Dear all,
Someone might have pose this question already but browsing the responses in the Stata archive I did no find a response to my problem.
I have a question on when to use cluster in a regression analysis. I am doing a Difference in Difference model and I want also to control for various individual and household characteristics.
Yi= b0+ b1 After+ b3Treatment + b4After*Treatment + Xis + His + ui
My treatment variable is at the Provincial level (only 18). I have individual observations that I have pooled from two different cross-sectional suveys, so this is not panel but I am following the same cohort in each survey. I have some questions:
If my treatement is at the province level, do I also need to cluster to adjust standard errors? I thought it was necessary to correct for intraclass correlation but in a this UCLA course, they mention that only if the interclass correlation is high (above .3 or .4), the ones I get, are very small around .014
http://www.gseis.ucla.edu/courses/ed230bc1/notes3/cluster.html
Do I still need to use the cluster option?
What are the implications if I cluster and do not really need to?
Do I also have to correct for inter-class correlation also (FE)? When I use both options, my t statistics jump up alot, more than 30, seems very strange!
thanks for your advice,
Gaby
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