japan
replace femEur = europe
predict double fprob
/* Difference in probabilities, female-male */
gen double meff_fem2 = fprob-mprob
/* Alternative average marginal effects for variable female */
sum meff_fem2 if usa == 1
sum meff_fem2 if japan == 1
sum meff_fem2 if europe == 1
On 28/08/06, James Marton <marton@uky.edu> wrote:
Hello Everyone
I am trying to estimate marginal effects for a conditional logit model that
is essentially identical to the one presented as example 5 on page 227 in
the STATA 9 reference for A-J under the clogit command. In that example,
each person chooses between 3 types of cars: American (excluded category),
Japanese, and European. Their choice depends on their sex and income (both
person specific) and also the number of car dealerships of each type in
their city (person & choice specific). The dataset is available at:
http://www.stata-press.com/data/r9/choice.dta
Does anyone know how to generate a set of marginal effects for each person
specific variable? In other words, after running the clogit model whose
output is given on page 228, I would like to put together a table with the
following information:
Variable Marginal Effect
Female marginal effect for choosing American if female
marginal effect for choosing Japanese if female
marginal effect for choosing European if female
Income marginal effect for choosing American if income inc. by 1 unit
marginal effect for choosing Japanese if income inc. by 1
unit
marginal effect for choosing European if income inc. by 1
unit
Here the marginal effects for female should sum to one and the marginal
effects for income should sum to one.
Any suggestions would be greatly appreciated!
Jim Marton
Assistant Professor
Martin School of Public Policy and Administration University of Kentucky
marton@uky.edu
http://www-martin.uky.edu/~marton
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