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  • #1

    Which Panel Data Model should I use?

    Hello all,

    I am conducting a panel data analysis, however, I am quite lost as to which model I should use. I have tried both fe models with clustered errors, as well as xtgls models. However, I am still not sure whether I have applied the right model, especially since my results are not really what I expected them to be. I have the following data:
    Country Year Votes IT CM LM
    Austria 1970 5.5 505.223 4.957.343 676679
    Austria 1971 5.5 5.053.519 5.092.965 685550.6
    Austria 1972 5.5 5.053.519 5.113.378 694422.2
    Austria 1973 5.5 5.091.111 5.007.167 703293.8
    Austria 1974 5.5 5.472.182 5.140.553 712165.4
    Austria 1975 5.4 5.245.344 5.248.239 721037
    Austria 1976 5.4 5.432.013 5.744.205 720821.2
    Austria 1977 5.4 529.593 5.792.313 720605.4
    Austria 1978 5.4 5.200.017 6.022.857 720389.6
    Austria 1979 6.6 5.350.383 5.966.746 720173.8
    Austria 1980 16.9 5.558.724 6.033.527 719958
    Austria 1981 16.9 5.693.232 6.334.436 721631.6
    Austria 1982 16.9 5.483.627 6.319.168 723305.2
    Austria 1983 5 535.186 6.106.641 724978.8
    Austria 1984 5 5.601.637 6.300.898 726652.4
    Austria 1985 5 5.758.453 6.745.496 728326
    Austria 1986 9.7 5.322.612 6.598.616 741308.6
    Austria 1987 9.7 5.231.168 6.540.061 754291.2
    Austria 1988 9.7 5.320.975 641.762 767273.8
    Austria 1989 9.7 5.529.271 6.627.364 780256.4
    Austria 1990 16.6 557.118 655.387 793239
    Austria 1991 16.6 5.469.242 6.612.209 813569.8
    Austria 1992 16.6 5.373.994 6.543.091 833900.6
    Austria 1993 16.6 5.195.966 6.685.321 854231.4
    Austria 1994 22.5 5.339.033 6.794.073 874562.2
    Austria 1995 21.9 5.420.726 6.837.323 894893
    Austria 1996 21.9 5.563.002 6.934.711 915223.8
    Austria 1997 21.9 5.886.284 7.148.751 935554.6
    Austria 1998 21.9 5.973.111 7.381.704 955885.4
    Austria 1999 26.9 5.985.473 7.433.208 976216.2
    Austria 2000 26.9 6.282.597 789.141 996547
    Austria 2001 26.9 6.351.423 799.649 1024491.6
    Austria 2002 10 6.349.685 8.219.291 1052436.2
    Austria 2003 10 6.360.531 8.321.743 1080380.8
    Austria 2004 10 6.424.712 8.447.604 1108325.4
    Austria 2005 10 6.535.706 8.858.264 1136270
    Austria 2006 15.1 6.530.724 915.128 1164214.4
    Austria 2007 15.1 6.688.657 9.208.181 1192158.8
    Austria 2008 28.2 6.776.202 8.988.975 1220103.2
    Austria 2009 28.2 6.224.786 8.927.649 1248047.6
    Austria 2010 15.2 6.500.278 8.884.157 1275992
    Austria 2011 15.2 6.727.844 8.853.999 1319268.4
    Austria 2012 15.2 6.768.095 8.945.255 1362544.8
    Austria 2013 24 6.879.239 8.651.894 1405821.2
    Austria 2014 24 6.933.448 869.601 1449097.6
    Austria 2015 24 6.895.322 855.661 1492374
    Austria 2016 46.2 6.749.627 8.846.185 1535650.4
    Austria 2017 26 696.795 8.854.134 1578926.8
    Austria 2018 26 7.045.536 8.768.121 1622203.2
    Austria 2019 26 7.067.865 8.873.651 1665479.6
