Hello all. For my thesis I'm researching the capital structure in the UK and France. More specifically, I need to capture the differences in capital structure between the UK and France. I have unbalanced panel data, clustered at firm level. My dependent variable is the leverage ratio and independent variables are profitability, size, asset growth, age and collateral. My data looks like this, but for lot's of firms in the UK and France


FirmAge BvDIDNumber year country Founding Year Leverage Profitability Collateral Size AssetGrowth DummyCountry
4 121580 2009 GB 2005 6.835131 -4.763282 .2543254 9.702473 -.5688832 1
5 121580 2010 GB 2005 2.48559 -5.911988 .267345 9.006877 -.5012533 1
6 121580 2011 GB 2005 .9377793 .7685989 .7642363 9.978038 1.641211 1
7 121580 2012 GB 2005 1.424916 1.030651 .3686646 10.35933 .4641946 1
8 121580 2013 GB 2005 1.907116 -.5167642 .4044732 10.08251 -.2418143 1
9 121580 2014 GB 2005 1.666307 -.2464925 .2784373 9.539644 -.4189381 1
10 121580 2015 GB 2005 3.015105 -.1529442 .0774213 10.19865 .9329448 1


I'm fairly new to STATA, but according to my research, I should use FE or RE when dealing with panel data.
The Hausman test told me to go with FE. However, my regression always omits the CountryDummy due to collinairity.
When using the RE model, I have the same issue. These are commands is used for the FE model with the result:

xtset BvDIDNumber year, yearly
xtreg W_LeverageW_
Profitability Collateral Size AssetGrowth FirmAge i.year DummyCountry, fe robust

Fixed-effects (within) regression Number of obs = 1,520,805
Group variable: BvDIDNumber Number of groups = 365,738

R-squared: Obs per group:
Within = 0.0149 min = 1
Between = 0.0180 avg = 4.2
Overall = 0.0203 max = 9

F(17,1155050) = 1030.03
corr(u_i, Xb) = -0.0356 Prob > F = 0.0000

---------------------------------------------------------------------------------
W_Leverage | Coefficient Std. err. t P>|t| [95% conf. interval]
----------------+----------------------------------------------------------------
W_Profitability | -.1755274 .0284945 -6.16 0.000 -.2313756 -.1196791
Collateral | .1492874 .0278396 5.36 0.000 .0947227 .2038521
Size | -.3854391 .0035752 -107.81 0.000 -.3924463 -.3784319
Growth | 2.83e-09 2.70e-09 1.05 0.295 -2.46e-09 8.12e-09
FirmAge | .177337 .0059341 29.88 0.000 .1657063 .1889677
|
year |
2008 | -.1392909 .0737492 -1.89 0.059 -.2838368 .0052551
2009 | -.063765 .0654566 -0.97 0.330 -.1920577 .0645278
2010 | -.0558726 .059235 -0.94 0.346 -.1719712 .060226
2011 | .0323748 .0536347 0.60 0.546 -.0727473 .1374969
2012 | .0451677 .0482439 0.94 0.349 -.0493886 .139724
2013 | .0179986 .0429419 0.42 0.675 -.0661662 .1021633
2014 | -.0223605 .0378232 -0.59 0.554 -.0964927 .0517716
2015 | .0039274 .0330422 0.12 0.905 -.0608343 .0686891
2016 | -.0053064 .0289801 -0.18 0.855 -.0621064 .0514937
2017 | .0004413 .0253577 0.02 0.986 -.0492589 .0501415
2018 | .02575 .0226593 1.14 0.256 -.0186614 .0701613
2019 | .097358 .02119 4.59 0.000 .0558264 .1388896
2020 | 0 (omitted)
|
DummyCountry | 0 (omitted)
_cons | 4.70828 .0640685 73.49 0.000 4.582708 4.833852
----------------+----------------------------------------------------------------
sigma_u | 6.7545334
sigma_e | 4.5279624
rho | .68994961 (fraction of variance due to u_i)
---------------------------------------------------------------------------------
F test that all u_i=0: F(365737, 1155050) = 7.30 Prob > F = 0.0000

So my question is: How can I run a regression which allows me to capture the difference in capital structure between the UK and France?

Thanks in advance.