Hi,

I am also working on a probit model, and I would like to see the marginal effect of a categorical variable on the dependent variable, in particular, the marginal effect of higher education on the probability of being poor. I checked the "Procedures for Binary Equations" which QMS Gareth suggested but for some reason, the advice on this part couldn't work in Eviews. In other words, when I click Proc, I don't see anything like "Forecast (Fitted Probability/Index)" or "Make Residual Series" button. By the way, I am using Eviews 6. So I couldn't calculate with that way and I am sort of stuck. I tried another way to calculate it but it didn't give expected results. I mean the results are by far higher than expected. Let me share my code here, and I would appreciate if somebody advises me to overcome this problem. Thanks in advance.

This is my model;

probit(h) poor4e c reg1 reg2 reg3 reg5 eth2 eth3 eth4 dem2 n_adult n_child ed12 edu5

This is what I tried to calculate the marginal affect of edu5, by keeping all other variables constant at their mean values;

!z_highedu=c(1)+c(2)*@mean(reg1)+c(3)*@mean(reg2)+c(4)*@mean(reg3)+c(5)*@mean(reg5)+c(6)*@mean(eth2)+c(7)*@mean(eth3)+c(8)*@mean(eth4)+c(9)*@mean(dem2)+c(10)*@mean(n_adult)+c(11)*@mean(n_child)+c(12)*@mean(ed12)+c(15)*1

!p_highedu=@cnorm(!z_highedu)

!z_nonhighedu=c(1)+c(2)*@mean(reg1)+c(3)*@mean(reg2)+c(4)*@mean(reg3)+c(5)*@mean(reg5)+c(6)*@mean(eth2)+c(7)*@mean(eth3)+c(8)*@mean(eth4)+c(9)*@mean(dem2)+c(10)*@mean(n_adult)+c(11)*@mean(n_child)+c(12)*@mean(ed12)+c(15)*0

!p_nonhighedu=@cnorm(!z_nonhighedu)

table (2,4)education

education (1,1)="!z_highedu"

education (1,2)="!p_highedu"

education (2,1)=!z_highedu

education (2,2)=!p_highedu

education (1,3)="!z_nonhighedu"

education (1,4)="!p_nonhighedu"

education (2,3)=!z_nonhighedu

education (2,4)=!p_nonhighedu

show education

By comparing !z_highedu and !z_nonhighedu or !p_highedu and !p_nonhighedu, I was hoping to see the marginal effect, but it is way higher than expected