Dear all,

I have an unbalanced panel of 57,910 observations of country, industries and year (2003-2018). And I would like to pick values of value added per worker in 2005. Nevertheless, when I do this on my panel I get that my coefficients are omitted for collinearity. My data now has no duplicates. So, my issue is that perhaps I am not using the right sintax to get the initial values in 2005. Any advice? Thank you very much!



* Example generated by -dataex-. To install: ssc install dataex
clear
Code:
 input int(country year isic1) float(country_industry TotalValueAdded logval_worker tradability_output tradability_country)
 8 2010 1010  1    96789712  8.800137   .1768752 .08869135
 8 2011 1010  1   125793104   8.74405  .15556923  .0863666
 8 2012 1010  1   176615488  8.695241   .1463699 .09472585
 8 2013 1010  1   131003208  9.109263    .164018 .14183685
 8 2014 1010  1   163158896  8.896569  .14443323 .13885614
 8 2015 1010  1   123891064  8.491784  .13452409 .12520152
 8 2016 1010  1   149982240  8.632782   .1765093 .11871612
 8 2017 1010  1   193711168  8.778877   .1774767 .14302167
 8 2018 1010  1   225976368  8.933749   .1989122 .14653176
 8 2010 1030  2    96789712  8.862595    .215029 .08869135
 8 2011 1030  2   125793104  8.762699  .21581225  .0863666
 8 2012 1030  2   176615488  8.792838  .20265244 .09472585
 8 2013 1030  2   131003208  8.798987  .20287557 .14183685
 8 2014 1030  2   163158896   9.24072  .19782813 .13885614
 8 2015 1030  2   123891064  8.477221  .20720184 .12520152
 8 2016 1030  2   149982240  8.561826  .27469403 .11871612
 8 2017 1030  2   193711168  8.420509  .26632798 .14302167
 8 2018 1030  2   225976368  8.732944  .26901108 .14653176
 8 2010 1040  3    96789712  10.06337   .3355838 .08869135
 8 2011 1040  3   125793104  9.008738  .19421376  .0863666
 8 2012 1040  3   176615488  9.875433   .2092457 .09472585
 8 2013 1040  3   131003208  9.586471  .17979157 .14183685
 8 2014 1040  3   163158896   9.45741  .17748743 .13885614
 8 2015 1040  3   123891064  8.265269   .1502877 .12520152
 8 2016 1040  3   149982240  8.601744  .24313246 .11871612
 8 2017 1040  3   193711168   8.94572  .24658133 .14302167
 8 2018 1040  3   225976368  9.221366  .27100095 .14653176
 8 2010 1050  4    96789712  9.241973  .12098086 .08869135
 8 2011 1050  4   125793104  9.180054  .11871654  .0863666
 8 2012 1050  4   176615488   8.78597   .1152698 .09472585
 8 2013 1050  4   131003208  8.432419  .14063852 .14183685
 8 2014 1050  4   163158896  8.729236  .11514153 .13885614
 8 2015 1050  4   123891064  8.724345  .11546322 .12520152
 8 2016 1050  4   149982240   8.84583  .13292608 .11871612
 8 2017 1050  4   193711168  8.945738  .14246953 .14302167
 8 2018 1050  4   225976368  9.014386   .1586218 .14653176
 8 2010 1410  5    96789712  8.425086   .2258532 .08869135
 8 2011 1410  5   125793104  8.540539    .388695  .0863666
 8 2012 1410  5   176615488  8.541057   .3685393 .09472585
 8 2013 1410  5   131003208    8.6199   .4107426 .14183685
 8 2014 1410  5   163158896  8.638366   .4123004 .13885614
 8 2015 1410  5   123891064  8.292302   .4005206 .12520152
 8 2016 1410  5   149982240  8.294022   .3923832 .11871612
 8 2017 1410  5   193711168  8.441474   .4230156 .14302167
 8 2018 1410  5   225976368  8.549866    .440155 .14653176
