Dear Statalist,

I am new to panel data regression analysis and Stata, so forgive me if my questions are too basic.
Currently i am conducting a research on company profitability with ROA as dependent variable and Liquidity, Log Total Asset, Leverage, and Asset Structure as independent variables. The data has 34 companies across 5 years with 170 total observations.
Code:
sum roa liquidity size leverage assetstructure

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
         roa |       170    .0177706    .1900833     -1.538       .456
   liquidity |       170    1.910747    1.954133       .011     20.167
        size |       170    12.81888    .6328861      10.76      14.01
    leverage |       170    1.254612    2.414883    -15.817     13.152
assetstruc~e |       170    .6500412    .1825059       .106       .996
First, i conducted Breusch-Pagan test that showed Prob>chibar2 = 0.00 which means that RE is chosen over OLS.
Code:
xtreg roa liquidity size leverage assetstructure, re
xttest0
Then I ran Hausman test that returned prob>chibar2 = 0.00 meaning FE is more suitable than RE.
Code:
hausman fe re
As for the tests, I checked my data for multicollinearity using vif and it showed that my data doesn't have multicollinearity problems. Then i checked for autocorrelation using xtserial and heteroscedasticity using xttest3 which shows that my data suffers from both problems.
Code:
 xtserial roa liquidity size leverage assetstructure

Wooldridge test for autocorrelation in panel data
H0: no first-order autocorrelation
    F(  1,      33) =      4.472
           Prob > F =      0.0421
Code:
xtreg roa liquidity size leverage assetstructure, fe

Fixed-effects (within) regression               Number of obs      =       170
Group variable: code                            Number of groups   =        34

R-sq:  within  = 0.2890                         Obs per group: min =         5
       between = 0.0425                                        avg =       5.0
       overall = 0.0516                                        max =         5

                                                F(4,132)           =     13.41
corr(u_i, Xb)  = -0.8918                        Prob > F           =    0.0000

--------------------------------------------------------------------------------
           roa |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     liquidity |   .0184212    .007616     2.42   0.017      .003356    .0334865
          size |   .4378722   .0898747     4.87   0.000     .2600913    .6156532
      leverage |   .0204201   .0049537     4.12   0.000     .0106212     .030219
assetstructure |   .5211536   .1530098     3.41   0.001     .2184851    .8238221
         _cons |  -5.994851   1.186008    -5.05   0.000    -8.340892    -3.64881
---------------+----------------------------------------------------------------
       sigma_u |  .32016264
       sigma_e |  .13284938
           rho |  .85311272   (fraction of variance due to u_i)
--------------------------------------------------------------------------------
F test that all u_i=0:     F(33, 132) =     5.51             Prob > F = 0.0000

. xttest3

Modified Wald test for groupwise heteroskedasticity
in fixed effect regression model

H0: sigma(i)^2 = sigma^2 for all i

chi2 (34)  =   77949.85
Prob>chi2 =      0.0000
After reading other questions on this site, i found that you can deal with autocorrelation and heteroscedasticity by clustering the standard errors. So i did the fixed effect regression using the cluster commands:
Code:
xtreg roa liquidity size leverage assetstructure, fe cluster(code)

Fixed-effects (within) regression               Number of obs      =       170
Group variable: code                            Number of groups   =        34

R-sq:  within  = 0.2890                         Obs per group: min =         5
       between = 0.0425                                        avg =       5.0
       overall = 0.0516                                        max =         5

                                                F(4,33)            =      2.70
corr(u_i, Xb)  = -0.8918                        Prob > F           =    0.0472

                                    (Std. Err. adjusted for 34 clusters in code)
--------------------------------------------------------------------------------
               |               Robust
           roa |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     liquidity |   .0184212   .0091547     2.01   0.052    -.0002042    .0370467
          size |   .4378722   .1960061     2.23   0.032     .0390949    .8366495
      leverage |   .0204201   .0066806     3.06   0.004     .0068284    .0340118
assetstructure |   .5211536   .3114909     1.67   0.104    -.1125794    1.154887
         _cons |  -5.994851   2.717433    -2.21   0.034    -11.52351   -.4661927
---------------+----------------------------------------------------------------
       sigma_u |  .32016264
       sigma_e |  .13284938
           rho |  .85311272   (fraction of variance due to u_i)
--------------------------------------------------------------------------------
(code)
my questions are:
1. Are my steps correct?
2. Do I need check my data with other tests?

Regards,
Hadi