    Belgium 1970 3.2 7.500.541 5.963.615 695361
    Belgium 1971 3 746.166 6.192.101 720329
    Belgium 1972 3 744.222 6.156.858 745297
    Belgium 1973 3 746.166 6.316.979 770265
    Belgium 1974 2 7.578.303 6.596.366 795233
    Belgium 1975 2 7.597.743 6.378.839 820201
    Belgium 1976 2 7.558.862 6.541.788 835525.4
    Belgium 1977 1.8 7.617.183 6.723.614 850849.8
    Belgium 1978 4.7 7.597.743 688.159 866174.2
    Belgium 1979 4.7 7.597.743 7.061.665 881498.6
    Belgium 1980 4.7 7.717.234 7.170.457 896823
    Belgium 1981 3.4 7.775.723 7.400.175 891822.6
    Belgium 1982 3.4 7.717.073 7.504.942 886822.2
    Belgium 1983 3.4 765.852 7.661.282 881821.8
    Belgium 1984 3.4 7.665.326 7.744.627 876821.4
    Belgium 1985 2.6 7.655.564 8.067.375 871821
    Belgium 1986 2.6 7.560.255 8.011.825 875764.2
    Belgium 1987 2.7 7.546.987 8.076.154 879707.4
    Belgium 1988 2.7 7.539.138 8.082.095 883650.6
    Belgium 1989 2.7 7.581.036 8.245.206 887593.8
    Belgium 1990 2.7 7.532.774 8.165.583 891537
    Belgium 1991 6.6 7.555.898 8.246.928 890285.2
    Belgium 1992 6.6 7.564.843 8.220.841 889033.4
    Belgium 1993 6.6 7.627.538 8.329.768 887781.6
    Belgium 1994 6.6 7.621.345 8.414.194 886529.8
    Belgium 1995 7.8 7.610.406 8.438.316 885278
    Belgium 1996 7.8 7.631.635 8.555.341 878896.2
    Belgium 1997 7.8 7.736.806 8.698.194 872514.4
    Belgium 1998 7.8 7.703.612 8.921.822 866132.6
    Belgium 1999 9.9 7.734.801 8.969.897 859750.8
    Belgium 2000 9.9 7.817.067 9.093.159 853369
    Belgium 2001 9.9 7.740.348 9.184.927 856867.6
    Belgium 2002 9.9 7.730.812 9.259.908 860366.2
    Belgium 2003 11.6 7.613.954 9.325.546 863864.8
    Belgium 2004 11.6 7.628.757 9.369.892 867363.4
    Belgium 2005 11.6 7.661.606 9.436.666 870862
    Belgium 2006 11.6 7.743.306 9.434.084 907258.4
    Belgium 2007 12 7.870.786 9.465.473 943654.8
    Belgium 2008 12 8.030.085 9.322.815 980051.2
    Belgium 2009 12 7.999.457 9.349.532 1016447.6
    Belgium 2010 9.1 8.183.108 9.292.619 1052844
    Belgium 2011 9.1 8.237.186 9.187.645 1119863.2
    Belgium 2012 9.1 8.338.676 9.219.106 1186882.4
    Belgium 2013 9.1 8.397.858 9.219.292 1253901.6
    Belgium 2014 5.2 8.469.238 9.207.774 1320920.8
    Belgium 2015 5.2 8.535.023 9.286.053 1387940
    Belgium 2016 5.2 8.475.529 930.704 1454959.2
    Belgium 2017 5.2 8.531.174 9.339.543 1521978.4
    Belgium 2018 5.2 8.506.691 9.275.301 1588997.6
    Belgium 2019 13.1 8.524.594 9.314.677 1656016.8
    Denmark 1973 15.9 46.845 2.647.943 128650
    Denmark 1974 15.9 5.120.025 278.959 133667
    Denmark 1975 13.6 4.837.444 2.475.823 138684
    Denmark 1976 13.6 4.877.834 2.717.329 143701
    Denmark 1977 14.6 4.908.028 3.197.778 148718
    Denmark 1978 14.6 4.617.492 3.751.507 153735
    Denmark 1979 11 4.748.418 4.093.838 158752
    Denmark 1980 11 5.101.815 4.480.595 163769
    Denmark 1981 8.9 5.764.093 5.079.679 170173.8
    Denmark 1982 8.9 5.529.821 5.151.875 176578.6
    Denmark 1983 8.9 548.239 5.220.655 182983.4
