Hello everyone, I am working on a panel data set whose time period goes from 2004 to 2016. I am experiencing an issue with time dummies both when using i.Year and when generating time dummies manually as STATA keeps on using 2 base groups instead of 1.

My dataset is coded in this way:
Code:
.  . xtset countrynum Year, yearly
       panel variable:  countrynum (strongly balanced)
        time variable:  Year, 2004 to 2016
                delta:  1 year

.
When using i.Year STATA uses both 2004 and 2005 as base years:
Code:
. reg Y I logYlevel_1 n H  i.countrynum Cor_1 i.countrynum##c.Cor_1 i.Year, vce(cluster countrynu
> m)
note: Cor_1 omitted because of collinearity

Linear regression                               Number of obs     =        240
                                                F(14, 19)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7647
                                                Root MSE          =     .01438

                                  (Std. Err. adjusted for 20 clusters in countrynum)
------------------------------------------------------------------------------------
                   |               Robust
                 Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
                 I |  -.0050199   .0195443    -0.26   0.800    -.0459266    .0358867
       logYlevel_1 |  -.1255014   .0508644    -2.47   0.023    -.2319618    -.019041
                 n |  -.0001286   .0003074    -0.42   0.680    -.0007721    .0005148
                 H |   .1810461   .1962326     0.92   0.368    -.2296734    .5917656
                   |
        countrynum |
                2  |  -.0075186   .0115144    -0.65   0.522    -.0316185    .0165812
                3  |  -.0415829   .0185308    -2.24   0.037    -.0803684   -.0027975
                4  |  -.0301643   .0216167    -1.40   0.179    -.0754087      .01508
                5  |   .0385532   .0177765     2.17   0.043     .0013464    .0757599
                6  |   .0338513   .0113286     2.99   0.008     .0101402    .0575623
                7  |   .0341033   .0208821     1.63   0.119    -.0096034    .0778101
                8  |    .023549   .0119514     1.97   0.064    -.0014656    .0485635
                9  |   .0537951   .0334736     1.61   0.125     -.016266    .1238563
               10  |    .008647   .0057067     1.52   0.146    -.0032972    .0205912
               11  |  -.0228318   .0093685    -2.44   0.025    -.0424402   -.0032233
               12  |   .0125716   .0159917     0.79   0.441    -.0208994    .0460427
               13  |  -.0263945   .0187979    -1.40   0.176    -.0657389    .0129498
               14  |  -.0221471   .0113101    -1.96   0.065    -.0458194    .0015251
               15  |  -.0336907   .0185583    -1.82   0.085    -.0725337    .0051524
               16  |   .0114023   .0125498     0.91   0.375    -.0148647    .0376693
               17  |   .0544347   .0217663     2.50   0.022     .0088773    .0999922
               18  |  -.0102997   .0046371    -2.22   0.039    -.0200052   -.0005942
               19  |   .0412845   .0238289     1.73   0.099      -.00859     .091159
               20  |   .0377269   .0146951     2.57   0.019     .0069696    .0684842
                   |
             Cor_1 |  -44.65295   475.2509    -0.09   0.926    -1039.364    950.0586
