I have a problem with an linear regression model in which I have 2 dependent variables. Both are highly correlated with each other and should both be explained by the linear model
y = Xbeta + u
I´am asking myself if I can perform a seemingly unrelated regression (SUR) or a multivariate regression model because I am not sure about the differences between this two approaches.
I would be glad if someone can help me in this case.
Thank you very much.
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Best Answer
As mentioned in the Wikipedia: SUR is equivalent to the equation-by-equation OLS under the following two conditions:
i. When there are no cross-equation correlations between the error terms ii. When each equation contains exactly the same set of regressors. That being said, if your model and data don't satisfy above two cases, then you can proceed with the SUR.
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