I have a quarterly balanced panel data with 8 independent variables from 2000q1:2012:q2 (n=20 and T=52).
I start off by Pooled OLS (using -regress-) and then Fixed Effects Model (using -xtreg, fe-). Next, I check for time fixed effects and conclude that they are not needed using -testparm-.
Moving on, I run a Random Effects Model (using - xtreg , re-) and to decide between FEM and REM make use of Hausman Test. The result suggests REM.
Furthermore, I check whether REM is preferred to Pooled OLS and end up with REM.
However, I find the presence of Heteroskedasticity, Autocorrelation and Cross-sectional Dependence/Contemporaneous Correlation based on the results from - xttest3- , - xtserial- and - xttest2- respectively. I have the following questions:
1. Is -xtgls- approriate in this case? Stata manual states:
" xtgls fits panel-data linear models by using feasible generalized least squares. This command allows estimation in the presence of AR(1) autocorrelation within panels and cross-sectional correlation and heteroskedasticity across panels".
2. How to test for presence of AR(1) autocorrelation within panels?
3. How to proceed ahead?
I start off by Pooled OLS (using -regress-) and then Fixed Effects Model (using -xtreg, fe-). Next, I check for time fixed effects and conclude that they are not needed using -testparm-.
Moving on, I run a Random Effects Model (using - xtreg , re-) and to decide between FEM and REM make use of Hausman Test. The result suggests REM.
Furthermore, I check whether REM is preferred to Pooled OLS and end up with REM.
However, I find the presence of Heteroskedasticity, Autocorrelation and Cross-sectional Dependence/Contemporaneous Correlation based on the results from - xttest3- , - xtserial- and - xttest2- respectively. I have the following questions:
1. Is -xtgls- approriate in this case? Stata manual states:
" xtgls fits panel-data linear models by using feasible generalized least squares. This command allows estimation in the presence of AR(1) autocorrelation within panels and cross-sectional correlation and heteroskedasticity across panels".
2. How to test for presence of AR(1) autocorrelation within panels?
3. How to proceed ahead?
Comment