             Cor_1 |          0  (omitted)
                   |
countrynum#c.Cor_1 |
                2  |  -785.9514     338.93    -2.32   0.032     -1495.34   -76.56274
                3  |  -350.8146   914.5333    -0.38   0.706    -2264.955    1563.326
                4  |   29.94349   449.2771     0.07   0.948    -910.4044    970.2914
                5  |   909.2216   706.9965     1.29   0.214     -570.539    2388.982
                6  |  -797.9921   222.6642    -3.58   0.002    -1264.034   -331.9506
                7  |    -308.33   548.4422    -0.56   0.581    -1456.233    839.5728
                8  |  -62.57157   447.8015    -0.14   0.890     -999.831    874.6878
                9  |   372.6863   449.6995     0.83   0.418    -568.5455    1313.918
               10  |   75.53298    746.382     0.10   0.920    -1486.663    1637.728
               11  |   -32.4799   463.6609    -0.07   0.945    -1002.933    937.9734
               12  |   1929.619    461.482     4.18   0.001     963.7258    2895.512
               13  |  -957.3895   506.8818    -1.89   0.074    -2018.305    103.5263
               14  |   1648.217   965.5464     1.71   0.104    -372.6945    3669.129
               15  |   53.18744   615.2624     0.09   0.932    -1234.572    1340.947
               16  |    2202.39   565.7829     3.89   0.001     1018.192    3386.587
               17  |   638.5813   549.3248     1.16   0.259    -511.1688    1788.331
               18  |   327.0107    517.551     0.63   0.535     -756.236    1410.257
               19  |    582.496   405.3486     1.44   0.167    -265.9084      1430.9
               20  |   9.871007   1133.115     0.01   0.993    -2361.765    2381.507
                   |
              Year |
             2006  |   .0142296   .0039022     3.65   0.002     .0060622     .022397
             2007  |   .0049212   .0039376     1.25   0.227    -.0033202    .0131626
             2008  |  -.0247142   .0052067    -4.75   0.000    -.0356119   -.0138166
             2009  |   -.065904   .0061165   -10.77   0.000    -.0787059   -.0531021
             2010  |  -.0084701   .0080807    -1.05   0.308    -.0253833     .008443
             2011  |  -.0142801   .0077827    -1.83   0.082    -.0305695    .0020092
             2012  |   -.044804   .0102844    -4.36   0.000    -.0663294   -.0232785
             2013  |  -.0459268   .0135691    -3.38   0.003    -.0743273   -.0175263
             2014  |  -.0290396   .0113149    -2.57   0.019     -.052722   -.0053573
             2015  |  -.0111417   .0152856    -0.73   0.475    -.0431348    .0208515
             2016  |  -.0155312   .0126094    -1.23   0.233    -.0419229    .0108605
                   |
             _cons |   1.252449   .5100886     2.46   0.024     .1848215    2.320077
------------------------------------------------------------------------------------
When I manually calculate time dummies, I use 2004 as a base group, but STATA says that 2016 was omitted for multicollinearity:
Code:
. reg Y I logYlevel_1 n H  i.countrynum Cor_1 i.countrynum##c.Cor_1 d2005 d2006 d2007 d2008 d2009
>  d2010 d2011 d2012 d2013 d2014 d2015 d2016 , vce(cluster countrynum)
note: Cor_1 omitted because of collinearity
note: d2016 omitted because of collinearity

