Singleton dummy variable (possible problem)

[Hugo Rocha]

Dear all,

I am running a couple of regressions with country and year fixed effects. But, in some regressions, when I include dummies for countries, F statistic goes missing (so the problem is certainly a singleton dummy somewhere, because the sample size is enough for the degrees of freedom). Countries in the dataset are represented as numbers. Any possible suggestion on how to solve this problem and locate the singleton dummy? Thank you! ( I did not put the tab countries due to the excess of characters allowed)

 * Example generated by -dataex-. To install: ssc install dataex
clear
input float country1 int year str2 isic float inv_rate1 str3 isiccomb byte sourcecode double(OutputINDSTAT4 Wages) float(emp gdp_percapita TotalOutput coeff_diversi)
840 1980 "36"  .02465116 "36" 3    4.300e+10   1.006e+10 103.07093  31725.71 1.4288206e+12 .7828951
124 1970 "15"  .03108122 "15" 3   9397453982  1325392470   8.15579  23772.37   98669453312  .771994
840 1993 "33"  .03249149 "33" 3   1.2631e+11  3.0341e+10  123.1207  41300.26  1.735673e+12 .8016322
840 1973 "27" .032639198 "27" 3    6.771e+10   1.361e+10  89.76096  28467.86  1.287729e+12  .789232
840 1971 "36" .022700815 "36" 3    1.718e+10   4.810e+09  84.70138 26059.816 1.1757533e+12 .7877562
840 1966 "27"  .05572354 "27" 3    4.630e+10   9.420e+09  78.84691 23837.215 1.0717137e+12 .7844567
124 1989 "26"  .06191513 "26" 3   7762007885  1555780035 13.236956 35763.516  1.786803e+11 .7766514
840 2004 "19" .014050784 "19" 1   5756974121  1096890991 140.27019  53076.24 2.9361835e+12 .9224685
124 1988 "24"  .04129102 "24" 3  22531874111  2834969664 12.978824 35440.508  177239048192 .7860352
840 1998 "17" .033607107 "17" 1  97078156250 16714824219  134.5009  47120.55  3.131152e+12 .9413515
840 2003 "23" .033053238 "23" 1 222849875000  5173883789 138.69086  51581.71 2.8813335e+12 .9245498
124 1982 "17"  .03036053 "17" 3   4271581823   971845656 10.984604  30183.06  127023939584 .7614031
840 1980 "17" .028521126 "17" 3    5.680e+10   1.111e+10 103.07093  31725.71 1.4288206e+12 .7828951
124 1970 "25"  .06435644 "25" 3   1160676065   277719521   8.15579  23772.37   98669453312  .771994
840 2013 "22"  .02656869 "22" 3  82425482000 19874717000 145.97845  56153.92 2.7011915e+12 .8281536
124 1979 "25"  .04223744 "25" 3   3739038982   782807933 10.760995 30416.396  138993172480 .7792382
840 1997 "26"  .05279192 "26" 1  97446468750 17231816406 132.36258  45674.03 3.0052516e+12 .9421328
124 1983 "36" .013669065 "36" 3   4511478304  1186291597 11.076824  30654.63  134779363328 .7679245
124 1975 "16"   .0233853 "16" 3    882851157   115026264  9.654721 27061.703  123320745984  .773169
124 1964 "20"  .04039735 "20" 3   1399965511   340256518  7.201654  19730.25   7.54404e+10  .769388
840 2003 "35"  .01864969 "35" 1 158765171875 30109058594 138.69086  51581.71 2.8813335e+12 .9245498
840 2012 "29" .025993686 "29" 3 395091867000 58412509000 144.58849     55552  2.659329e+12 .8266457
124 1970 "22"  .04039776 "22" 3   1540864512   581295686   8.15579  23772.37   98669453312  .771994
124 1969 "22" .035920464 "22" 3   1447833868   535856409  8.164087 23481.746   9.63015e+10 .7776658
840 1969 "23"  .04379861 "23" 3    2.443e+10   1.370e+09  84.23369  25700.67 1.1903348e+12 .7891335
840 1989 "36" .021874525 "36" 3    6.583e+10   1.512e+10 121.82807   39646.8 1.6576732e+12 .8044491
840 1977 "36"  .02674772 "36" 3    3.290e+10   8.110e+09  96.26191 30044.285 1.4170328e+12 .7924358
840 1976 "36"  .02789855 "36" 3    2.760e+10   6.940e+09  93.08827  28982.56 1.3292258e+12 .7863804
840 2003 "18" .008491283 "18" 1  35554578125  5658536133 138.69086  51581.71 2.8813335e+12 .9245498
124 1979 "21" .065928854 "21" 3  10798822630  2106837490 10.760995 30416.396  138993172480 .7792382
840 2004 "15"   .0235957 "15" 1 584906625000 52151515625 140.27019  53076.24 2.9361835e+12 .9224685
840 1971 "27"  .04151962 "27" 3    4.817e+10   1.041e+10  84.70138 26059.816 1.1757533e+12 .7877562
840 1978 "23"  .02208293 "23" 3    1.037e+11   3.000e+09 100.19444 31413.426 1.4627904e+12 .7929254
840 2013 "20" .035359234 "20" 3  88617589000 13399120000 145.97845  56153.92 2.7011915e+12 .8281536
840 1991 "27"  .04650017 "27" 3   1.2172e+11   2.046e+10 121.56706  39587.73 1.6336614e+12 .8001903
840 1977 "28"  .02936118 "28" 3    8.140e+10   1.830e+10  96.26191 30044.285 1.4170328e+12 .7924358
840 2000 "30"  .02253478 "30" 1 112952679688 11015568359 138.63611  50205.23 3.1705056e+12 .9420096
840 1975 "24"  .06949891 "24" 3    9.180e+10   1.172e+10  90.27315 27752.486 1.2275606e+12 .7793719
124 1979 "22"  .03245436 "22" 3   4208553009  1376956593 10.760995 30416.396  138993172480 .7792382
840 2010 "31"  .02235981 "31" 3 110225982000 16555225000  140.7138  54371.41  2.477068e+12 .8355898
840 2009 "25"  .03106351 "25" 3 171403278000 27402191000 141.22081  53480.25 2.3697901e+12  .839965
124 1973 "17"  .04424779 "17" 3   3050725435   711935926   9.09335 26566.717  122023444480 .7768121
840 2003 "28" .029430447 "28" 1 229887328125 54458734375 138.69086  51581.71 2.8813335e+12 .9245498
840 1994 "17" .034872964 "17" 3  1.01626e+11  1.8138e+10 125.68998  42520.34 1.8012163e+12 .8045634
840 1999 "28"  .04088608 "28" 1 243248296875 58651789063 136.75647  48762.61 3.2182575e+12 .9413739
124 1974 "15"  .02477184 "15" 3  17253261187  2042907186  9.562041 27039.414  133928755200 .7765449
840 1992 "20" .021414176 "20" 3    5.954e+10  1.0294e+10   121.797  40591.29 1.7067297e+12 .8025618
840 1998 "36"  .02916295 "36" 1 131397531250 27978519531  134.5009  47120.55  3.131152e+12 .9413515
124 1987 "26"  .04255066 "26" 3   6327381271  1259442994 12.543772 34422.844  159211159552 .7861783
840 1972 "25"   .0501894 "25" 3    2.112e+10   5.160e+09  86.97282  27187.73 1.2567706e+12 .7931709
124 1984 "36" .015064103 "36" 3   4818287253  1237774754 11.369482  32116.95  138367156224 .7711541
840 2010 "16"  .01009832 "16" 3  39202752000   940695000  140.7138  54371.41  2.477068e+12 .8355898
840 2007 "26"  .05725816 "26" 1 149943468750 21730236328 146.39578     55989  3.080468e+12 .9066486
124 1967 "24"  .10014836 "24" 3   2499281549   453319242  7.906885   21828.6   88298528768 .7727897
124 1985 "28"  .04150943 "28" 3  10091489828  2145723164 11.795504 33246.566  139898568704 .7775148
124 1965 "28"  .04169884 "28" 3   2402633063   588134889  7.508637 20638.375   80182960128 .7723618
840 1981 "33"  .04139344 "33" 3    4.880e+10   1.156e+10 104.21618 32227.516 1.4228834e+12 .7818055
840 1966 "26" .064363144 "26" 3    1.476e+10   3.840e+09  78.84691 23837.215 1.0717137e+12 .7844567
840 1963 "22" .028307693 "22" 3    1.625e+10   5.510e+09 73.074265  20620.72  9.030245e+11 .7825109
840 1970 "17" .034317344 "17" 3    2.710e+10   6.090e+09  84.69689   25454.2  1.155691e+12 .7854229
840 2006 "21"  .04456621 "21" 1 170360546875 20639992188 145.09415  55483.83  3.047019e+12 .9147386
840 2005 "31"  .02032121 "31" 1  1.30258e+11  2.3512e+10  142.4933  54449.45  3.008504e+12 .9174208
840 1971 "28" .024568394 "28" 3    4.518e+10   1.183e+10  84.70138 26059.816 1.1757533e+12 .7877562
124 1965 "15"  .02775453 "15" 3   6651304658   902610799  7.508637 20638.375   80182960128 .7723618
840 1979 "25"  .04672305 "25" 3    4.730e+10   1.015e+10 102.81062 32106.373 1.4935535e+12 .7893529
840 2003 "26"  .04630388 "26" 1   1.1051e+11 18970273438 138.69086  51581.71 2.8813335e+12 .9245498
840 1987 "16" .022115385 "16" 3    2.080e+10   1.490e+09  116.8861  37408.96  1.595493e+12 .8057776
840 2011 "18" .015910074 "18" 3  12523260000  2726990000 142.14735  54758.74 2.5623357e+12 .8250764
124 1988 "17"   .0383815 "17" 3   7028514643  1487769978 12.978824 35440.508  177239048192 .7860352
840 1982 "24"  .05319025 "24" 3    1.724e+11   2.156e+10 103.40858  31350.66  1.331578e+12 .7829695
840 2009 "26"  .04197488 "26" 3  89583516000 15942407000 141.22081  53480.25 2.3697901e+12  .839965
124 1963 "17"  .03931034 "17" 3   1344442446   305976557  6.961045 18873.299   6.87436e+10 .7681732
840 1985 "24"  .04111498 "24" 3    2.009e+11   2.434e+10 111.38438 35609.535  1.430635e+12 .7960103
124 1963 "23" .032214765 "23" 3   1381530513   101992186  6.961045 18873.299   6.87436e+10 .7681732
840 1992 "25"  .04210254 "25" 3   1.1605e+11   2.323e+10   121.797  40591.29 1.7067297e+12 .8025618
840 1983 "16"   .0398773 "16" 3    1.630e+10   1.350e+09 104.77914 32480.977  1.365531e+12 .7898316
840 1964 "24"  .05108724 "24" 3    3.817e+10   6.900e+09  74.73962 21509.076  9.721075e+11 .7795107
840 1993 "21"  .05589624 "21" 3  1.27683e+11  1.9902e+10  123.1207  41300.26  1.735673e+12 .8016322
124 1984 "33"  .04025157 "33" 3   1227736656   333573733 11.369482  32116.95  138367156224 .7711541
840 2002 "15" .030331217 "15" 1 525586687500 51187167969 138.15208  50589.63  2.986348e+12 .9304876
840 2010 "23" .019689966 "23" 3 627770571000  8433885000  140.7138  54371.41  2.477068e+12 .8355898
840 1998 "34"  .03475203 "34" 1 414918843750 43991316406  134.5009  47120.55  3.131152e+12 .9413515
840 1986 "25"  .04093887 "25" 3    7.328e+10   1.528e+10   113.924  36499.08  1.443684e+12 .7996418
840 2010 "19" .020039143 "19" 3   4844369000   860174000  140.7138  54371.41  2.477068e+12 .8355898
124 1989 "36" .007243243 "36" 3   7812684759  2234850148 13.236956 35763.516  1.786803e+11 .7766514
840 2015 "23"  .02969718 "23" 3 507785122000 10357030000 150.24847  58514.89  2.737627e+12 .8383057
840 1975 "21"  .06522782 "21" 3    4.170e+10   6.990e+09  90.27315 27752.486 1.2275606e+12 .7793719
840 1972 "24"  .04644119 "24" 3    5.943e+10   9.340e+09  86.97282  27187.73 1.2567706e+12 .7931709
840 1991 "36"  .01871698 "36" 3    6.625e+10   1.509e+10 121.56706  39587.73 1.6336614e+12 .8001903
840 2012 "35"  .01716096 "35" 3 277483202000 45690906000 144.58849     55552  2.659329e+12 .8266457
840 1994 "15"   .0234226 "15" 3  4.30994e+11  3.8492e+10 125.68998  42520.34 1.8012163e+12 .8045634
124 1979 "27"  .05571531 "27" 3  11874436583  2076105663 10.760995 30416.396  138993172480 .7792382
124 1964 "26"  .08118812 "26" 3    936400772   222511075  7.201654  19730.25   7.54404e+10  .769388
840 2015 "27"  .02589473 "27" 3 228434073000 23380366000 150.24847  58514.89  2.737627e+12 .8383057
840 1963 "20" .035928145 "20" 3    8.350e+09   2.140e+09 73.074265  20620.72  9.030245e+11 .7825109
840 2004 "36" .020689776 "36" 1 141610906250 28483798828 140.27019  53076.24 2.9361835e+12 .9224685
840 1999 "19" .016028171 "19" 1   9673218750  1759656982 136.75647  48762.61 3.2182575e+12 .9413739
840 1999 "32"  .06077582 "32" 1 235089140625 36713621094 136.75647  48762.61 3.2182575e+12 .9413739
124 1975 "36"  .02130045 "36" 3   2630857123   738330979  9.654721 27061.703  123320745984  .773169
840 2012 "36" .025330657 "36" 3 215883977000 40835569000 144.58849     55552  2.659329e+12 .8266457
end