 8 2011 1910  6   125793104  9.159176  .14866973  .0863666
 8 2012 1910  6   176615488 10.614596   .1523459 .09472585
 8 2014 1910  6   163158896   8.74985  .17065017 .13885614
 8 2015 1910  6   123891064   7.74456  .16286217 .12520152
 8 2016 1910  6   149982240  7.694532   .1238466 .11871612
 8 2017 1910  6   193711168  10.03203  .13627516 .14302167
 8 2018 1910  6   225976368 10.130532  .13455296 .14653176
 8 2010 3100  7    96789712  8.986774   .2543435 .08869135
 8 2011 3100  7   125793104  9.029225   .3122739  .0863666
 8 2012 3100  7   176615488   9.05458  .31815135 .09472585
 8 2013 3100  7   131003208  9.016403  .29301417 .14183685
 8 2014 3100  7   163158896  9.176045  .28281972 .13885614
 8 2015 3100  7   123891064  8.728418  .28148833 .12520152
 8 2016 3100  7   149982240  8.708357   .2639583 .11871612
 8 2017 3100  7   193711168  8.844979   .2826954 .14302167
 8 2018 3100  7   225976368  8.803402  .31619525 .14653176
12 2011 1010  8 75196186624         .  .15556923 .12106317
12 2012 1010  8 70800785408         .   .1463699 .13205482
12 2013 1010  8 66283483136         .    .164018 .13740344
12 2014 1010  8 61726912512         .  .14443323  .1576208
12 2015 1010  8 34376491008         .  .13452409 .11134155
12 2011 1020  9 75196186624         .   .3592764 .12106317
12 2012 1020  9 70800785408         .  .34193125 .13205482
12 2013 1020  9 66283483136         .  .29112867 .13740344
12 2014 1020  9 61726912512         .  .29428324  .1576208
12 2015 1020  9 34376491008         .  .27611375 .11134155
12 2011 1030 10 75196186624         .  .21581225 .12106317
12 2012 1030 10 70800785408         .  .20265244 .13205482
12 2013 1030 10 66283483136         .  .20287557 .13740344
12 2014 1030 10 61726912512         .  .19782813  .1576208
12 2015 1030 10 34376491008         .  .20720184 .11134155
12 2011 1040 11 75196186624         .  .19421376 .12106317
12 2012 1040 11 70800785408         .   .2092457 .13205482
12 2013 1040 11 66283483136         .  .17979157 .13740344
12 2014 1040 11 61726912512         .  .17748743  .1576208
12 2015 1040 11 34376491008         .   .1502877 .11134155
12 2011 1050 12 75196186624         .  .11871654 .12106317
12 2012 1050 12 70800785408         .   .1152698 .13205482
12 2013 1050 12 66283483136         .  .14063852 .13740344
12 2014 1050 12 61726912512         .  .11514153  .1576208
12 2015 1050 12 34376491008         .  .11546322 .11134155
12 2011 1072 13 75196186624         .  .13218853 .12106317
12 2012 1072 13 70800785408         .  .12412757 .13205482
12 2013 1072 13 66283483136         .   .1235223 .13740344
12 2014 1072 13 61726912512         .  .11877646  .1576208
12 2015 1072 13 34376491008         .  .11726826 .11134155
12 2011 1080 14 75196186624         .  .06792859 .12106317
12 2012 1080 14 70800785408         . .063373916 .13205482
12 2013 1080 14 66283483136         .  .06100389 .13740344
12 2014 1080 14 61726912512         .  .06142768  .1576208
12 2015 1080 14 34376491008         .  .05720979 .11134155
12 2011 1103 15 75196186624         .   .1048784 .12106317
12 2012 1103 15 70800785408         .  .10637137 .13205482
12 2013 1103 15 66283483136         .  .11095482 .13740344
12 2014 1103 15 61726912512         .  .10666358  .1576208
end