Dear Statalisters,

I would like to do a fixed effect regression using 28 European countries across a 1969-2016 timeframe. my problem is that I have a very unbalanced panel. My independent variable is an index which is computable only for the years shown below while my dependent variable would be available every year.
Code:
xtdescribe, pattern(50)

      id:  1, 2, ..., 28                                     n =         28
    year:  1967, 1969, ..., 2016                             T =         44
           Delta(year) = 1 unit
           Span(year)  = 50 periods
           (id*year uniquely identifies each observation)

Distribution of T_i:   min      5%     25%       50%       75%     95%     max
                         2       2       6         8         9      13      27

     Freq.  Percent    Cum. |  Pattern
 ---------------------------+----------------------------------------------------
        1      3.57    3.57 |  ...........................................1..1...
        1      3.57    7.14 |  ...........................................1..1..1
        1      3.57   10.71 |  .......................................1...1..1..1
        1      3.57   14.29 |  .....................................1..1..1......
        1      3.57   17.86 |  .................................1...1..1..1..1...
        1      3.57   21.43 |  .................................1...1..1..11.1111
        1      3.57   25.00 |  ..............................1.1....1..1..1.1....
        1      3.57   28.57 |  ............................1....1...1..1..1..1...
        1      3.57   32.14 |  ............................1.1...................
        1      3.57   35.71 |  .........................1...1.......1..1..1..1...
        1      3.57   39.29 |  .........................1...1.....1.1..1..1..1...
        1      3.57   42.86 |  ........................1..1....1.....1.1.1..1..1.
        1      3.57   46.43 |  ....................1......11.1..1...1..1..1..1...
        1      3.57   50.00 |  ....................1......111...1...1..1..1......
        1      3.57   53.57 |  ....................1....1..1....1...1..1..1..1...
        1      3.57   57.14 |  ....................1...1...1....1...1..1..1..1...
        1      3.57   60.71 |  ...................1.....1..1...1....1..1..1..1..1
        1      3.57   64.29 |  ...................11.1.1.1.1..1.1...1...1.1...1..
        1      3.57   67.86 |  ..................1.....1..1..1..1...1..1..1..1...
        1      3.57   71.43 |  ..................1..1...1..1.1..1................
        1      3.57   75.00 |  ................1...1..1..1.....1....1..1..1..1...
        1      3.57   78.57 |  ...............1.........1.......1.1.1..1..1..1...
        1      3.57   82.14 |  .............1....1....1....1....1...1..1..1..1..1
        1      3.57   85.71 |  ............1......1....1...1....1...1..1..1..1...
        1      3.57   89.29 |  ...........1.....1....1....1.....1....1....1......
        1      3.57   92.86 |  ......1....1..1.11..1.1.1..11..1.1111111111111111.
        1      3.57   96.43 |  ..1....1....1......1....1..11...1....1..1..1..1..1
        1      3.57  100.00 |  1.......1.....1.....1....1..1....1....1...........
 ---------------------------+----------------------------------------------------
       28    100.00         |  X.X...XXX..XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
Is it possible to run the fe regression? How should I deal with the missing data?
Thanks for the help!