Example of a regression with country dummies

 reg l_gdp_percapita share_man i.country1 i.year, robust

Linear regression                               Number of obs     =     45,316
                                                F(177, 45132)     =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9638
                                                Root MSE          =     .20151

------------------------------------------------------------------------------
             |               Robust
l_gdp_perc~a |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   share_man |   .9188907   .0458941    20.02   0.000     .8289374    1.008844
             |
    country1 |
         12  |   .1398192   .0097238    14.38   0.000     .1207605     .158878
         31  |  -.0220833   .0236409    -0.93   0.350    -.0684199    .0242533
         32  |   1.000396   .0105811    94.55   0.000     .9796571    1.021135
         36  |   1.724077   .0098756   174.58   0.000     1.704721    1.743433
         40  |   1.650948   .0105608   156.33   0.000     1.630248    1.671647
         44  |   1.667833   .0150731   110.65   0.000     1.638289    1.697376
         48  |   1.967524    .011058   177.93   0.000      1.94585    1.989198
         50  |   -1.29537   .0119894  -108.04   0.000    -1.318869   -1.271871
         51  |   .0843728   .0281494     3.00   0.003     .0291994    .1395461
         52  |   .6119524    .012826    47.71   0.000     .5868133    .6370915
         56  |   1.526947   .0103872   147.00   0.000     1.506588    1.547306
         60  |   1.657907   .0126674   130.88   0.000     1.633078    1.682735
         68  |  -.0507294   .0159609    -3.18   0.001     -.082013   -.0194459
         70  |  -.1275699   .0263274    -4.85   0.000    -.1791721   -.0759676
         72  |   .4438411   .0114761    38.68   0.000     .4213478    .4663343
         76  |   .3688905   .0110913    33.26   0.000     .3471514    .3906296
        100  |    .361612   .0131338    27.53   0.000     .3358696    .3873545
        104  |  -1.961633    .023902   -82.07   0.000    -2.008481   -1.914784
        112  |   .6383378   .0113539    56.22   0.000     .6160839    .6605917
        116  |  -1.643725   .0109332  -150.34   0.000    -1.665154   -1.622295
        120  |  -.7420946   .0186935   -39.70   0.000    -.7787341   -.7054551
        124  |   1.788242    .010166   175.90   0.000     1.768317    1.808168
        140  |  -1.332602   .0581746   -22.91   0.000    -1.446625   -1.218578
        144  |  -.2394646   .0124757   -19.19   0.000    -.2639173    -.215012
        152  |   .6076752   .0112157    54.18   0.000     .5856922    .6296581
        156  |  -.2011489   .0311219    -6.46   0.000    -.2621484   -.1401495
        170  |   .3194332   .0100574    31.76   0.000     .2997206    .3391458
        188  |   .6719599    .013369    50.26   0.000     .6457566    .6981633
        191  |   .8065507   .0117399    68.70   0.000     .7835403    .8295611
        196  |   1.068581   .0120084    88.99   0.000     1.045044    1.092117
        203  |   1.021347   .0120049    85.08   0.000     .9978173    1.044877
        208  |   1.713557   .0106053   161.58   0.000      1.69277    1.734343
        218  |   .3025109   .0112648    26.85   0.000     .2804318    .3245901
        222  |  -.0738693   .0138399    -5.34   0.000    -.1009957    -.046743
        231  |  -2.145684   .0119943  -178.89   0.000    -2.169193   -2.122175
        233  |   .9057312   .0111763    81.04   0.000     .8838255    .9276369
        242  |   .2236346   .0106636    20.97   0.000     .2027338    .2445354
        246  |    1.43978   .0104581   137.67   0.000     1.419282    1.460278
        250  |   1.544187   .0105397   146.51   0.000     1.523529    1.564845
        266  |   1.137986   .0110765   102.74   0.000     1.116276    1.159696
        268  |   .0766702   .0136464     5.62   0.000      .049923    .1034174
        270  |  -1.162161   .0103543  -112.24   0.000    -1.182456   -1.141867
        275  |  -.5467384   .0108368   -50.45   0.000    -.5679787   -.5254981
        276  |   1.509933   .0113012   133.61   0.000     1.487783    1.532084
        288  |  -.3154668   .0410579    -7.68   0.000     -.395941   -.2349925
        300  |   1.255589   .0112735   111.38   0.000     1.233492    1.277685
        320  |    .110528   .0140347     7.88   0.000     .0830197    .1380362
        340  |  -.3263836   .0102711   -31.78   0.000    -.3465152    -.306252
        344  |   1.242486    .015634    79.47   0.000     1.211843    1.273128
        348  |   .8694839   .0110921    78.39   0.000     .8477432    .8912246
        352  |   1.624975   .0099666   163.04   0.000      1.60544     1.64451
        356  |  -.9933728   .0121642   -81.66   0.000    -1.017215   -.9695309
        360  |  -.3468424   .0120225   -28.85   0.000    -.3704068   -.3232781
        364  |   .4794817   .0177027    27.09   0.000     .4447841    .5141793
        372  |   1.657644   .0131108   126.43   0.000     1.631947    1.683341
        376  |   1.319273   .0097486   135.33   0.000     1.300166    1.338381
        380  |    1.57303   .0113083   139.10   0.000     1.550866    1.595195
        384  |  -.8037646   .0102571   -78.36   0.000    -.8238688   -.7836605
        392  |   1.406302   .0108517   129.59   0.000     1.385033    1.427572
        398  |   .8981183    .009638    93.19   0.000     .8792277     .917009
        400  |   .3052589    .012813    23.82   0.000     .2801452    .3303727
        404  |  -.5147151   .0269775   -19.08   0.000    -.5675914   -.4618389
        410  |   .6722883   .0217413    30.92   0.000      .629675    .7149016
        414  |   2.236188   .0231366    96.65   0.000      2.19084    2.281536
        418  |  -.7040705   .0458362   -15.36   0.000    -.7939102   -.6142307
        422  |    .611516   .0229675    26.63   0.000     .5664992    .6565327
        426  |   -1.56843   .0165501   -94.77   0.000    -1.600868   -1.535991
        428  |   .6195997   .0143469    43.19   0.000     .5914795      .64772
        440  |   .7144657   .0133826    53.39   0.000     .6882356    .7406958
        442  |   2.204164    .010143   217.31   0.000     2.184283    2.224044
        446  |   1.779534   .0186684    95.32   0.000     1.742943    1.816124
        450  |  -1.651845   .0120918  -136.61   0.000    -1.675545   -1.628145
        454  |  -1.883317   .0170413  -110.51   0.000    -1.916718   -1.849915
        458  |   .4775227   .0125024    38.19   0.000     .4530177    .5020277
        462  |   .6493281   .0111001    58.50   0.000     .6275717    .6710844
        470  |   .7183254   .0171533    41.88   0.000     .6847046    .7519463
        484  |   .7464449   .0112014    66.64   0.000     .7244899    .7683999
        496  |   -.184911   .0177652   -10.41   0.000    -.2197311    -.150091
        504  |  -.4884675   .0097987   -49.85   0.000    -.5076732   -.4692619
        508  |  -2.018648   .0132443  -152.42   0.000    -2.044607   -1.992689
        512  |   1.219262   .0133043    91.64   0.000     1.193186    1.245339
        524  |  -1.343939   .0101304  -132.66   0.000    -1.363795   -1.324083
        528  |   1.734882    .009824   176.60   0.000     1.715627    1.754137
        554  |   1.484114   .0124538   119.17   0.000     1.459704    1.508523
        558  |  -.0703292    .012193    -5.77   0.000    -.0942278   -.0464307
        562  |  -1.966414   .0229068   -85.84   0.000    -2.011312   -1.921517
        566  |  -.5526878   .0205543   -26.89   0.000    -.5929745    -.512401
        578  |   1.966367   .0102139   192.52   0.000     1.946347    1.986386
        586  |  -.6789311   .0105184   -64.55   0.000    -.6995474   -.6583148
        590  |   .6901412   .0100713    68.53   0.000     .6704013    .7098811
        604  |   .0505702   .0149795     3.38   0.001     .0212102    .0799302
        608  |   -.286317   .0117811   -24.30   0.000    -.3094082   -.2632258
