Hi everyone,

I have cross-sectional data with 3 observations per student for 3 different subjects, and was planning to estimate some teacher effects with an FD/FE model.

It would be ideal if every student had three teachers, one for each subject. Unfortunately, only about 27% do and the other 83% of the 2359 students have two teachers - with one of them teaching 2 subjects.

I am guessing there will be serial correlation if I use a xtreg fe model, since unobserved teacher effects will be almost the same for all those pairs of observations with the same teacher on 2 different subjects. So perhaps a customized FD model is a better choice. Not only that, I also think I would have to weigh the results with iweights if I use FE, with those pairs of same-teacher-observations weighing half, since their demeaned teacher values are essentially the same teacher effect being measured. Since I'm unsure about how to go about with this or if it is even a good solution, FD seems like a better choice (since it would eliminate the teacher effects completely between the same teacher, and only measure the subject effects in those cases).

Still, since xtreg is so convenient to use, I thought I would convince myself first by doing a test for serial correlation and heteroskedasticity. Since my data is actually cross-sectional, or a panel without a time variable, I don't know where to start on what tests to use. What would be appropriate to look at in this case? And am I even on the right track here or am i missing something important?

Code:
IDSUBJ IDSTUD IDTEACH NTEACH IDCLASS
1 20110 202 3 201
4 20111 201 3 201
2 20111 203 3 201
1 20111 202 3 201
1 20112 202 3 201
4 20112 201 3 201
2 20112 203 3 201
2 30102 302 2 301
4 30102 301 2 301
1 30102 301 2 301
2 30103 302 2 301
1 30103 301 2 301
4 30103 301 2 301
4 30104 301 2 301
1 30104 301 2 301
Since I didn't know about crossposting last time; I did post a similar but not identical question here on stackexchange.