r2001: insufficient observations panel data

[Matthias De Herdt]

Hi everyone,

For my master thesis I am trying to evaluate the evolution of the container liner shipping industry between 2000-2019. For this I gathered a dataset which starts with 20 different companies but due to mergers, bankruptcies and lost data, I only have 8 companies by 2019. For every year, I have data surrounding its market share, average costs, its average capacity and a dummy variable. Whenever I try to run an xtreg, I get the error code r(2001) that there are insufficient observations. I've tried to search on the forum if someone had the same issue in the past but without success. Often you ask for the dataex command so I will provide it below to be sure.

. dataex ID Year lnMS100 lnavc AvTEUCAP DummyAL

----------------------- copy starting from the next line -----------------------

* Example generated by -dataex-. For more info, type help dataex
clear
input int(ID Year) double(lnMS100 lnavc AvTEUCAP) byte DummyAL
  1 2000  -3.142577827841428   .25541370954537124  2701.194805194805 1
  2 2000  -5.195039418142751    .5272147257257073  1483.888888888889 0
  3 2000 -3.6691296264462334    .5272147257257073 1706.2222222222222 0
  4 2000 -3.1875719348816136    .5272147257257073 1380.8402777777778 0
  5 2000  -4.235231711720422    .5272147257257073 1621.9767441860465 0
  6 2000  -4.021842367400227    .5272147257257073 1199.0972222222222 0
  7 2000 -3.8475936941410693   -.6316802077384022 2389.9767441860463 1
  8 2000  -2.980306053773459    .4108803992114169 2912.3333333333335 1
  9 2000  -3.753716702486806    .8023687048752312 2213.4117647058824 1
 10 2000 -2.0498355230780354    .5272147257257073 2199.7304964539007 0
 11 2000  -5.676656460133953    .5272147257257073 1375.0833333333333 0
 12 2000  -4.748665460431981    .5272147257257073 1346.3870967741937 1
 13 2000  -3.566871240944357    .5272147257257073 2159.9206349206347 1
 14 2000 -3.3668494624118686    .5272147257257073 2103.8734177215188 1
 15 2000 -3.8645213797241116    .5272147257257073  2349.860465116279 1
 16 2000  -5.208419434957451    .5272147257257073          823.59375 0
 17 2000  -4.162736009151584    .5272147257257073 1666.4222222222222 0
 18 2000  -4.328643916058393    .5272147257257073               1155 0
 19 2000 -3.9437430002519833    .5272147257257073               2593 1
 20 2000 -3.5926046301192605    .5272147257257073 1744.9736842105262 0
 21 2001 -3.1506453943724537   .19006465156868063  2769.679012345679 1
 22 2001  -5.497588648070576    .5272147257257073 1650.8461538461538 0
 23 2001  -3.609112220448567   .02736347026153056 1751.1358024691358 0
 24 2001 -3.2353674590498973    .5272147257257073  1824.070796460177 0
 25 2001  -3.989816280771454    .5272147257257073  1795.037037037037 0
 26 2001 -3.8619012058358804   -.7983165690890951 1197.3804347826087 0
 27 2001   -3.80927073997414    .5665590633979939             3628.5 1
 28 2001  -3.010777254274865    .4254126455392841  3146.621951219512 1
 29 2001 -3.6477944511226434    .7169475871473403  2200.967741935484 1
 30 2001  -2.021276215231871   .16424041369321932 2336.8821548821547 0
 31 2001  -5.645190759340897    .5272147257257073 1424.3076923076924 0
 32 2001  -4.840303584952445    .5272147257257073 1380.3333333333333 1
 33 2001 -3.6324287199259198    .5272147257257073  2131.892307692308 1
 34 2001 -3.4244574552340974    .5272147257257073 1983.8139534883721 1
 35 2001 -3.7030760332846913  .006466851205782546 2690.0208333333335 1
 36 2001  -5.067621497269431    .5272147257257073  942.5714285714286 0
 37 2001  -4.318005743664967    .5272147257257073 1837.1842105263158 0
 38 2001 -4.3871950776005955    .5272147257257073 1142.9122807017543 0
 39 2001 -3.8395491927238874    .5272147257257073  2503.311111111111 1
 40 2001 -3.6827224711045967    .5272147257257073 1757.0133333333333 0
 41 2002 -3.2092411784320127   .08925139120041857 2990.4155844155844 1
 42 2002  -5.469613785661368    .5272147257257073  1715.642857142857 0
 43 2002  -3.378412484892208  -.18889661909975522 2025.2604166666667 0
 44 2002  -3.210410095795776    .5272147257257073 1965.7521367521367 0
 45 2002  -4.136303599653312    .5272147257257073 2070.8636363636365 0
 46 2002 -3.7192145135924735   -.6099483777334297 1707.0987654320988 0
 47 2002 -3.7933007900856883    .6721181435018257 3566.6944444444443 1
 48 2002  -2.973617954320472   .49490842785964584 3349.9080459770116 1