        616  |   .6803964   .0117916    57.70   0.000     .6572846    .7035082
        620  |    1.10305   .0108115   102.03   0.000     1.081859     1.12424
        642  |   .6804005   .0117587    57.86   0.000     .6573532    .7034479
        646  |  -1.589416   .0138312  -114.91   0.000    -1.616525   -1.562306
        682  |    1.56228   .0114958   135.90   0.000     1.539748    1.584812
        686  |  -.8868662   .0249211   -35.59   0.000     -.935712   -.8380205
        702  |   1.559547   .0166446    93.70   0.000     1.526923    1.592171
        703  |   .6443317   .0118639    54.31   0.000     .6210783    .6675852
        704  |  -.8683774   .0114083   -76.12   0.000    -.8907379   -.8460169
        705  |   .9703285    .011908    81.49   0.000     .9469887    .9936683
        710  |   1.054817   .0142531    74.01   0.000     1.026881    1.082753
        716  |  -1.197127   .0099345  -120.50   0.000    -1.216599   -1.177656
        724  |   1.385057    .010179   136.07   0.000     1.365106    1.405008
        736  |  -.9589485    .010491   -91.41   0.000    -.9795111   -.9383859
        748  |  -.2198058   .0130833   -16.80   0.000    -.2454493   -.1941623
        752  |   1.631499   .0105799   154.21   0.000     1.610762    1.652235
        756  |   1.905009   .0099525   191.41   0.000     1.885502    1.924516
        762  |   -1.07388   .0117352   -91.51   0.000    -1.096881   -1.050878
        764  |    .283712   .0138427    20.50   0.000     .2565802    .3108438
        780  |   .8580207   .0157231    54.57   0.000     .8272033    .8888382
        784  |   3.482394   .0165427   210.51   0.000      3.44997    3.514818
        788  |  -.0400499   .0114344    -3.50   0.000    -.0624616   -.0176383
        792  |   .6924607   .0096331    71.88   0.000     .6735796    .7113418
        800  |   -1.13468   .0352539   -32.19   0.000    -1.203778   -1.065582
        804  |   .2291589   .0166405    13.77   0.000     .1965432    .2617746
        807  |   .2485353   .0123563    20.11   0.000     .2243168    .2727539
        818  |   -.058803   .0128072    -4.59   0.000    -.0839052   -.0337007
        826  |   1.495211   .0100999   148.04   0.000     1.475415    1.515007
        834  |  -1.494105   .0132088  -113.11   0.000    -1.519995   -1.468216
        840  |   1.830288   .0098971   184.93   0.000     1.810889    1.849686
        858  |   .5544513   .0106193    52.21   0.000     .5336374    .5752653
        860  |   .0213968   .0099338     2.15   0.031     .0019263    .0408673
        862  |  -2.202293    .014429  -152.63   0.000    -2.230574   -2.174012
        887  |  -.8229839   .0102919   -79.96   0.000    -.8431562   -.8028115
        894  |  -.3254562   .0306429   -10.62   0.000    -.3855168   -.2653957
             |
        year |
       1964  |    .093142   .0302506     3.08   0.002     .0338502    .1524338
       1965  |   .1269253   .0294211     4.31   0.000     .0692594    .1845911
       1966  |   .1174069   .0316488     3.71   0.000     .0553746    .1794391
       1967  |   .1319217   .0308946     4.27   0.000     .0713677    .1924756
       1968  |   .1874856   .0282115     6.65   0.000     .1321906    .2427806
       1969  |   .2313429   .0288315     8.02   0.000     .1748328     .287853
       1970  |   .2944888   .0281154    10.47   0.000     .2393821    .3495955
       1971  |   .3220804   .0278954    11.55   0.000     .2674049    .3767559
       1972  |   .3588911   .0275966    13.00   0.000     .3048013    .4129808
       1973  |   .3849375   .0275078    13.99   0.000     .3310217    .4388533
       1974  |   .4376506   .0266705    16.41   0.000      .385376    .4899251
       1975  |   .4207195   .0257967    16.31   0.000     .3701575    .4712815
       1976  |   .4493373   .0257377    17.46   0.000     .3988909    .4997837
       1977  |   .4619859   .0256467    18.01   0.000     .4117179    .5122539
       1978  |   .4909571   .0254936    19.26   0.000     .4409892     .540925
       1979  |   .5460373   .0255093    21.41   0.000     .4960386    .5960359
       1980  |   .5555927   .0247801    22.42   0.000     .5070233     .604162
       1981  |   .5836529    .024464    23.86   0.000     .5357032    .6316027
       1982  |   .5853933   .0244204    23.97   0.000     .5375289    .6332578
       1983  |   .5996335     .02401    24.97   0.000     .5525735    .6466934
       1984  |    .629723   .0240294    26.21   0.000     .5826251     .676821
       1985  |   .6396022   .0240536    26.59   0.000     .5924569    .6867476
       1986  |   .6677129   .0241434    27.66   0.000     .6203914    .7150345
       1987  |    .706043   .0240272    29.39   0.000     .6589493    .7531368
       1988  |   .7201399   .0241164    29.86   0.000     .6728713    .7674085
       1989  |    .727629   .0243977    29.82   0.000     .6798091    .7754488
       1990  |   .7347261    .024509    29.98   0.000     .6866881    .7827642
       1991  |   .7553216   .0240907    31.35   0.000     .7081034    .8025399
       1992  |    .786211   .0240693    32.66   0.000     .7390346    .8333873
       1993  |   .7952321   .0239937    33.14   0.000     .7482041    .8422602
       1994  |   .8156353   .0239282    34.09   0.000     .7687356     .862535
       1995  |    .819727   .0237128    34.57   0.000     .7732496    .8662045
       1996  |   .8351929   .0239033    34.94   0.000      .788342    .8820438
       1997  |   .8775972   .0238985    36.72   0.000     .8307558    .9244386
       1998  |   .8968982   .0237906    37.70   0.000     .8502683    .9435282
       1999  |   .9371042   .0237903    39.39   0.000     .8904749    .9837335
       2000  |    .972243   .0239075    40.67   0.000     .9253838    1.019102
       2001  |   .9855313   .0238646    41.30   0.000     .9387562    1.032306
       2002  |   1.017459   .0239096    42.55   0.000      .970596    1.064322
       2003  |   1.031339    .023939    43.08   0.000     .9844183     1.07826
       2004  |   1.084362   .0238365    45.49   0.000     1.037642    1.131081
       2005  |   1.118332   .0237818    47.02   0.000     1.071719    1.164945
       2006  |   1.164148   .0237877    48.94   0.000     1.117523    1.210772
       2007  |   1.211904   .0239643    50.57   0.000     1.164933    1.258874
       2008  |   1.227434    .023992    51.16   0.000     1.180409    1.274459
       2009  |   1.203944   .0241581    49.84   0.000     1.156593    1.251294
       2010  |   1.230624   .0239956    51.29   0.000     1.183592    1.277656
       2011  |   1.259778    .024245    51.96   0.000     1.212257    1.307299
       2012  |   1.264025   .0242692    52.08   0.000     1.216457    1.311593
       2013  |   1.276914   .0244094    52.31   0.000     1.229071    1.324757
       2014  |   1.298817   .0243788    53.28   0.000     1.251034      1.3466
       2015  |   1.322773   .0244492    54.10   0.000     1.274852    1.370694
       2016  |   1.335156   .0245274    54.44   0.000     1.287082     1.38323
       2017  |   1.367187   .0247622    55.21   0.000     1.318653    1.415721
       2018  |   1.364428   .0248158    54.98   0.000     1.315788    1.413067
             |
       _cons |   7.884736   .0258162   305.42   0.000     7.834136    7.935336
------------------------------------------------------------------------------

[Clyde Schechter]

by country1, sort: gen byte is_singleton = (_N == 1)
list country1 if is_singleton

[Hugo Rocha]

Thank you very much. For now, the variable is_singleton gives me 0 (which proves that my hypothesis was wrong). But I also have enough degrees of freedom...I will think more about the potential problem, which I think is the following:

I merged industry level data with country level data. So, some variables are repeated. For instance, population is the same for country year and industry while value added is only the same for country, industry and year. Could that be a problem in the regressions?

