Have a good day to all contributers,
I have a panel data set with T=3 and N=22 with 1 dependent 4 independent variables.
To choose which model will fits best for my date i have tried the following procedure:
1- Run the regression for Fixed Effect Model >> xtreg y x1 x2 x3 x4, fe
2- Run the regression for Random effext model >> xtreg y x1 x2 x3 x4, re
3- Run Hausman Test to compare FE and RE >> hausman fixed random, sigmamore // Prob>chi2=0.0563 then i go for RE model.
4- Run LM Test to compare RE and POLS >> xttest0 // Prob > chibar2 = 0.0000 then i go for RE model.
5- I have checked for heteroscedasticity for RE model wiht the following commands:
5.1- xtreg Consumption Price Rainy_Day Total_Rain Total_Evaporation, re
5.2- predict eps,e
5.3- robvar eps, by(groups) >> W0: Pr > F =0.0007, W50: Pr > F = 0.85, W10: Pr > F = 0.0007 since W0 and W10 < 0.05 Reject the Null and conclude that there is heteroscedasticity
6- I have checked for auto-correlation >> xtregar y x1 x2 x3 x4, re lbi >> DW=2.43 Baltagi-WU LBI=2.95. Since both test statistics are greater than 2 then there is no auto-correlation.
7- I have checked for cross-section dependency using Pesaran and Friedman Test
7.1 xtreg y x1 x2 x3 x4, re
7.2 xtcsd, pesaran >> Pr= 0.58
7.3 xtcsd, friedman >> Pr= 1.00 both values are greater than 0.05 then do not reject H0 and i have concluded that there is no cross-section dependency.
8- At last, i have run the following robust RE model estimation
xtreg y x1 x2 x3 x4, re vce(robust)
My questions:
a-) My final model at the 8th step has Prob>chi2 = 0.0991 and Walt chi2(4) = 7.80.
With these results i concluded that my model is not appropriate for my data. Am i right?
b-) If my perception on section a is right, how can i fix this problem or improve my model? Any suggestion would be very appreciated.
Kind and best regards.
I have a panel data set with T=3 and N=22 with 1 dependent 4 independent variables.
To choose which model will fits best for my date i have tried the following procedure:
1- Run the regression for Fixed Effect Model >> xtreg y x1 x2 x3 x4, fe
2- Run the regression for Random effext model >> xtreg y x1 x2 x3 x4, re
3- Run Hausman Test to compare FE and RE >> hausman fixed random, sigmamore // Prob>chi2=0.0563 then i go for RE model.
4- Run LM Test to compare RE and POLS >> xttest0 // Prob > chibar2 = 0.0000 then i go for RE model.
5- I have checked for heteroscedasticity for RE model wiht the following commands:
5.1- xtreg Consumption Price Rainy_Day Total_Rain Total_Evaporation, re
5.2- predict eps,e
5.3- robvar eps, by(groups) >> W0: Pr > F =0.0007, W50: Pr > F = 0.85, W10: Pr > F = 0.0007 since W0 and W10 < 0.05 Reject the Null and conclude that there is heteroscedasticity
6- I have checked for auto-correlation >> xtregar y x1 x2 x3 x4, re lbi >> DW=2.43 Baltagi-WU LBI=2.95. Since both test statistics are greater than 2 then there is no auto-correlation.
7- I have checked for cross-section dependency using Pesaran and Friedman Test
7.1 xtreg y x1 x2 x3 x4, re
7.2 xtcsd, pesaran >> Pr= 0.58
7.3 xtcsd, friedman >> Pr= 1.00 both values are greater than 0.05 then do not reject H0 and i have concluded that there is no cross-section dependency.
8- At last, i have run the following robust RE model estimation
xtreg y x1 x2 x3 x4, re vce(robust)
My questions:
a-) My final model at the 8th step has Prob>chi2 = 0.0991 and Walt chi2(4) = 7.80.
With these results i concluded that my model is not appropriate for my data. Am i right?
b-) If my perception on section a is right, how can i fix this problem or improve my model? Any suggestion would be very appreciated.
Kind and best regards.
.
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