Linear regression                               Number of obs     =        240
                                                F(14, 19)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7647
                                                Root MSE          =     .01438

                                  (Std. Err. adjusted for 20 clusters in countrynum)
------------------------------------------------------------------------------------
                   |               Robust
                 Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
                 I |  -.0050199   .0195443    -0.26   0.800    -.0459266    .0358867
       logYlevel_1 |  -.1255014   .0508644    -2.47   0.023    -.2319618    -.019041
                 n |  -.0001286   .0003074    -0.42   0.680    -.0007721    .0005148
                 H |   .1810461   .1962326     0.92   0.368    -.2296734    .5917656
                   |
        countrynum |
                2  |  -.0075186   .0115144    -0.65   0.522    -.0316185    .0165812
                3  |  -.0415829   .0185308    -2.24   0.037    -.0803684   -.0027975
                4  |  -.0301643   .0216167    -1.40   0.179    -.0754087      .01508
                5  |   .0385532   .0177765     2.17   0.043     .0013464    .0757599
                6  |   .0338513   .0113286     2.99   0.008     .0101402    .0575623
                7  |   .0341033   .0208821     1.63   0.119    -.0096034    .0778101
                8  |    .023549   .0119514     1.97   0.064    -.0014656    .0485635
                9  |   .0537951   .0334736     1.61   0.125     -.016266    .1238563
               10  |    .008647   .0057067     1.52   0.146    -.0032972    .0205912
               11  |  -.0228318   .0093685    -2.44   0.025    -.0424402   -.0032233
               12  |   .0125716   .0159917     0.79   0.441    -.0208994    .0460427
               13  |  -.0263945   .0187979    -1.40   0.176    -.0657389    .0129498
               14  |  -.0221471   .0113101    -1.96   0.065    -.0458194    .0015251
               15  |  -.0336907   .0185583    -1.82   0.085    -.0725337    .0051524
               16  |   .0114023   .0125498     0.91   0.375    -.0148647    .0376693
               17  |   .0544347   .0217663     2.50   0.022     .0088773    .0999922
               18  |  -.0102997   .0046371    -2.22   0.039    -.0200052   -.0005942
               19  |   .0412845   .0238289     1.73   0.099      -.00859     .091159
               20  |   .0377269   .0146951     2.57   0.019     .0069696    .0684842
                   |
             Cor_1 |  -44.65295   475.2509    -0.09   0.926    -1039.364    950.0586
             Cor_1 |          0  (omitted)
                   |
countrynum#c.Cor_1 |
                2  |  -785.9514     338.93    -2.32   0.032     -1495.34   -76.56274
                3  |  -350.8146   914.5333    -0.38   0.706    -2264.955    1563.326
                4  |   29.94349   449.2771     0.07   0.948    -910.4044    970.2914
                5  |   909.2216   706.9965     1.29   0.214     -570.539    2388.982
                6  |  -797.9921   222.6642    -3.58   0.002    -1264.034   -331.9506
                7  |    -308.33   548.4422    -0.56   0.581    -1456.233    839.5728
                8  |  -62.57157   447.8015    -0.14   0.890     -999.831    874.6878
                9  |   372.6863   449.6995     0.83   0.418    -568.5455    1313.918
               10  |   75.53298    746.382     0.10   0.920    -1486.663    1637.728
               11  |   -32.4799   463.6609    -0.07   0.945    -1002.933    937.9734
               12  |   1929.619    461.482     4.18   0.001     963.7258    2895.512
               13  |  -957.3895   506.8818    -1.89   0.074    -2018.305    103.5263
               14  |   1648.217   965.5464     1.71   0.104    -372.6945    3669.129
               15  |   53.18744   615.2624     0.09   0.932    -1234.572    1340.947
               16  |    2202.39   565.7829     3.89   0.001     1018.192    3386.587
               17  |   638.5813   549.3248     1.16   0.259    -511.1688    1788.331
               18  |   327.0107    517.551     0.63   0.535     -756.236    1410.257
               19  |    582.496   405.3486     1.44   0.167    -265.9084      1430.9
               20  |   9.871007   1133.115     0.01   0.993    -2361.765    2381.507
                   |
             d2005 |   .0155312   .0126094     1.23   0.233    -.0108605    .0419229
             d2006 |   .0297608   .0104419     2.85   0.010     .0079056    .0516161
             d2007 |   .0204524   .0107642     1.90   0.073    -.0020774    .0429822
             d2008 |   -.009183   .0113028    -0.81   0.427    -.0328401     .014474
             d2009 |  -.0503728   .0090671    -5.56   0.000    -.0693504   -.0313952
             d2010 |   .0070611   .0079591     0.89   0.386    -.0095974    .0237196
             d2011 |   .0012511   .0063774     0.20   0.847     -.012097    .0145992
             d2012 |  -.0292728   .0047347    -6.18   0.000    -.0391825    -.019363
             d2013 |  -.0303956   .0096392    -3.15   0.005    -.0505708   -.0102204
             d2014 |  -.0135084   .0036453    -3.71   0.002    -.0211382   -.0058787
             d2015 |   .0043896   .0062192     0.71   0.489    -.0086274    .0174065
             d2016 |          0  (omitted)
             _cons |   1.236918   .5037766     2.46   0.024     .1825014    2.291334
-----------------------------------------------------------------------------------
The same happens to 2004 if I use 2016 as a base group:
Code:
. reg Y I logYlevel_1 n H  i.countrynum Cor_1 i.countrynum##c.Cor_1 d2004 d2005 d2006 d2007 d2008
>  d2009 d2010 d2011 d2012 d2013 d2014 d2015 , vce(cluster countrynum)
note: Cor_1 omitted because of collinearity
note: d2004 omitted because of collinearity

Linear regression                               Number of obs     =        240
                                                F(14, 19)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7647
                                                Root MSE          =     .01438