    Denmark 1984 3.6 5.612.459 5.599.583 189388.2
    Denmark 1985 3.6 5.712.928 634.277 195793
    Denmark 1986 3.6 4.894.337 6.135.568 203672.2
    Denmark 1987 4.8 4.641.191 6.323.819 211551.4
    Denmark 1988 9 49.785 6.593.586 219430.6
    Denmark 1989 9 5.252.831 6.897.054 227309.8
    Denmark 1990 6.4 5.180.474 7.090.704 235189
    Denmark 1991 6.4 5.370.344 7.290.814 248772.8
    Denmark 1992 6.4 5.039.881 7.443.523 262356.6
    Denmark 1993 6.4 4.957.723 762.567 275940.4
    Denmark 1994 6.4 5.193.167 7.645.187 289524.2
    Denmark 1995 6.4 511.053 7.643.201 303108
    Denmark 1996 6.4 5.214.737 7.839.516 316691.6
    Denmark 1997 6.4 5.286.699 7.966.184 330275.2
    Denmark 1998 9.8 5.442.199 7.825.836 343858.8
    Denmark 1999 9.8 5.926.977 7.875.962 357442.4
    Denmark 2000 9.8 6.613.194 8.504.195 371026
    Denmark 2001 12.6 6.616.779 8.504.801 384897.4
    Denmark 2002 12.6 6.669.894 8.411.801 398768.8
    Denmark 2003 12.6 6.449.561 8.382.774 412640.2
    Denmark 2004 12.6 6.632.492 8.425.921 426511.6
    Denmark 2005 13.3 6.873.502 8.854.929 440383
    Denmark 2006 13.3 7.097.939 8.923.073 454254.4
    Denmark 2007 13.9 7.212.341 9.090.938 468125.8
    Denmark 2008 13.9 731.926 8.876.997 481997.2
    Denmark 2009 13.9 6.850.073 8.895.474 495868.6
    Denmark 2010 13.9 6.983.673 8.915.679 509740
    Denmark 2011 12.3 7.287.223 8.924.421 522296
    Denmark 2012 12.3 7.369.058 8.921.219 534852
    Denmark 2013 12.3 7.328.474 9.037.654 547408
    Denmark 2014 12.3 7.278.108 8.970.823 559964
    Denmark 2015 21.1 7.321.796 9.047.837 572520
    Denmark 2016 21.1 7.178.616 9.001.206 585076
    Denmark 2017 21.1 7.307.635 9.081.329 597632
    Denmark 2018 21.1 7.430.067 8.990.208 610188
    Denmark 2019 21.1 7.505.315 9.017.547 622744
    France 1970 12.6 2.465.617 2.283.761 5210336
    France 1971 12.6 2.464.328 2.443.233 5282601.6
    France 1972 12.6 2.444.888 2.537.598 5354867.2
    France 1973 12.6 2.577.102 236.775 5427132.8
    France 1974 12.6 3.130.559 2.308.566 5499398.4
    France 1975 12.6 2.982.771 2.383.405 5571664
    France 1976 12.6 3.080.193 2.478.418 5635457.8
    France 1977 12.6 3.266.129 275.483 5699251.6
    France 1978 .8 3.193.744 3.132.793 5763045.4
    France 1979 .8 3.288.368 3.588.702 5826839.2
    France 1980 .8 3.587.303 4.110.257 5890633
    France 1981 .2 4.017.097 4.951.791 5903070.4
    France 1982 .2 3.726.557 5.196.036 5915507.8
    France 1983 .2 360.686 5.176.623 5927945.2
    France 1984 .2 3.799.716 54.943 5940382.6
    France 1985 .2 3.734.645 5.857.213 5952820
    France 1986 9.9 3.082.714 5.259.402 5941709.4
    France 1987 9.9 3.003.585 5.098.059 5930598.8
    France 1988 9.8 2.983.056 5.243.268 5919488.2
    France 1989 9.8 3.200.376 5.998.421 5908377.6
    France 1990 9.8 3.245.022 6.112.674 5897267
    France 1991 9.8 3.339.932 6.526.645 5935412.2
    France 1992 9.8 3.345.392 6.626.357 5973557.4
    France 1993 12.4 3.394.591 7.137.478 6011702.6
    France 1994 12.4 3.220.808 6.099.631 6049847.8
