[Duong Le]

“Do you mean here that using either 2SLS or the three-stage procedure is appropriate in this case?”

Yes, both procedures are consistent, the three step procedure might be more “natural” than the 2SLS, and therefore preferable. But 2SLS is consistent in this case too, so there is nothing wrong just using 2SLS.


“my interpretation is that individuals living in urban areas and with higher education have a higher income than their counterparts living in rural and with lower income by [exp(0.415)-1]*100. ”

I am not sure what you are saying. What you have is 2 dummy variables. The base /omitted category is (low education & rural), the estimate on (high education & urban) is the difference between (high education & urban) and the omitted/base category (low education & rural). So the estimate [exp(0.415)-1]*100 is the premium in earning of being educated and urban, compared to being uneducated and rural.

Dear Professor Joro,

I am sorry for bothering you again, but do you know how to compute marginal effects of an interaction term after xtivreg2? I have been trying to google, but it seems I have found none. Specifically, the following is what I want to compute:

margins tenure_south, dydx(tenure)

That is the difference of effects of tenure for South and non-south regions.

Code

webuse nlswork, clear
gen union_south = union*south     // interaction term for IV
gen rtenure = floor(tenure)
gen tenure_south = rtenure*south  // interaction term for endogenous variable
gen age_south = age*south         // interaction term for age

xtivreg2 ln_w age age_south south (tenure tenure_south = union union_south), fe

margins tenure_south, dydx(tenure)

Error message

variable __marg_pvar_1 not found

When I tried to use xtivreg command

xtivreg ln_w age age_south south (tenure tenure_south = union union_south), fe

margins tenure_south, dydx(tenure)

Error message

factor tenure_south not found in list of covariates

Thank you.