Hello,
For a logit model, the marginal effect of change in a regressor, say jth regressor for observation i, on the conditional probability that y_i=1 is
G(x_i'b)[1 - G(x_i'b)]b_j
where, G(x’b) = exp(x’b)/[1+exp(x’b)].
You can request these marginal effects for each regressor from PROC QLIM by specifying the OUTPUT statement and its MARGINAL option. For example,
OUTPUT OUT=myoutputdata MARGINAL;
The average marginal effect is the sample average of these marginal effects. For a logit model, this is
(1/N)*SUMOVER_i{ G(x_i'b)[1 - G(x_i'b)] }b_j
You can obtain this by averaging the column for the marginal effect of the log of annual earnings over the observations in the data set you specify with the OUT option (myoutputdata in the example above).
If you calculated the average marginal effect of the log of annual earnings as described above and obtained the value -0.0204, then the interpretation of this is that on average a 1 percent increase in log earnings reduces the probability of the event occurring by 2.04 percent.
I hope this helps,
Gunce