Seemingly Unrelated regression and Bootstrap

[margarida filipe]

Hello! I am using a seemingly unrelated regression to estimate the impacts of terrorist attacks on the tourism flows from four different nationalities. Although the independent variables are all the same across the equations, I decided to use this method because it yield different sandard errors than the individidual OLS regressions.

the model works like this:

. sureg (lYg = d1 T1e T2e T3e T1t T2t T3t LT1e LT2e LT3e LT1t LT2t LT3t L2T1e L2T2e L2T3e L2T1t L2T2t L2T3t) (lYf = d1 T1e T2e T3e T1t T2t T3t LT1e LT2e LT3e LT1t LT2t LT3t L2T1e L2T2e L2T3e L2T1t L2T2t L2T3t) (lYuk = d1 T1e T2e T3e T1t T2t T3t LT1e LT2e LT3e LT1t LT2t LT3t L2T1e L2T2e L2T3e L2T1t L2T2t L2T3t) (lYus = d1 T1e T2e T3e T1t T2t T3t LT1e LT2e LT3e LT1t LT2t LT3t L2T1e L2T2e L2T3e L2T1t L2T2t L2T3t), level(90) corr


However, I am pretty sure that my equations suffer from serial correlation (and possibly heteroskedasticity) and the SUR model does not account for that. I was wondering if using the bootstrap method would correct this problem.

I would strongly appreciate any advice on this matter as this is for my master's dissertation and a really want to get right.

Thanks in advance