    France 1995 12.4 3.258.469 6.081.164 6087993
    France 1996 12.4 3.322.989 6.178.545 6126138
    France 1997 17.3 3.638.428 6.842.113 6164283
    France 1998 17.3 3.708.957 7.308.211 6202428
    France 1999 17.3 419.752 722.791 6240573
    France 2000 17.3 4.591.538 7.751.446 6278718
    France 2001 17.3 4.550.206 7.884.198 6370494.4
    France 2002 29.9 4.412.336 7.935.886 6462270.8
    France 2003 29.9 4.109.246 8.147.341 6554047.2
    France 2004 29.9 414.617 8.337.487 6645823.6
    France 2005 29.9 4.301.358 8.550.555 6737600
    France 2006 29.9 435.309 8.795.571 6829376.2
    France 2007 15.9 4.369.375 8.865.978 6921152.4
    France 2008 15.9 4.587.447 8.617.055 7012928.6
    France 2009 15.9 4.087.569 8.610.149 7104704.8
    France 2010 15.9 4.513.947 8.591.022 7196481
    France 2011 15.9 4.796.066 848.532 7314068.4
    France 2012 31.5 4.987.191 8.607.812 7431655.8
    France 2013 31.5 502.857 8.590.809 7549243.2
    France 2014 31.5 5.123.683 8.544.069 7666830.6
    France 2015 31.5 5.385.682 8.666.798 7784418
    France 2016 31.5 5.285.506 8.697.827 7902005.4
    France 2017 47.1 5.364.735 8.780.763 8019592.8
    France 2018 47.1 545.649 8.820.801 8137180.2
    France 2019 47.1 5.490.777 894.235 8254767.6
    Germany 1990 4.5 3.377.561 5.307.707 5936181
    Germany 1991 4.5 322.934 5.498.868 6241826
    Germany 1992 4.5 3.035.448 5.310.899 6547471
    Germany 1993 4.5 3.016.404 5.505.585 6853116
    Germany 1994 6.3 3.085.767 5.518.541 7158761
    Germany 1995 6.3 3.220.757 5.575.909 7464406
    Germany 1996 6.3 33.565 5.739.933 7770051
    Germany 1997 6.3 3.844.801 6.392.199 8075696
    Germany 1998 6.9 4.014.946 6.803.582 8381341
    Germany 1999 6.9 4.164.272 7.221.175 8686986
    Germany 2000 6.9 4.774.082 7.873.695 8992631
    Germany 2001 6.9 4.884.409 7.832.419 9253936.8
    Germany 2002 4.6 4.904.709 8.077.346 9515242.6
    Germany 2003 4.6 4.910.915 8.183.472 9776548.4
    Germany 2004 4.6 5.157.415 8.313.499 10037854
    Germany 2005 9.3 5.518.964 8.421.184 10299160
    Germany 2006 9.3 5.894.626 863.297 10560466
    Germany 2007 9.3 589.803 8.797.256 10821772
    Germany 2008 9.3 6.051.058 84.093 11083078
    Germany 2009 12.3 5.603.434 838.634 11344384
    Germany 2010 12.3 6.045.068 8.424.089 11605690
    Germany 2011 12.3 6.263.173 8.347.546 11685690
    Germany 2012 12.3 6.375.655 8.435.017 11765690
    Germany 2013 13.6 639.547 837.017 11845690
    Germany 2014 13.6 6.407.585 8.302.892 11925690
    Germany 2015 13.6 6.604.784 8.410.995 12005690
    Germany 2016 13.6 6.571.953 8.441.802 12085690
    Germany 2017 21.8 6.697.076 8.542.004 12165690
    Germany 2018 21.8 6.753.723 8.504.769 12245690
    Germany 2019 21.8 6.807.494 8.542.661 12325690
    Ireland 1997 .7 8.681.377 9.186.399 207455.6
    Ireland 1998 .7 8.730.085 9.322.749 255154.4
    Ireland 1999 .7 8.647.158 9.299.142 302853.2
    Ireland 2000 .7 8.758.348 9.456.368 350552
    Ireland 2001 .7 8.613.224 9.529.057 398250.8
