Hi all!

First time posting here.

I am writing research on digitalization in EU28 and its economic effect. After doing a FE model such as this:

Code:
 xtreg y x1 x2 i.year, fe vce (robust)
As a small additional check for my previous findings, I was hoping to introduce one period lag of my dependent variable, in my case, real GDP per capita (RGDPpc). This leads to me having a dynamic panel for which I received suggestion to use Arellano-Bond estimator. I understand that this leads to endogeneity problem and I have read papers mentioned below the code, so I have a general understanding what AB estimator do, such as, that instruments are created by "using first differences of the strictly exogenous variables" and multiple lags of dependent variable, yet here are things that I am not sure of.
  1. I read that first-differencing removes panel fixed effects. Does that mean country specific effects are eliminated and I have to only include time dummies as I have done in an example below or should I include country dummies as well?
  2. Does suppressing constant affects results? I read that in original AB (1991) paper it did not but is there occasion that this is not true?
  3. Since my data is expressed in growth rates (by first-differencing natural log of my variables), except for inflation, I was thinking whether additional first-differencing that is done by STATA to find instruments is somewhat a problem?
  4. Lastly, I was wondering whether two step estimator is needed here? I read about Windmeijer bias correction but I am not sure what that is and what are the occasions one shuld use two step estimator? (after I introduce "twostep" I get the following error: variance-covariance matrix of the two-step estimator is not full rank. Two-step estimator is not available. One-step estimator is available and variance-covariance matrix provides correct coverage. ")
Any other suggestions?

I understand that some parts of this is fairly simple for some, yet dynamic panels are absolutely new for me, so any help is highly appreciated. Please let me know if additional information is required.
( I ran estat abond and I reject no autocorrelation of order 1 and cannot reject no autocorrelation of order 2).


Code:
. xtabond lnRGDPPC lnfix_net lncell_sub lnnet_user lnger_ter lngcon lntopen lngcf  lninflation
///_Iyear_2002 - _Iyear_2017, vce(robust) noconstant

Arellano-Bond dynamic panel-data estimation     Number of obs     =        351
Group variable: country1                        Number of groups  =         27
Time variable: year
                                                Obs per group:
                                                              min =          2
                                                              avg =         13
                                                              max =         15

Number of instruments =    143                  Wald chi2(24)     =   39057.21
                                                Prob > chi2       =     0.0000
One-step results
                               (Std. Err. adjusted for clustering on country1)
------------------------------------------------------------------------------
             |               Robust
    lnRGDPPC |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    lnRGDPPC |
         L1. |    .170156    .094328     1.80   0.071    -.0147236    .3550355
             |
   lnfix_net |  -.0002524   .0046447    -0.05   0.957    -.0093558     .008851
  lncell_sub |   .0376404   .0271245     1.39   0.165    -.0155227    .0908035
  lnnet_user |   .0053039   .0086888     0.61   0.542    -.0117259    .0223336
   lnger_ter |   .0858762   .0409437     2.10   0.036      .005628    .1661243
      lngcon |   .2420834    .039317     6.16   0.000     .1650236    .3191432
     lntopen |   .0328535   .0211607     1.55   0.121    -.0086207    .0743276
       lngcf |   .1425929   .0143577     9.93   0.000     .1144524    .1707335
 lninflation |  -.0010479   .0006515    -1.61   0.108    -.0023249    .0002291
 _Iyear_2002 |          0  (omitted)
 _Iyear_2003 |  -.0063436   .0048963    -1.30   0.195    -.0159401    .0032529
 _Iyear_2004 |   .0035061   .0048961     0.72   0.474    -.0060901    .0131023
 _Iyear_2005 |   .0008608   .0067311     0.13   0.898    -.0123318    .0140535
 _Iyear_2006 |   .0036587   .0056125     0.65   0.514    -.0073415     .014659
 _Iyear_2007 |   .0080905    .007153     1.13   0.258    -.0059291    .0221102
 _Iyear_2008 |    -.01364   .0052185    -2.61   0.009     -.023868    -.003412
 _Iyear_2009 |   -.034101   .0079815    -4.27   0.000    -.0497445   -.0184575
 _Iyear_2010 |   .0065017   .0090098     0.72   0.471    -.0111572    .0241607
 _Iyear_2011 |  -.0003967   .0068669    -0.06   0.954    -.0138556    .0130623
 _Iyear_2012 |  -.0050726   .0058925    -0.86   0.389    -.0166217    .0064764
 _Iyear_2013 |   .0012146   .0062783     0.19   0.847    -.0110906    .0135197
 _Iyear_2014 |   .0025448   .0083946     0.30   0.762    -.0139084     .018998
 _Iyear_2015 |   .0064822   .0119633     0.54   0.588    -.0169654    .0299298
 _Iyear_2016 |   .0004811   .0069569     0.07   0.945    -.0131541    .0141163
 _Iyear_2017 |   .0075268   .0092821     0.81   0.417    -.0106658    .0257194
------------------------------------------------------------------------------
Instruments for differenced equation
        GMM-type: L(2/.).lnRGDPPC
        Standard: D.lnfix_net D.lncell_sub D.lnnet_user D.lnger_ter D.lngcon
                  D.lntopen D.lngcf D.lninflation D._Iyear_2002
                  D._Iyear_2003 D._Iyear_2004 D._Iyear_2005 D._Iyear_2006
                  D._Iyear_2007 D._Iyear_2008 D._Iyear_2009 D._Iyear_2010
                  D._Iyear_2011 D._Iyear_2012 D._Iyear_2013 D._Iyear_2014
                  D._Iyear_2015 D._Iyear_2016 D._Iyear_2017
Aforementioned papers:
https://blog.stata.com/2015/11/12/xtabond-cheat-sheet/
https://core.ac.uk/download/pdf/6490419.pdf
https://www.stata.com/manuals13/xtxtabond.pdf