For instance, I regress one coefficient that measures how spread are activities (diversification) (one per country year) and hc (one per country year) with country and year fixed effects. If I drop country fixed effects, the F statistics shows up

 reg coeff_diversi hc i.year i.country1 if coeff_diversi!=0, robust

Linear regression                               Number of obs     =     43,431
                                                F(165, 43259)     =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7821
                                                Root MSE          =     .06269

------------------------------------------------------------------------------
             |               Robust
coeff_dive~i |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          hc |   .0231033   .0033971     6.80   0.000     .0164449    .0297616
             |
        year |
       1964  |   .0070322   .0048791     1.44   0.150     -.002531    .0165953
       1965  |   .0146178   .0049385     2.96   0.003     .0049383    .0242973
       1966  |   .0227623   .0047333     4.81   0.000      .013485    .0320396
       1967  |   .0425662   .0043228     9.85   0.000     .0340934    .0510391
       1968  |   .0469698   .0041906    11.21   0.000     .0387561    .0551835
       1969  |   .0467264   .0046817     9.98   0.000     .0375501    .0559027
       1970  |   .0468719   .0042532    11.02   0.000     .0385355    .0552083
       1971  |   .0507616   .0043498    11.67   0.000      .042236    .0592872
       1972  |   .0479324   .0043003    11.15   0.000     .0395037    .0563612
       1973  |   .0542467   .0043189    12.56   0.000     .0457816    .0627119
       1974  |   .0479649   .0042969    11.16   0.000      .039543    .0563868
       1975  |   .0522091   .0046413    11.25   0.000      .043112    .0613062
       1976  |   .0440663    .004159    10.60   0.000     .0359146    .0522179
       1977  |   .0494056   .0044711    11.05   0.000     .0406421     .058169
       1978  |   .0546773   .0046082    11.87   0.000     .0456453    .0637094
       1979  |   .0588964   .0044809    13.14   0.000     .0501137    .0676791
       1980  |   .0567194   .0045112    12.57   0.000     .0478774    .0655615
       1981  |   .0588611   .0044438    13.25   0.000     .0501513     .067571
       1982  |    .045586   .0043547    10.47   0.000     .0370507    .0541213
       1983  |   .0536755   .0043265    12.41   0.000     .0451954    .0621555
       1984  |   .0483774   .0042507    11.38   0.000      .040046    .0567088
       1985  |   .0467919   .0042871    10.91   0.000     .0383891    .0551948
       1986  |   .0473375   .0043733    10.82   0.000     .0387657    .0559093
       1987  |    .047974   .0043502    11.03   0.000     .0394476    .0565004
       1988  |   .0550064   .0043826    12.55   0.000     .0464163    .0635964
       1989  |   .0495036   .0045009    11.00   0.000     .0406817    .0583256
       1990  |   .0605602   .0045997    13.17   0.000     .0515448    .0695757
       1991  |   .0846971   .0047603    17.79   0.000     .0753669    .0940274
       1992  |   .0958856   .0048163    19.91   0.000     .0864456    .1053257
       1993  |   .1053437   .0048447    21.74   0.000     .0958481    .1148393
       1994  |   .1179111   .0047373    24.89   0.000      .108626    .1271963
       1995  |   .1374344   .0047293    29.06   0.000     .1281649    .1467038
       1996  |   .1429373   .0048319    29.58   0.000     .1334667    .1524079
       1997  |   .1400917   .0049773    28.15   0.000      .130336    .1498474
       1998  |    .138634   .0050463    27.47   0.000     .1287432    .1485247
       1999  |   .1497352   .0049694    30.13   0.000     .1399951    .1594754
       2000  |    .140914   .0050945    27.66   0.000     .1309286    .1508993
       2001  |   .1421135   .0050155    28.33   0.000     .1322829    .1519441
       2002  |   .1424849   .0051584    27.62   0.000     .1323743    .1525954
       2003  |   .1437489   .0050302    28.58   0.000     .1338897    .1536082
       2004  |   .1332971   .0050419    26.44   0.000     .1234148    .1431794
       2005  |   .1311122   .0051443    25.49   0.000     .1210294    .1411951
       2006  |   .1375866   .0050268    27.37   0.000     .1277339    .1474392
       2007  |   .1305009   .0051599    25.29   0.000     .1203873    .1406145
       2008  |   .1243996   .0051589    24.11   0.000      .114288    .1345112
       2009  |   .1043273   .0051375    20.31   0.000     .0942576    .1143969
       2010  |   .1063189   .0052756    20.15   0.000     .0959785    .1166592
       2011  |   .0976709   .0054594    17.89   0.000     .0869703    .1083715
       2012  |   .0990249   .0055229    17.93   0.000     .0881999      .10985
       2013  |   .0888747   .0053974    16.47   0.000     .0782958    .0994537
       2014  |   .0863951   .0054407    15.88   0.000     .0757312    .0970589
       2015  |   .0957632   .0055477    17.26   0.000     .0848897    .1066368
       2016  |   .0993834   .0055856    17.79   0.000     .0884355    .1103314
       2017  |   .0984421   .0057871    17.01   0.000     .0870994    .1097849
       2018  |   .0889737   .0056371    15.78   0.000     .0779248    .1000225
             |
    country1 |
         12  |  -.2740049   .0110094   -24.89   0.000    -.2955836   -.2524262
         32  |   .2955214   .0102822    28.74   0.000     .2753682    .3156746
         36  |   .2270897   .0105738    21.48   0.000     .2063649    .2478146
         40  |   .2899315   .0101091    28.68   0.000     .2701175    .3097455
         48  |   .0341568   .0104149     3.28   0.001     .0137434    .0545702
         50  |   .1527019   .0109175    13.99   0.000     .1313034    .1741004
         51  |  -.0743148   .0125613    -5.92   0.000    -.0989351   -.0496944
         52  |  -.1264611   .0110368   -11.46   0.000    -.1480934   -.1048287
         56  |   .1656755   .0106126    15.61   0.000     .1448747    .1864763
         68  |   .0444195   .0105831     4.20   0.000     .0236765    .0651625
         72  |  -.1153677   .0156929    -7.35   0.000    -.1461261   -.0846092
         76  |    .234378    .011241    20.85   0.000     .2123455    .2564106
        100  |   .1784771   .0102615    17.39   0.000     .1583644    .1985898
        104  |  -.1779339   .0192789    -9.23   0.000     -.215721   -.1401469
        116  |  -.1046556   .0110446    -9.48   0.000    -.1263032   -.0830079
        120  |   .1043519   .0109719     9.51   0.000     .0828469     .125857
        124  |   .2662538   .0103617    25.70   0.000     .2459446     .286563
        144  |   .1126012   .0101262    11.12   0.000     .0927536    .1324489
        152  |    .103691   .0105766     9.80   0.000     .0829606    .1244213
        156  |   .2908106     .01128    25.78   0.000     .2687016    .3129196
        170  |   .1361711   .0114632    11.88   0.000      .113703    .1586391
        188  |    .027452   .0143193     1.92   0.055    -.0006141    .0555181
        191  |   .2302249   .0101211    22.75   0.000     .2103873    .2500625
        196  |   .1547246   .0103406    14.96   0.000     .1344567    .1749924
        203  |   .2515095   .0104688    24.02   0.000     .2309904    .2720285
        208  |   .1827166   .0102675    17.80   0.000     .1625921    .2028411
        218  |   .1126458   .0102712    10.97   0.000      .092514    .1327777
        222  |   .1362511     .01138    11.97   0.000     .1139461    .1585561
        231  |    .153172   .0114799    13.34   0.000     .1306713    .1756728
        233  |   .2173635   .0146067    14.88   0.000     .1887342    .2459929
        242  |  -.0080045   .0120625    -0.66   0.507    -.0316472    .0156383
        246  |   .2341309   .0101384    23.09   0.000     .2142595    .2540023
        250  |   .2495341   .0103019    24.22   0.000     .2293422    .2697261
        266  |   .0114783   .0110105     1.04   0.297    -.0101026    .0330592
        270  |  -.0398359   .0113502    -3.51   0.000    -.0620825   -.0175894
        276  |   .2569757   .0103053    24.94   0.000      .236777    .2771743
        288  |   .1950263   .0115399    16.90   0.000      .172408    .2176447
        300  |   .2216812   .0101069    21.93   0.000     .2018716    .2414908
        320  |   .1499753   .0106295    14.11   0.000     .1291414    .1708093
        340  |   .1305524   .0105528    12.37   0.000     .1098687    .1512361
        344  |   .1427722    .011285    12.65   0.000     .1206534    .1648911
        348  |   .2252548   .0101113    22.28   0.000     .2054365     .245073
        352  |  -.3495205   .0134313   -26.02   0.000    -.3758461   -.3231949
        356  |   .2483412   .0107418    23.12   0.000     .2272871    .2693953
        360  |   .2217557   .0105376    21.04   0.000     .2011018    .2424096
        364  |   .1908697    .010805    17.66   0.000     .1696916    .2120477
        372  |   .0627518   .0103672     6.05   0.000     .0424319    .0830718
        376  |   .1858014   .0102474    18.13   0.000     .1657164    .2058864
        380  |   .3143102   .0100603    31.24   0.000     .2945918    .3340287
        384  |   .0735434   .0114113     6.44   0.000     .0511771    .0959098
        392  |    .280409   .0102257    27.42   0.000     .2603665    .3004516
        398  |   .0530912   .0102977     5.16   0.000     .0329074    .0732749
        400  |   .1669511    .010333    16.16   0.000     .1466982    .1872039
        404  |   .0014941   .0144975     0.10   0.918    -.0269212    .0299093
        410  |   .2968318   .0101274    29.31   0.000      .276982    .3166817
        414  |  -.1420112   .0114841   -12.37   0.000    -.1645203   -.1195022
        418  |   .0813612   .0109475     7.43   0.000      .059904    .1028184
        426  |  -.0086961   .0126677    -0.69   0.492     -.033525    .0161328
        428  |   .1532957   .0101231    15.14   0.000     .1334542    .1731372
        440  |   .2027491   .0100715    20.13   0.000     .1830088    .2224894
        442  |   .0101923   .0105423     0.97   0.334    -.0104708    .0308553
        446  |  -.0974387   .0110059    -8.85   0.000    -.1190104   -.0758671
        450  |   -.046019   .0114089    -4.03   0.000    -.0683807   -.0236573
        454  |   .0170533   .0115603     1.48   0.140    -.0056051    .0397117
        458  |   .2268676    .010114    22.43   0.000      .207044    .2466911
        462  |  -.3348532   .0107463   -31.16   0.000    -.3559161   -.3137903
        470  |   .0980504   .0103239     9.50   0.000     .0778154    .1182854
        484  |   .1779812    .010142    17.55   0.000     .1581027    .1978597
        496  |   .0023974   .0177264     0.14   0.892    -.0323467    .0371415
        504  |    .172932   .0118047    14.65   0.000     .1497946    .1960695
        508  |     .14813   .0108653    13.63   0.000     .1268337    .1694263
        524  |   .1305298   .0118673    11.00   0.000     .1072696      .15379
        528  |   .1844966   .0101437    18.19   0.000     .1646148    .2043783
        554  |   .1175206   .0116087    10.12   0.000     .0947674    .1402738
        558  |   .0879743   .0105915     8.31   0.000     .0672148    .1087339
        562  |  -.1374954   .0262762    -5.23   0.000    -.1889971   -.0859936
        566  |    .130927   .0132292     9.90   0.000     .1049974    .1568565
        578  |   .2180195   .0103005    21.17   0.000     .1978303    .2382086
        586  |   .1314931   .0111758    11.77   0.000     .1095883    .1533978
        590  |   .0079952   .0105128     0.76   0.447      -.01261    .0286003
        604  |   .2003175   .0104038    19.25   0.000     .1799258    .2207091
        608  |    .215282     .01019    21.13   0.000     .1953094    .2352546
        616  |   .2863203   .0101604    28.18   0.000     .2664058    .3062349
        620  |    .290855    .010414    27.93   0.000     .2704434    .3112665
        642  |   .2255848   .0120925    18.65   0.000     .2018833    .2492862
        646  |  -.3773645   .0166717   -22.64   0.000    -.4100413   -.3446876
        682  |   .1820516   .0107395    16.95   0.000      .161002    .2031012
        686  |  -.0838915   .0186541    -4.50   0.000    -.1204539    -.047329
        702  |   .1273215   .0102824    12.38   0.000     .1071679    .1474751
        703  |   .1928029   .0106368    18.13   0.000     .1719545    .2136513
        704  |   .2856825   .0104719    27.28   0.000     .2651573    .3062077
        705  |   .2506313   .0104383    24.01   0.000     .2301721    .2710905
        710  |    .233001   .0110177    21.15   0.000      .211406    .2545959
        716  |  -.1599331   .0106045   -15.08   0.000    -.1807181   -.1391481
        724  |   .2597114   .0101732    25.53   0.000     .2397718    .2796509
        736  |  -.0241401   .0112276    -2.15   0.032    -.0461465   -.0021337
        748  |  -.2618311   .0117498   -22.28   0.000    -.2848611   -.2388012
        752  |   .2440147    .010136    24.07   0.000      .224148    .2638814
        756  |   .1096669   .0106516    10.30   0.000     .0887896    .1305442
        762  |  -.1821556   .0114267   -15.94   0.000    -.2045521    -.159759
        764  |   .2204733   .0116248    18.97   0.000     .1976886     .243258
        780  |  -.0360495   .0107002    -3.37   0.001    -.0570222   -.0150768
        784  |   .1467737   .0111108    13.21   0.000     .1249963    .1685511
        788  |   .1066127   .0114708     9.29   0.000     .0841297    .1290956
        792  |   .2812574   .0104625    26.88   0.000     .2607507    .3017641
        800  |  -.0567918   .0145758    -3.90   0.000    -.0853606   -.0282231
        804  |   .1011144   .0128415     7.87   0.000     .0759448    .1262839
        818  |   .1820029   .0105685    17.22   0.000     .1612884    .2027175
        826  |   .2785503   .0103375    26.95   0.000     .2582885     .298812
        834  |   .0890866    .011143     7.99   0.000     .0672462     .110927
        840  |   .2771997   .0104435    26.54   0.000     .2567302    .2976692
        858  |   .0686334   .0104331     6.58   0.000     .0481842    .0890825
        862  |   .1836377   .0111876    16.41   0.000     .1617098    .2055655
        887  |  -.0419907   .0115557    -3.63   0.000    -.0646402   -.0193412
        894  |   .1961816    .010881    18.03   0.000     .1748547    .2175084
             |
       _cons |   .3959035   .0125454    31.56   0.000     .3713143    .4204927
------------------------------------------------------------------------------