 49 2002  -3.557774813876204    .7191350538553968 2663.9508196721313 1
 50 2002  -2.069356379617951   .22707965640731465 2407.6688963210704 0
 51 2002  -5.812895448072045    .5272147257257073               1420 0
 52 2002  -4.740604640917288    .5272147257257073               1556 1
 53 2002  -3.668111076315416    .5272147257257073 2425.4166666666665 1
 54 2002 -3.4844275658805866    .5272147257257073 2132.5365853658536 1
 55 2002 -3.6578291232398397  -.10056457811052427  3128.276595744681 1
 56 2002 -5.1555639861224165  -1.9050681547350554  913.3611111111111 0
 57 2002  -4.340899987014789  -.29600623257005015            2062.75 0
 58 2002  -4.381071878906438   -.7146900089995538 1188.9166666666667 0
 59 2002  -3.829072966054631  -.17038167542556182 2949.7380952380954 1
 60 2002 -3.7638934514207896   .07379711910496739 1944.6029411764705 0
 61 2003 -3.2552653059638166   .16250243859662916  2002.795081967213 1
 62 2003  -5.478989903803495    .5303107135428466          826.21875 0
 63 2003 -3.2952408232088963  -.20876727530950737  2235.866666666667 0
 64 2003 -3.2738413845887226    .5272147257257073 3285.5342465753424 0
 65 2003  -4.026840587279942    .5272147257257073 1283.5795454545455 0
 66 2003   -3.72389556985238    -.557397540253148   1935.73417721519 0
 67 2003 -3.7947197026463355   .17021518203996514 3850.4594594594596 1
 68 2003  -3.027226678522224     .507373709624662 3568.8953488372094 1
 69 2003 -3.5569088919214615    .8500497540495568  2657.573529411765 1
 70 2003  -2.045929179693251    .2845667597841793 2583.1230283911673 0
 71 2003  -5.918266575187958    .5272147257257073  896.8421052631579 0
 72 2003  -4.870618173015101    .5272147257257073 1868.4615384615386 1
 73 2003 -3.6266985202746467   .49910889859170193  2856.491525423729 1
 74 2003 -3.4209180852765915   .07402418146281867  2379.770114942529 1
 75 2003 -3.7282076726846234  -.05717296910571845          1903.3125 1
 76 2003  -5.165821252860165   -1.889060067908781 1063.5882352941176 0
 77 2003   -4.48888518105156   -.3603431286434301 2033.1714285714286 0
 78 2003  -4.346464716650142   -.6635461569897616  1465.232142857143 0
 79 2003 -3.9766665060257536  -.16596170635084304         3711.46875 1
 80 2003  -3.658443199091601   .06785431911554918 3401.3958333333335 0
 81 2004 -3.2280442793466935   .07475027418620901  3386.390243902439 1
 82 2004  -5.457204835753502    .7368471596750873            1867.75 0
 83 2004 -3.0887728488960167   -.2851550441996342 2059.2258064516127 0
 84 2004  -3.389007000462504   -.3111720708830461 2129.7207207207207 0
 85 2004  -3.848423007857333    .4579535606973005         2333.15625 0
 86 2004 -3.5972775054723125   -.5655745620249409 1999.5104166666667 0
 87 2004 -3.7521039261430698    .3055557117118877 3867.5208333333335 1
 88 2004 -3.2022599526657194   .44964141328287505  3699.974358974359 1
 89 2004 -3.5376195799281005     .850712709603479  3041.089552238806 1
 90 2004  -2.030098952577813   .31304198481282697  2591.692957746479 0
 91 2004  -5.939246906710693    .5272147257257073                  . 0
 92 2004  -5.155005441654641    .6522321906443238 1757.7391304347825 1
 93 2004 -3.6142477243276447    .4203126106805727  3145.383333333333 1
 94 2004 -3.3277930703821195   .22472125345582736   2761.78021978022 1
 95 2004  -3.644096994401177  -.07670244610139512  3330.418181818182 1
 96 2004  -5.181828797982159  -1.8705274005883137 1035.7368421052631 0
 97 2004  -4.588487634601949   -.2597455613673898 2587.0333333333333 0
 98 2004  -4.346386525417256   -.5935627184352682             1396.2 0
 99 2004  -3.905782349986651 -.023336884331167734 2660.3396226415093 1
100 2004 -3.6784630726470646     .136278622245621  2106.964285714286 0
end

------------------ copy up to and including the previous line ------------------

Listed 100 out of 317 observations
Use the count() option to list more


Do you think there is a problem with the way my panel data is structured or do I really have insufficient observations?

Thank you in advance and kind regards,
Matthias De Herdt

[Carlo Lazzaro]

Matthias:
welcome to this forum
The issue is probably trivial.
You have one ID per each observation, which is fine for a cross-sectional database but insufficient (as Stata complains) for a panel dataset, where the same -panelid- is measured on the same set of variables at (theoretically) equally time-spaced intervals.