I refer to this post which seems to question the importance of the normal distribution of the residuals, arguing that this together with heteroskedasticity could potentially be avoided by using robust standard errors.
I have considered various transformations - roots, logs etc. - and all is proving useless in resolving completely the issue.
Here is a Q-Q plot of my residuals:
- Dependent variable: already with logarithmic transformation (fixes outlier issues and a problem with skewness in this data)
- Independent variables: age of firm, and a number of binary variables (indicators) (Later on I have some counts, for a separate regression as independent variables)
iqr command (Hamilton) in Stata does not determine any severe outliers which rule out normality, but the graph below suggests otherwise and so does the Shapiro-Wilk test.