Dear all,
I am using a repeated cross-section of pupil-level data to regress exam
attainment on various characteristics. Since pupils are clustered in particular
schools, I need to correct the standard errors for clustering at school-level.
I could adopt one of the following approaches:
regress Y X, cluster(school)
xtreg Y X, re (i=school)
So the first approach corrects standard errors by using the cluster command.
The second approach uses a random effects GLS approach.
I thought that the two approaches do the same thing and should give the
same results. However, I find that the standard errors are alot smaller
using the second approach.
Does anyone know how the two approaches differ from one another?
Thanks,
Sandra
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