[Clyde Schechter]

Look carefully at your output:

F(165, 43259)

You have 165 degrees of freedom available with this vce.

I counted up your independent variables: 170. 170 > 165. Therefore no omnibus F statistic.

What I don't understand, however, is why the degrees numerator degrees of freedom is 165. If you had used vce(cluster ...), and there were 166 clusters, that would make sense. But I don't know why the df has been reduced here with plain -robust-. I hope somebody else following along can explain that.

That said, why do you care about the overall F-test. It is a test that all of the variables (including all of those year and country dummies) are zero. Is that your research hypothesis? Do you really care to test that hypothesis? Why is it of interest? It almost never is. So before putting too much effort into investigating this, think about whether it even matters--most likely, it does not.

[Hugo Rocha]

Oh, yes. Thank you. I counted it wrongly. My question now goes specifically to the number of degrees of freedom (I thought I had more). I am pretty sure I had more but I do not understand how a simple regression with time and country dummies and a robust would not give 165 degrees of freedom. There are definitely no 166 clusters as you pointed out (that's why I did not use xtreg)

You are right. In fact, the country and year fixed effects are controls more than anything else

[Hugo Rocha]

Look carefully at your output:

F(165, 43259)

You have 165 degrees of freedom available with this vce.

I counted up your independent variables: 170. 170 > 165. Therefore no omnibus F statistic.

What I don't understand, however, is why the degrees numerator degrees of freedom is 165. If you had used vce(cluster ...), and there were 166 clusters, that would make sense. But I don't know why the df has been reduced here with plain -robust-. I hope somebody else following along can explain that.

That said, why do you care about the overall F-test. It is a test that all of the variables (including all of those year and country dummies) are zero. Is that your research hypothesis? Do you really care to test that hypothesis? Why is it of interest? It almost never is. So before putting too much effort into investigating this, think about whether it even matters--most likely, it does not.

I think I forgot to give a proper response. The reason to add country and year fixed effects is to use them as controls. Nothing in the research hypothesis is linked to the idea that those dummies have to be significant or not. Nothing more, nothing less. Can I still use these results or should I do some form of bootstrap to see if I can get a proper F statistic?

[Clyde Schechter]

The reason to add country and year fixed effects is to use them as controls. Nothing in the research hypothesis is linked to the idea that those dummies have to be significant or not. Nothing more, nothing less. Can I still use these results or should I do some form of bootstrap to see if I can get a proper F statistic?

Since you do not care about the country and year fixed effects other than as "controls" there is no reason to get an overall model F statistic here. Just use the results you already have.

[Hugo Rocha]

Look carefully at your output:

F(165, 43259)

You have 165 degrees of freedom available with this vce.

I counted up your independent variables: 170. 170 > 165. Therefore no omnibus F statistic.

What I don't understand, however, is why the degrees numerator degrees of freedom is 165. If you had used vce(cluster ...), and there were 166 clusters, that would make sense. But I don't know why the df has been reduced here with plain -robust-. I hope somebody else following along can explain that.

That said, why do you care about the overall F-test. It is a test that all of the variables (including all of those year and country dummies) are zero. Is that your research hypothesis? Do you really care to test that hypothesis? Why is it of interest? It almost never is. So before putting too much effort into investigating this, think about whether it even matters--most likely, it does not.