    Ireland 2002 .8 8.355.217 9.635.816 445949.6
    Ireland 2003 .8 8.273.316 9.679.919 493648.4
    Ireland 2004 .8 8.160.423 9.732.273 541347.2
    Ireland 2005 .8 8.126.427 9.726.582 589046
    Ireland 2006 .8 8.061.874 9.730.331 617345.2
    Ireland 2007 1.1 7.986.171 9.690.047 645644.4
    Ireland 2008 1.1 8.079.366 9.592.088 673943.6
    Ireland 2009 1.1 814.596 9.550.742 702242.8
    Ireland 2010 1.1 8.334.658 9.506.381 730542
    Ireland 2011 3.4 8.340.453 9.477.294 733685.6
    Ireland 2012 3.4 8.419.837 9.495.406 736829.2
    Ireland 2013 3.4 8.378.477 9.523.363 739972.8
    Ireland 2014 3.4 8.393.317 9.553.163 743116.4
    Ireland 2015 3.4 8.116.712 9.593.762 746260
    Ireland 2016 3.9 8.168.639 9.637.222 749403.6
    Ireland 2017 3.9 8.026.732 9.691.886 752547.2
    Ireland 2018 3.9 808.281 9.728.851 755690.8
    Ireland 2019 3.9 7.998.513 9.756.441 758834.4
    Latvia 1995 15 5.459.974 3.199.184 538093
    Latvia 1996 15 7.117.347 4.366.003 516510
    Latvia 1997 15 7.045.464 5.017.045 494927
    Latvia 1998 16.4 7.082.068 5.144.059 473344
    Latvia 1999 16.4 6.641.998 5.257.454 451761
    Latvia 2000 16.4 6.275.933 4.717.365 430178
    Latvia 2001 16.4 630.378 5.069.319 419487.4
    Latvia 2002 5.4 617.218 5.303.643 408796.8
    Latvia 2003 5.4 6.560.503 5.980.671 398106.2
    Latvia 2004 5.4 6.897.086 6.923.817 387415.6
    Latvia 2005 5.4 7.060.657 7.124.454 376725
    Latvia 2006 6.9 7.046.677 7.609.389 364137.2
    Latvia 2007 6.9 6.789.491 7.722.565 351549.4
    Latvia 2008 6.9 6.825.654 7.502.869 338961.6
    Latvia 2009 6.9 676.208 6.847.433 326373.8
    Latvia 2010 7.7 7.411.082 7.856.084 313786
    Latvia 2011 13.9 7.636.077 7.802.837 303654
    Latvia 2012 13.9 7.724.549 8.024.182 293522
    Latvia 2013 13.9 7.566.708 8.025.798 283390
    Latvia 2014 16.6 7.594.755 7.865.642 273258
    Latvia 2015 16.6 759.467 8.074.553 263126
    Latvia 2016 16.6 7.551.381 8.103.791 252994
    Latvia 2017 16.6 7.731.674 8.316.394 242862
    Latvia 2018 11 7.838.705 8.050.452 232730
    Latvia 2019 11 7.743.818 8.062.903 222598
    Lithuania 1992 21.2 5.086.556 2.154.553 309152.6
    Lithuania 1993 21.2 5.499.369 2.123.291 297297.4
    Lithuania 1994 21.2 567.178 208.027 285442.2
    Lithuania 1995 21.2 586.075 2.038.904 273587
    Lithuania 1996 31.3 6.984.422 2.841.133 261731.8
    Lithuania 1997 31.3 7.426.125 3.570.293 249876.6
    Lithuania 1998 31.3 7.064.932 4.056.081 238021.4
    Lithuania 1999 31.3 6.561.284 4.409.921 226166.2
    Lithuania 2000 8.6 653.243 4.683.633 214311
    Lithuania 2001 8.6 6.801.526 4.715.453 211690.6
    Lithuania 2002 8.6 7.143.372 4.642.679 209070.2
    Lithuania 2003 8.6 7.141.019 5.006.042 206449.8
    Lithuania 2004 54.5 715.842 5.568.894 203829.4
    Lithuania 2005 54.5 7.380.458 5.943.702 201209
    Lithuania 2006 54.5 7.561.928 669.585 193121.6
    Lithuania 2007 54.5 7.338.783 7.101.967 185034.2
    Lithuania 2008 41.3 7.480.256 6.634.425 176946.8
    Lithuania 2009 41.3 703.754 6.016.963 168859.4
