Dear all,

I'm testing the OLS assumptions for a multiple cross-sectional regression model.

In relation to this, I would like to ask if one first have to test all the assumptions before running eventual standard robust errors-model (if heteroscedasticity is a problem).

So, should I first test for homoscedasticity and if heteroscedasticity is present then use standard robust errors. Should I then test for linearity and normality on the standard robust errors-model? Or should all OLS assumptions tests be carried out on the initial model?

Also, I would like to ask if somebody knows the code in stata for finding the 1 percent percentile and 99 percent percentile thresholds? (in relation to deleting outliers)

Lastly, in relation to the constant variance (homoscedasticity) and linearity assumptions, should I then apply just normal redisuals, standardized or studentized residuals?

Thanks in advance!

Best,
Anders