When is self-selection a problem? Mincer equation I need help understanding this selection bias problem. I am estimating a mincer equation for a final year project and I was told I need to worry about self-selection bias IN OCCUPATIONS.

My lecturer said that, because wages vary between occupations, and individuals select occupations as a choice, the sample is selected. In that sense, I need to correct this problem. We were taught the Heckman selection model in the context of people deciding whether to work or not. I understand this case, but not the case of occupations. I mean, all is a choice, isn't? In my model I also have hours of work, public or private sector, full time or part time, region, industry, and other common variables. Why do we worry about occupations but not about everything else? I just cannot get my head around this.

Occupations are low, middle and high skill. I'm estimating the returns to education for Australian workers.

I think one thing is important, which is if the variable is included or not in the regression. For example, normally you cannot include a variable
of employment or inactive, because inactive have no wage. This is why, as I understood from the lecture, we need to test for selection. But choice variables that are included, are they a concern?
There is no fundamental difference between the choice of occupation and say region. In fact,  there exists a large literature in migration that builds on Roy's model, starting with Borjas (1987).  I'd argue that ideally you'd like to correct for self- selection/ sorting in all choice dimension. In practice this can be hard/ cumbersome/ impossible to do.

Why do we tend to worry about self- selection more in the context of occupations than regions? I suppose it boils down to the fact that everyone had to actively choose an occupation at some point,  whereas we are all born in some region. But,  again,  there is no fundamental difference.