I keep getting this problem. I ran another type of regression. In this one, I get 152 degrees of freedom. I counted the independent variables (144 countries + 37 years) and obviously I do not have enough degrees of freedom. The issue is that I have 2471 observations (which, in theory, should grant me more degrees of freedom). I wonder what is wrong... I am not even using vce(cluster)...

[Clyde Schechter]

I'm not sure I'll have any better luck with this instance than the previous one, but please show code and output.

[Hugo Rocha]

I'm not sure I'll have any better luck with this instance than the previous one, but please show code and output.

Sure! Thank you so much! This is something I've been thinking for a while (I even thought about bootstrapping some of these regressions...)

 * Example generated by -dataex-. To install: ssc install dataex
clear
input float country1 int year float(r_valworker share_emp_high share_emp_low share_emp_medium lval_per_worker_high lval_per_worker_medium lval_per_worker_low prod_growth_high prod_growth_low prod_growth_medium ScientistsRD lScientistsRD)
 8 1988 4439.2246 .12965345  .3912511  .4790954  8.880505  7.589213  8.171848            .           .            .         .        .
 8 1989  4265.253 .12530428  .4013861 .47330955  8.895403  7.546593  8.039945     .0148983  -.13190365   -.04262018         .        .
 8 1990  2246.523  .1249325  .4126177  .4624498 8.2269945  6.984655  7.460485    -.6684084  -.57946014   -.56193733         .        .
 8 2000 2263.5276  .1582526  .4604143  .3813331  7.620377  7.834363  7.553929            .           .            .         .        .
 8 2001 2503.9985  .1751221  .4756922  .3491857  8.017388  8.095426  7.794576     .3970118   .24064684    .26106262         .        .
 8 2002  2641.915 .15242586 .51788557 .32968855  7.925795  8.317231  7.859735   -.09159374   .06515932    .22180557         .        .
 8 2004  4991.272 .14079918  .4980766  .3611242  8.592158  8.723073   8.16071      .318552   .23613167     .4208469         .        .
 8 2005  4716.539  .1637332  .4487818   .387485  8.424066  8.567766  8.193295   -.16809273   .03258419    -.1553068         .        .
 8 2006  5287.005  .1468614 .42200795 .43113065  8.402942  8.767994  8.152844  -.021123886   -.0404501    .20022774         .        .
 8 2007  6195.056 .14727657  .4692856  .3834378  8.776394   8.95278  8.241965     .3734522   .08912086    .18478584         .        .
 8 2008  7302.705 .14263852   .450509  .4068524  8.813539  9.295128  8.214221    .03714466 -.027744293     .3423481 155.52783 5.046825
 8 2009  6402.368 .14793181  .4556726  .3963956  8.676035  8.883341  8.384981   -.13750362   .17076015     -.411787         .        .
 8 2010  6174.423 .13063808  .4620707  .4072913  8.481051  9.112885  8.328651    -.1949835  -.05632973    .22954464         .        .
 8 2011  6268.898 .14645116  .5074627  .3460862  8.655917  8.956795 8.4345665    .17486572   .10591507   -.15609074         .        .
 8 2012  6349.688 .13843411  .5061126  .3554533  8.811537  8.983329  8.222886     .1556196   -.2116804    .02653408         .        .
 8 2013  6152.296 .15033917  .5122234  .3374374  8.467857  9.207172  8.251358    -.3436794  .028471947    .22384357         .        .
 8 2014  6296.575 .13161048  .5375166  .3308729  8.492803  9.237621  8.176059    .02494526  -.07529926   .030448914         .        .
 8 2015  5616.676  .1307974  .6707768 .19842575  8.581607  8.547111  8.168373    .08880424 -.007685661    -.6905107         .        .
 8 2016  5430.544  .1233472   .673796  .2028568  8.399269  8.551927  8.185474   -.18233776  .017101288   .004816055         .        .
 8 2017  7146.679  .1279655  .6884204  .1836141  8.524913  9.123482  8.209089    .12564373  .023614883    .57155514         .        .
 8 2018  7202.353 .13034825  .6928678 .17678393  8.480988   9.15999  8.247661   -.04392529   .03857136    .03650856         .        .
 8 2019  7256.068 .13035184  .6928773 .17677084  8.488389  9.167354  8.255095   .007401466  .007433891    .00736332         .        .
12 1967 11691.505 .18097174 .55794674  .2610815  9.122244  9.360679  9.438393            .           .            .         .        .
12 1968 12584.733 .18428104 .54746747 .26825148   9.25158  9.435449  9.486474    .12933636    .0480814    .07476997         .        .
12 1969 13609.748  .1845082 .53040004 .28509176  9.373878  9.537872  9.520479    .12229729  .034005165    .10242367         .        .
12 1970  15518.93 .18931597 .50712496  .3035591  9.509806  9.713778  9.610042    .13592815   .08956242     .1759062         .        .
12 1971 14432.426   .180199  .4902716  .3295294   9.32499  9.549534  9.657037    -.1848154   .04699516   -.16424465         .        .
12 1972 16590.434  .1766196  .4814773   .341903  9.521315  9.725537  9.756828    .19632435   .09979153    .17600346         .        .
12 1973 18260.172  .2009487   .417836  .3812153   9.46036  9.721846  9.903684   -.06095505   .14685535  -.003691673         .        .
12 1974 12989.005 .20602697  .4002572  .3937158  9.192734   9.41304   9.50552    -.2676258   -.3981638    -.3088055         .        .
12 1975 12118.965 .20562667  .3918453   .402528  9.147731  9.344562  9.432709   -.04500294  -.07281113  -.068478584         .        .
12 1976 13006.476 .20529114  .3838836 .41082525  9.252396  9.459433  9.459143     .1046648  .026433945    .11487103         .        .
12 1977 13078.188  .2083673  .3777309  .4139019  9.233461  9.458183  9.490875   -.01893425   .03173256 -.0012493134         .        .
12 1978 14839.333  .2023211 .38604406  .4116349 9.4358425  9.607968  9.637872    .20238113    .1469965    .14978504         .        .
12 1979 14548.896  .1864776  .4197903   .393732  9.457874  9.637605  9.556035   .022031784   -.0818367   .029636383         .        .
12 1980 13748.536  .1795429  .4457567  .3747004    9.4146  9.628469 9.4475155   -.04327393  -.10851955  -.009135246         .        .
12 1984 15143.292 .10394432 .34636346  .5496922   9.77344   9.62081 9.4109535            .           .            .         .        .
12 1985  20537.43 .09695626  .3159349 .58710885 10.282496  9.616346  9.450422     .5090561   .03946877  -.004463196         .        .
12 1986  20266.95  .1123149  .3190531 .56863195  10.12515   9.89852  9.632133   -.15734577   .18171024    .28217316         .        .
12 1987 18683.297 .11068128  .3140121  .5753066  9.970844  9.800606  9.622663    -.1543064 -.009469032   -.09791374         .        .
12 1988  16984.92 .10832198  .3116898  .5799882  9.912285  9.606123    9.5532   -.05855942  -.06946373    -.1944828         .        .
12 1989  11782.97 .11376194  .3261723 .56006575  9.588373  9.261719  9.188452    -.3239117    -.364748    -.3444042         .        .
12 1990  11477.55 .11670896  .3100426  .5732485  9.412992  9.432994  9.126344   -.17538166  -.06210804    .17127514         .        .
12 1991   7952.45 .11515048 .32071185  .5641377   9.10318  9.126975  8.472986    -.3098116   -.6533575    -.3060188         .        .
12 1992  8168.856 .12020048  .3066514 .57314813   8.89035   9.29258  8.620675    -.2128296   .14768887     .1656046         .        .
12 1993  8782.847  .1169888  .3105113  .5724999  8.974285  9.284086  8.747589    .08393478   .12691402  -.008493423         .        .
