Hi everyone,
I have a challenge with interpreting the marginal effect in Probit model with a logged transformed covariate. Please, let us assumed that the dependent variable is no schooling (a binary variable which takes 1 if the child was not enrolled in school and 0 if enrolled). The variable of interest is the welfare variable which is logX (measured by the logged of the total household consumption) and the coefficient of the logX is -0.335. Other covariates are included in the model.
In my humble opinion, this means that if the total household consumption increased by 10%, the proportion of children who did not go to school will be reduced by 3 percentage points (0.335*10/100).
Please, is it by 3 percentage points or 3 percent? This is where I am confused.
In the Probit model, I know that for the continuous covariate (age), the marginal effect is interpreted as a percent (increased or decreased depending on the sign of the coefficient). For the binary covariate (gender), it is interpreted as a percentage point (increased or decreased depending on the sign of the coefficient). But, with the logged covariate, it is not straightforward. I am confused.
I would appreciate your value inputs.
Thanks
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