Hello sir,
I am in dilemma what to use among xtgls or xtpcse.
The panel data i have has problems like heteroskedasticity autocorrelation and cross sectional dependency.
In that context i can use one of the two models mentioned here.
The problem i face with these is very high Wald Chi2 values
the model is used to see the relevance of states as well as years in the data for the parameters used. Below i give IDEA ABOUT THE STRUCTURE OF PANEL DATA .
State YearId Id LoAgri LoIND LoSer LQindex ASSETcon Spread CD loGFCF lopccp loNVA loSSTICT ay by cy
STATE INDICATES THE NAME OF THE REGION. YearId indicates the time id , Id indicates the group Id. rest of them are the variables.
ay by and cy are the dummies variables for which i want to capture the effect . I use i.Id and i.YearId in the model for the same .
The number of Years is 16 and the number of states are 18 and the total obervations are around 280. Hope this informationwill be sufficient.
Kindly reply back . Eagarly waiting for it . Thanks . Regards
I am in dilemma what to use among xtgls or xtpcse.
The panel data i have has problems like heteroskedasticity autocorrelation and cross sectional dependency.
In that context i can use one of the two models mentioned here.
The problem i face with these is very high Wald Chi2 values
the model is used to see the relevance of states as well as years in the data for the parameters used. Below i give IDEA ABOUT THE STRUCTURE OF PANEL DATA .
State YearId Id LoAgri LoIND LoSer LQindex ASSETcon Spread CD loGFCF lopccp loNVA loSSTICT ay by cy
STATE INDICATES THE NAME OF THE REGION. YearId indicates the time id , Id indicates the group Id. rest of them are the variables.
ay by and cy are the dummies variables for which i want to capture the effect . I use i.Id and i.YearId in the model for the same .
The number of Years is 16 and the number of states are 18 and the total obervations are around 280. Hope this informationwill be sufficient.
Kindly reply back . Eagarly waiting for it . Thanks . Regards