12 1994  6653.912  .1138719  .3144786  .5716495  8.696587  8.913931  8.512832   -.27769852  -.23475742    -.3701553         .        .
12 1995  6567.588 .14133923  .3220551 .53660566  8.115495  8.783136 8.5643215    -.5810919   .05148983   -.13079453         .        .
12 1996  7219.541 .16468935 .26998258 .56532806   8.11125 8.6875725  8.768592 -.0042448044   .20427036   -.09556389         .        .
12 2011  104782.7 .13354105 .45462745  .4118315 10.175012  11.77546  10.05473            .           .            .         .        .
12 2012  98154.73  .1313677  .4536118  .4150205 10.146583  11.70269  9.987966   -.02842903 -.066765785   -.07277107         .        .
12 2013  92545.44   .129225   .452762   .418013  10.15526 11.668107  9.923548   .008677483  -.06441784  -.034582138         .        .
12 2014  84594.83 .12760094 .45239365  .4200054 10.102828  11.69335  9.904133   -.05243206   -.0194149   .025242805         .        .
12 2015 73051.375 .12667717  .4525526  .4207702 10.184197 11.514767  9.733036     .0813694   -.1710968   -.17858315         .        .
12 2016  73483.45  .1266802  .4525521  .4207677  10.18996  11.52135  9.738728   .005763054  .005691528   .006583214         .        .
12 2017  73276.39 .12667243  .4525578 .42076975 10.187627 11.517197  9.736101  -.002333641 -.002626419 -.0041532516  819.3427 6.708502
31 2001 2012.2168 .31097785  .3734186  .3156036  6.393171  7.195367  6.962002            .           .            .         .        .
31 2002  2591.533 .29568484  .3400245  .3642907   6.20818  7.677098  7.232841    -.1849909   .27083874     .4817305         .        .
31 2004  3679.681 .27914184  .3183503  .4025079  6.683822  8.535518  7.299468     .2919364  -.09735966    .17204475         .        .
31 2005   4081.88 .26736712 .32261825  .4100146  7.540033  8.442768   7.16381     .8562112  -.13565826    -.0927496         .        .
31 2006  6746.218 .25891653  .3342892 .40679425  7.763603  8.629279  7.442637    .22356987    .2788272    .18651104         .        .
31 2007  8416.528 .24273303   .320222   .437045  7.986825  8.810495  7.809034    .22322226    .3663969    .18121624         .        .
31 2008 10930.525 .23819044  .3151936   .446616  7.872125  9.164552  7.697609   -.11470032  -.11142445     .3540564         .        .
31 2009 4727.7134  .2316099  .3254212  .4429689  7.812225   8.46707  8.331616   -.05990028     .634007    -.6974821         .        .
31 2010   13300.6 .28761628  .2850645  .4273192  8.227627  9.142522  8.353521     .4154019  .021904945     .6754522         .        .
31 2011  13190.36 .27537894 .29567564  .4289454  8.591687  9.250731   8.39861     .3640604   .04508877     .1082096         .        .
31 2012  14811.11   .314645 .29571843 .38963655  8.672541  9.514072  8.275123    .08085346  -.12348747    .26334095         .        .
31 2013  14536.25  .3114675  .3013327  .3871998  8.603611  9.410095  8.227553   -.06892967  -.04756927    -.1039772         .        .
31 2014 17758.125 .28775316  .3060823  .4061645  8.793789  9.427498  8.416452     .1901779   .18889904   .017402649         .        .
31 2015 15739.746 .30101645  .2983651  .4006184   8.76638   9.29916  8.189207    -.0274086  -.22724533   -.12833786         .        .
31 2016 12388.192  .2918967  .3219274  .3861759   8.56836  9.249236   8.36486      -.19802    .1756525    -.0499239         .        .
31 2017  11615.02 .27782878  .3294835  .3926878  8.486109  9.406858  8.393745   -.08225155   .02888584    .15762234         .        .
31 2018 12707.815  .2814335 .33877215  .3797944  8.458452  9.450384  8.447421  -.027656555   .05367565     .0435257         .        .
31 2019 13176.832   .281428  .3387764 .37979555  8.494794  9.486629  8.483661   .036341667  .036239624   .036244392         .        .
32 1984  57492.39  .2855973  .4276221 .28678063  9.977311 10.606667 10.131503            .           .            .         .        .
32 1985  54557.56 .28055698  .4376798 .28176326  9.808346 10.439713  9.967964   -.16896534  -.16353893   -.16695404         .        .
32 1986  65701.49  .2847554  .4330283 .28221628  10.09982 10.730403 10.270656     .2914734    .3026915    .29069042         .        .
32 1987  49450.79 .28436053  .4275238  .2881157  9.908232 10.474728  9.979658   -.19158745   -.2909975   -.25567532         .        .
32 1988     52229  .2688626  .4249187  .3062187  9.967232 10.528918 10.034654    .05900002   .05499554    .05419064         .        .
32 1989 32829.484  .2695381  .4158292 .31463265  9.496304  10.06189  9.564408    -.4709282   -.4702454    -.4670277         .        .
32 1990  55617.83 .26841688  .4213748  .3102083  10.00787  10.57742 10.075063     .5115671   .51065445    .51552963         .        .
32 1993  56136.24  .2371161  .4712982  .2915857 10.310698 10.603754 10.248013            .           .            .         .        .
32 1994  77653.87   .244521  .4713644 .28411454 10.435687 10.823834 10.409808     .1249895    .1617956    .22008038         .        .
32 1995  77903.96   .244648  .4737134 .28163862 10.219766 10.831408 10.371952    -.2159214   -.0378561   .007573128         .        .
32 1996  78929.69  .2377657 .47691685 .28531742 10.263393 10.877473 10.339172    .04362774 -.032779694    .04606533         .        .
32 1997 28968.035  .2235028  .4793819  .2971153  10.27496 10.626966 10.103237   .011567116   -.2359352    -.2505064  695.6194 6.544803
32 1998  32695.01  .2250596  .4860656  .2888748 10.179857 10.538002  10.07401   -.09510326  -.02922821   -.08896446  704.8409 6.557972
32 1999 33733.246  .2184506  .4934906  .2880588 10.044236  10.50168  10.00366   -.13562107  -.07034969   -.03632164  713.0788 6.569592
32 2000  30083.06 .21344894  .4970998  .2894513 10.016192 10.446154  9.905672  -.028043747  -.09798717   -.05552673  716.5565 6.574457
32 2001   36621.1  .2125105 .50185865 .28563085  9.890747 10.561974  9.921709   -.12544537  .016036987    .11581993  688.2777 6.534193
32 2002 16823.445  .2085191  .5085703 .28291065  8.914659  9.890275  9.053519    -.9760885   -.8681898    -.6716986  692.1918 6.539863
36 1963 17949.059  .3703806  .3573605 .27225885   9.56387   9.89152  9.638744            .           .            .         .        .
36 1964 19080.793 .37556055   .353139 .27130044  9.625208  9.959644  9.693663    .06133747   .05491829    .06812477         .        .
36 1965     20115  .3834227  .3454236  .2711537  9.638718 10.017025  9.754637    .01350975   .06097412    .05738068         .        .
36 1966 20234.445  .3817929  .3443574 .27384967   9.65967 10.003472  9.759399   .020952225   .00476265  -.013552666         .        .
36 1967  22601.41  .3839923  .3438628  .2721449  9.757687 10.119466  9.835953    .09801674   .07655334     .1159935         .        .
36 1968 23888.453  .3880938  .3391461 .27276006  9.804205  10.16992  9.876474    .04651833   .04052162    .05045509         .        .
36 1969 22680.387  .3462443 .36242175   .291334  9.805988  10.15028  9.867252   .001783371 -.009222031  -.019641876         .        .
36 1970  23822.14  .3456888  .3600407 .29427055  9.840582  10.21119  9.892482   .034593582  .025229454    .06091118         .        .
36 1971  25124.83  .3477526 .35890505 .29334235  9.865488 10.261692  9.952371    .02490616   .05988884    .05050182         .        .
end