                                  (Std. Err. adjusted for 20 clusters in countrynum)
------------------------------------------------------------------------------------
                   |               Robust
                 Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
                 I |  -.0050199   .0195443    -0.26   0.800    -.0459266    .0358867
       logYlevel_1 |  -.1255014   .0508644    -2.47   0.023    -.2319618    -.019041
                 n |  -.0001286   .0003074    -0.42   0.680    -.0007721    .0005148
                 H |   .1810461   .1962326     0.92   0.368    -.2296734    .5917656
                   |
        countrynum |
                2  |  -.0075186   .0115144    -0.65   0.522    -.0316185    .0165812
                3  |  -.0415829   .0185308    -2.24   0.037    -.0803684   -.0027975
                4  |  -.0301643   .0216167    -1.40   0.179    -.0754087      .01508
                5  |   .0385532   .0177765     2.17   0.043     .0013464    .0757599
                6  |   .0338513   .0113286     2.99   0.008     .0101402    .0575623
                7  |   .0341033   .0208821     1.63   0.119    -.0096034    .0778101
                8  |    .023549   .0119514     1.97   0.064    -.0014656    .0485635
                9  |   .0537951   .0334736     1.61   0.125     -.016266    .1238563
               10  |    .008647   .0057067     1.52   0.146    -.0032972    .0205912
               11  |  -.0228318   .0093685    -2.44   0.025    -.0424402   -.0032233
               12  |   .0125716   .0159917     0.79   0.441    -.0208994    .0460427
               13  |  -.0263945   .0187979    -1.40   0.176    -.0657389    .0129498
               14  |  -.0221471   .0113101    -1.96   0.065    -.0458194    .0015251
               15  |  -.0336907   .0185583    -1.82   0.085    -.0725337    .0051524
               16  |   .0114023   .0125498     0.91   0.375    -.0148647    .0376693
               17  |   .0544347   .0217663     2.50   0.022     .0088773    .0999922
               18  |  -.0102997   .0046371    -2.22   0.039    -.0200052   -.0005942
               19  |   .0412845   .0238289     1.73   0.099      -.00859     .091159
               20  |   .0377269   .0146951     2.57   0.019     .0069696    .0684842
                   |
             Cor_1 |  -44.65295   475.2509    -0.09   0.926    -1039.364    950.0586
             Cor_1 |          0  (omitted)
                   |
countrynum#c.Cor_1 |
                2  |  -785.9514     338.93    -2.32   0.032     -1495.34   -76.56274
                3  |  -350.8146   914.5333    -0.38   0.706    -2264.955    1563.326
                4  |   29.94349   449.2771     0.07   0.948    -910.4044    970.2914
                5  |   909.2216   706.9965     1.29   0.214     -570.539    2388.982
                6  |  -797.9921   222.6642    -3.58   0.002    -1264.034   -331.9506
                7  |    -308.33   548.4422    -0.56   0.581    -1456.233    839.5728
                8  |  -62.57157   447.8015    -0.14   0.890     -999.831    874.6878
                9  |   372.6863   449.6995     0.83   0.418    -568.5455    1313.918
               10  |   75.53298    746.382     0.10   0.920    -1486.663    1637.728
               11  |   -32.4799   463.6609    -0.07   0.945    -1002.933    937.9734
               12  |   1929.619    461.482     4.18   0.001     963.7258    2895.512
               13  |  -957.3895   506.8818    -1.89   0.074    -2018.305    103.5263
               14  |   1648.217   965.5464     1.71   0.104    -372.6945    3669.129
               15  |   53.18744   615.2624     0.09   0.932    -1234.572    1340.947
               16  |    2202.39   565.7829     3.89   0.001     1018.192    3386.587
               17  |   638.5813   549.3248     1.16   0.259    -511.1688    1788.331
               18  |   327.0107    517.551     0.63   0.535     -756.236    1410.257
               19  |    582.496   405.3486     1.44   0.167    -265.9084      1430.9
               20  |   9.871007   1133.115     0.01   0.993    -2361.765    2381.507
                   |
             d2004 |          0  (omitted)
             d2005 |   .0155312   .0126094     1.23   0.233    -.0108605    .0419229
             d2006 |   .0297608   .0104419     2.85   0.010     .0079056    .0516161
             d2007 |   .0204524   .0107642     1.90   0.073    -.0020774    .0429822
             d2008 |   -.009183   .0113028    -0.81   0.427    -.0328401     .014474
             d2009 |  -.0503728   .0090671    -5.56   0.000    -.0693504   -.0313952
             d2010 |   .0070611   .0079591     0.89   0.386    -.0095974    .0237196
             d2011 |   .0012511   .0063774     0.20   0.847     -.012097    .0145992
             d2012 |  -.0292728   .0047347    -6.18   0.000    -.0391825    -.019363
             d2013 |  -.0303956   .0096392    -3.15   0.005    -.0505708   -.0102204
             d2014 |  -.0135084   .0036453    -3.71   0.002    -.0211382   -.0058787
             d2015 |   .0043896   .0062192     0.71   0.489    -.0086274    .0174065
             _cons |   1.236918   .5037766     2.46   0.024     .1825014    2.291334
------------------------------------------------------------------------------------

.

Why do you think this is the case?