Hi,

I am trying to estimate the impact of directors' remuneration on firm performance. My unbalanced data set comprises 1696 firms and 16 time periods (in particular, years). I have 7 independent variables in total. In existent literature, fixed effects model (xtreg, fe) has been used as a common methodology to estimate parameters. Below is my model.

Code:
xtreg Profitability4 Size2 Leverage1 CurrentRatio SalesGro CapitalExpenditure2 WPromoterSharesin1 AD_Totalremuneration i.Year, fe
I checked for serial correlation in the error term using the command xtserial and found presence of serial correlation. Below is the output for the same.
Code:
Wooldridge test for autocorrelation in panel data
H0: no first-order autocorrelation
    F(  1,    1084) =    216.002
           Prob > F =      0.0000
Code:

Then, I checked for group-wise heteroskedasticity (using command xttest3) and found presence of the same. Below is the concerned output.






Code:


Modified Wald test for groupwise heteroskedasticity
in fixed effect regression model

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

chi2 (1264)  =  2.6e+36
Prob>chi2 =      0.0000




Code:



Finally, I checked for cross-sectional dependence using xtcdf and found presence of cross-sectional dependence. Here is the result.






Code:


quietly: xtreg Profitability4 Size2 Leverage1 CurrentRatio SalesGro CapitalExpenditure2
>  WPromoterSharesin1 AD_Totalremuneration i.Year, fe

. predict res, r
(15,392 missing values generated)

. xtcdf Profitability4 res

xtcd test on variables Profitability4 res
Panelvar: CompanyID
Timevar: Year
------------------------------------------------------------------------------+
    Variable    |  CD-test   p-value   average joint T | mean ρ   mean abs(ρ) |
----------------+--------------------------------------+----------------------|
 Profitability4 +  119.953    0.000         13.24      +  0.03       0.31     | 54693 com
> binations of panel units ignored (insufficient joint observations).
      res       +  1.985      0.047          8.29      +  0.00       0.17     | 843986 co
> mbinations of panel units ignored (insufficient joint observations).
------------------------------------------------------------------------------+
 Notes: Under the null hypothesis of cross-section independence, CD ~ N(0,1)
        P-values close to zero indicate data are correlated across panel groups.




Code:







I have the following questions:



1. I would like to know if I have run the xtcdf correctly. Also, what does presence of cross-sectional dependence mean intuitively?

2. Since my data set exhibits serial correlation, heteroscedasticity and cross-sectional dependence, should I use xtreg, fe cluster(CompanyID) or xtscc, fe? What are the relevant criteria for choosing one of the these two commands?

3. While using xtscc, I realised that it does not support use of factor variables. In that case, should I manually create time dummies and introduce them in the model?

4. How should we select the number of lags in case of xtscc?



Thanks and Regards,

Prateek