 reg share_emp_low ScientistsRD newopen i.country1 i.year, robust

Linear regression Number of obs = 1,139
F(108, 1021) = .
Prob > F = .
R-squared = 0.8580
Root MSE = .05855

------------------------------------------------------------------------------
| Robust
share_emp_~w | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
ScientistsRD | -.0000182 4.10e-06 -4.45 0.000 -.0000263 -.0000102
newopen | .0306499 .0134608 2.28 0.023 .004236 .0570639
|
country1 |
12 | .0390319 .0089973 4.34 0.000 .0213765 .0566873
32 | .0264572 .0107241 2.47 0.014 .0054135 .0475009
36 | .0279287 .0265439 1.05 0.293 -.0241581 .0800156
40 | -.141712 .0179403 -7.90 0.000 -.1769162 -.1065079
56 | -.1380952 .0190501 -7.25 0.000 -.175477 -.1007133
68 | .1038386 .0135161 7.68 0.000 .0773161 .130361
70 | .0061113 .0071933 0.85 0.396 -.0080041 .0202267
72 | -.0579535 .0111488 -5.20 0.000 -.0798307 -.0360762
76 | -.0140174 .0096252 -1.46 0.146 -.0329048 .0048701
100 | -.0006805 .0121731 -0.06 0.955 -.0245677 .0232066
104 | .2086858 .0092162 22.64 0.000 .1906009 .2267707
108 | -.0810715 .0097066 -8.35 0.000 -.1001186 -.0620244
124 | -.099391 .0197778 -5.03 0.000 -.1382008 -.0605813
144 | .3067344 .0261847 11.71 0.000 .2553524 .3581163
152 | .1177367 .0101864 11.56 0.000 .0977481 .1377253
156 | -.16938 .0198902 -8.52 0.000 -.2084103 -.1303496
170 | .0256934 .0088262 2.91 0.004 .0083738 .0430131
188 | .0137406 .0080701 1.70 0.089 -.0020952 .0295764
191 | -.0323313 .0097891 -3.30 0.001 -.0515404 -.0131222
196 | .0172505 .0105208 1.64 0.101 -.0033944 .0378953
203 | -.2028318 .0146672 -13.83 0.000 -.2316132 -.1740504
208 | -.0756765 .0258375 -2.93 0.003 -.1263773 -.0249758
218 | .1475472 .0088859 16.60 0.000 .1301105 .1649839
231 | -.0377665 .0103062 -3.66 0.000 -.0579902 -.0175427
233 | .0160659 .0187784 0.86 0.392 -.0207828 .0529147
246 | -.0384194 .0308944 -1.24 0.214 -.0990433 .0222045
250 | -.1062896 .0178572 -5.95 0.000 -.1413306 -.0712486
268 | .0046148 .0177887 0.26 0.795 -.0302917 .0395213
276 | -.2015235 .017231 -11.70 0.000 -.2353358 -.1677112
288 | .097724 .0325372 3.00 0.003 .0338765 .1615715
300 | .0339611 .016594 2.05 0.041 .0013989 .0665234
344 | .0787726 .0387409 2.03 0.042 .0027517 .1547935
348 | -.1366387 .0181531 -7.53 0.000 -.1722604 -.101017
352 | .0322505 .1058428 0.30 0.761 -.1754437 .2399447
356 | -.0440973 .0130634 -3.38 0.001 -.0697314 -.0184632
360 | .1164001 .0088287 13.18 0.000 .0990757 .1337245
364 | -.1768097 .0088262 -20.03 0.000 -.1941293 -.1594901
368 | -.1828083 .0093387 -19.58 0.000 -.2011334 -.1644831
372 | -.0866184 .0208905 -4.15 0.000 -.1276116 -.0456252
380 | -.1487393 .0101895 -14.60 0.000 -.1687341 -.1287445
392 | -.0921825 .0237647 -3.88 0.000 -.1388158 -.0455492
398 | -.2232853 .0081826 -27.29 0.000 -.2393419 -.2072287
400 | -.0415749 .0225237 -1.85 0.065 -.0857729 .0026231
404 | .1593107 .0092725 17.18 0.000 .1411155 .177506
410 | -.1786261 .0216578 -8.25 0.000 -.221125 -.1361271
414 | -.0875235 .0106739 -8.20 0.000 -.1084687 -.0665782
418 | .1604697 .0118813 13.51 0.000 .1371553 .1837842
428 | .1243692 .0133739 9.30 0.000 .0981257 .1506128
440 | .073028 .0162552 4.49 0.000 .0411305 .1049255
442 | -.1315108 .0406674 -3.23 0.001 -.2113121 -.0517094
446 | .1853148 .0416654 4.45 0.000 .1035552 .2670744
450 | .1491167 .0110414 13.51 0.000 .1274504 .1707831
458 | -.2159781 .0175757 -12.29 0.000 -.2504668 -.1814894
470 | -.1449349 .0337687 -4.29 0.000 -.2111989 -.078671
480 | .3088908 .0102039 30.27 0.000 .2888679 .3289137
484 | .0431905 .061717 0.70 0.484 -.0779161 .1642971
498 | .2180727 .0313135 6.96 0.000 .1566265 .2795188
499 | -.0040085 .0242069 -0.17 0.869 -.0515095 .0434924
504 | .1192473 .013898 8.58 0.000 .0919754 .1465193
512 | -.2117548 .0105234 -20.12 0.000 -.2324047 -.1911048
528 | -.1455527 .0196271 -7.42 0.000 -.1840667 -.1070388
554 | .0290145 .0322723 0.90 0.369 -.0343132 .0923422
562 | .216894 .0432069 5.02 0.000 .1321095 .3016784
578 | -.0228868 .0236493 -0.97 0.333 -.0692935 .0235199
590 | .0282461 .0245788 1.15 0.251 -.0199846 .0764769
600 | .0635899 .0248803 2.56 0.011 .0147676 .1124122
608 | -.0716009 .0100036 -7.16 0.000 -.0912308 -.0519709
616 | -.1086621 .0114786 -9.47 0.000 -.1311865 -.0861377
620 | .0524814 .0163468 3.21 0.001 .0204043 .0845586
634 | -.1895964 .0106213 -17.85 0.000 -.2104385 -.1687543
642 | -.06063 .0129022 -4.70 0.000 -.0859479 -.0353122
643 | -.110699 .0163403 -6.77 0.000 -.1427634 -.0786345
688 | -.0259334 .0115281 -2.25 0.025 -.0485549 -.0033119
702 | -.3122946 .0445061 -7.02 0.000 -.3996284 -.2249607
703 | -.1804116 .0183051 -9.86 0.000 -.2163315 -.1444918
704 | .05554 .0190248 2.92 0.004 .0182078 .0928722
705 | -.1721807 .0197598 -8.71 0.000 -.2109552 -.1334063
710 | -.1037827 .0176847 -5.87 0.000 -.1384853 -.0690801
724 | -.1011537 .0126494 -8.00 0.000 -.1259755 -.076332
752 | -.1049328 .0250657 -4.19 0.000 -.1541191 -.0557466
756 | -.1556459 .0215026 -7.24 0.000 -.1978403 -.1134515
764 | -.0818176 .0115342 -7.09 0.000 -.1044511 -.0591842
784 | -.1707653 .0157209 -10.86 0.000 -.2016143 -.1399163
788 | .0877253 .010389 8.44 0.000 .067339 .1081115
792 | -.0002936 .0088619 -0.03 0.974 -.0176832 .017096
804 | -.1445857 .0082918 -17.44 0.000 -.1608565 -.1283148
807 | .1113764 .0179714 6.20 0.000 .0761114 .1466415
818 | .01966 .0078042 2.52 0.012 .0043459 .0349742
826 | -.0950676 .019013 -5.00 0.000 -.1323766 -.0577585
834 | .2470735 .0126206 19.58 0.000 .2223083 .2718388
840 | -.1171398 .0222937 -5.25 0.000 -.1608865 -.0733932
858 | .2027972 .0092866 21.84 0.000 .1845743 .2210201
860 | -.001717 .0100985 -0.17 0.865 -.0215332 .0180993
862 | -.1005945 .0104069 -9.67 0.000 -.1210158 -.0801732
|
year |
1997 | .0038764 .0142744 0.27 0.786 -.024134 .0318869
1998 | -.0048712 .0119387 -0.41 0.683 -.0282983 .018556
1999 | .0032616 .0115313 0.28 0.777 -.0193662 .0258894
2000 | .0002936 .0118457 0.02 0.980 -.022951 .0235383
2001 | .0216224 .0117911 1.83 0.067 -.0015152 .0447599
2002 | .0134293 .0133879 1.00 0.316 -.0128417 .0397002
2004 | .0300838 .0155691 1.93 0.054 -.0004673 .0606349
2005 | .0165905 .015576 1.07 0.287 -.0139742 .0471551
2006 | .0016531 .0160394 0.10 0.918 -.0298208 .033127
2007 | .0030222 .0158234 0.19 0.849 -.0280279 .0340724
2008 | -.036996 .0119942 -3.08 0.002 -.060532 -.0134599
2009 | -.0364633 .0125827 -2.90 0.004 -.0611541 -.0117724
2010 | -.0541106 .0126126 -4.29 0.000 -.0788602 -.029361
2011 | -.0602714 .013812 -4.36 0.000 -.0873745 -.0331684
2012 | -.065318 .0128833 -5.07 0.000 -.0905988 -.0400372
2013 | -.0631121 .013358 -4.72 0.000 -.0893243 -.0368999
2014 | -.0623813 .0132152 -4.72 0.000 -.0883133 -.0364493
2015 | -.0560207 .0133733 -4.19 0.000 -.082263 -.0297784
2016 | -.0518552 .0134605 -3.85 0.000 -.0782685 -.0254419
2017 | -.0550888 .0136225 -4.04 0.000 -.0818201 -.0283575
2018 | -.061747 .0137483 -4.49 0.000 -.0887252 -.0347687
|
_cons | .4666028 .0137993 33.81 0.000 .4395246 .4936809
------------------------------------------------------------------------------

[Clyde Schechter]

Thanks. It seems to be the same problem, and I cannot figure it out. Your example data isn't really able to reproduce the problem because it has other problems of its own.

But there is still the same oddity in the output: you have 118 explanatory variables, but it shows it is calculating only 108 df for the F statistics--but I see no reason why that should be. While I can explain the missing F statistic as coming from having more explanatory variables than df, I can't explain the small number of df.

I definitely would not waste my time bootstrapping this. You don't need that F statistic for anything at all.

The only reason I would pursue any aspect of this is because this anomaly makes me worry the regression and standard error calculations may be incorrect, altogether. I suggest you contact Stata Technical support. Send them your full data set (not just the -dataex-) and the exact code and output you are getting and ask them specfically why the df is coming out the way it is. I'd also appreciate it if you post back here when you get their response.

[Hugo Rocha]

Thanks. It seems to be the same problem, and I cannot figure it out. Your example data isn't really able to reproduce the problem because it has other problems of its own.

But there is still the same oddity in the output: you have 118 explanatory variables, but it shows it is calculating only 108 df for the F statistics--but I see no reason why that should be. While I can explain the missing F statistic as coming from having more explanatory variables than df, I can't explain the small number of df.

I definitely would not waste my time bootstrapping this. You don't need that F statistic for anything at all.

The only reason I would pursue any aspect of this is because this anomaly makes me worry the regression and standard error calculations may be incorrect, altogether. I suggest you contact Stata Technical support. Send them your full data set (not just the -dataex-) and the exact code and output you are getting and ask them specfically why the df is coming out the way it is. I'd also appreciate it if you post back here when you get their response.

That's exactly my concern. That the standard errors and coefficients are wrong... I am letting you know what I find out... As a test, I run the following estimations (which should give me the same results). In fact they do, but the standard errors are different. In the first estimation, the coefficient is statistically significant. In the other, it is statistically insignificant.

  reg share_emp_high ScientistsRD i.country1 i.year,  robust

 xtreg  share_emp_high ScientistsRD i.year, fe robust

[Clyde Schechter]

As a test, I run the following estimations (which should give me the same results).

No, they should not give the same results. They should give the same coefficients, but the standard errors should be different. Since version 13, when you specify -robust- with -xtreg, fe- and some other fixed effects xt estimators Stata automatically uses the cluster robust standard error. By contrast, with -regress-, -robust- gives the non-cluster robust standard error. So the standard errors will, in general, differ.

If you look closely at the output of those two commands, you will even see it. Look at the note just above the coefficient table in the output of -xtreg, fe robust- and you will see it says "(Std. err. adjusted for XX clusters in variable)" There is no such note with -reg, robust-.

[Hugo Rocha]

No, they should not give the same results. They should give the same coefficients, but the standard errors should be different. Since version 13, when you specify -robust- with -xtreg, fe- and some other fixed effects xt estimators Stata automatically uses the cluster robust standard error. By contrast, with -regress-, -robust- gives the non-cluster robust standard error. So the standard errors will, in general, differ.

If you look closely at the output of those two commands, you will even see it. Look at the note just above the coefficient table in the output of -xtreg, fe robust- and you will see it says "(Std. err. adjusted for XX clusters in variable)" There is no such note with -reg, robust-.

Sorry, I misspoke when I said results, I meant coefficients. My apologies!