    Lithuania 2010 41.3 7.468.725 7.157.096 160772
    Lithuania 2011 41.3 7.655.063 7.100.578 155824.8
    Lithuania 2012 50.2 7.950.163 704.905 150877.6
    Lithuania 2013 50.2 8.199.123 6.816.105 145930.4
    Lithuania 2014 50.2 8.275.615 6.306.606 140983.2
    Lithuania 2015 50.2 8.255.813 7.109.617 136036
    Lithuania 2016 32 8.329.086 7.197.243 131088.8
    Lithuania 2017 32 8.545.651 7.436.115 126141.6
    Lithuania 2018 32 8.614.827 727.837 121194.4
    Lithuania 2019 32 8.709.712 7.264.605 116247.2
    Netherlands 1977 .2 6.020.567 5.580.267 328709
    Netherlands 1978 .2 583.132 567.272 382798
    Netherlands 1979 .2 6.095.749 6.319.088 436887
    Netherlands 1980 .2 6.225.511 6.665.238 490976
    Netherlands 1981 .3 6.524.629 7.153.466 545065
    Netherlands 1982 .5 6.553.318 7.262.486 599154
    Netherlands 1983 .5 6.356.079 7.216.537 653243
    Netherlands 1984 .5 6.677.785 7.387.078 707332
    Netherlands 1985 .5 6.830.733 7.619.017 761421
    Netherlands 1986 .4 607.973 7.416.521 845589.4
    Netherlands 1987 .4 5.920.835 7.449.555 929757.8
    Netherlands 1988 .4 6.078.601 7.484.605 1013926.2
    Netherlands 1989 1.3 6.380.917 7.849.378 1098094.6
    Netherlands 1990 1.3 6.286.551 7.768.694 1182263
    Netherlands 1991 1.3 6.359.949 7.822.333 1215043.2
    Netherlands 1992 1.3 6.374.998 7.725.591 1247823.4
    Netherlands 1993 1.3 6.542.454 795.682 1280603.6
    Netherlands 1994 3.7 6.739.019 7.902.093 1313383.8
    Netherlands 1995 3.7 670.779 7.925.957 1346164
    Netherlands 1996 3.7 6.838.557 8.075.811 1388198.6
    Netherlands 1997 3.7 7.233.839 8.330.735 1430233.2
    Netherlands 1998 4.1 7.182.314 8.523.499 1472267.8
    Netherlands 1999 4.1 7.182.266 8.624.905 1514302.4
    Netherlands 2000 4.1 7.536.873 89.501 1556337
    Netherlands 2001 4.1 7.395.481 9.043.324 1592295
    Netherlands 2002 22.9 7.358.714 9.072.421 1628253
    Netherlands 2003 12 7.186.776 9.392.641 1664211
    Netherlands 2004 12 761.637 9.647.229 1700169
    Netherlands 2005 12 7.828.608 96.92 1736127
    Netherlands 2006 32.6 7.899.716 9.670.264 1755403.6
    Netherlands 2007 32.6 8.011.014 9.664.986 1774680.2
    Netherlands 2008 32.6 7.991.331 9.506.996 1793956.8
    Netherlands 2009 32.6 7.937.505 9.465.075 1813233.4
    Netherlands 2010 22.4 8.086.859 9.470.567 1832510
    Netherlands 2011 22.4 8.255.253 9.430.736 1861905.2
    Netherlands 2012 19.7 8.309.721 9.419.394 1891300.4
    Netherlands 2013 19.7 8.288.644 9.439.845 1920695.6
    Netherlands 2014 19.7 8.338.205 9.479.378 1950090.8
    Netherlands 2015 19.7 8.722.551 9.509.399 1979486
    Netherlands 2016 19.7 8.407.702 9.549.968 2008881.2
    Netherlands 2017 22.1 8.541.669 9.594.807 2038276.4
    Netherlands 2018 22.1 8.659.211 9.611.849 2067671.6
    Netherlands 2019 22.1 867.876 9.654.858 2097066.8
    Sweden 1988 0 3.930.612 4.932.604 729865
    Sweden 1989 0 4.059.693 5.728.377 759316
    Sweden 1990 0 3.810.809 6.403.824 788767
    Sweden 1991 6.8 3.591.838 6.493.347 818218
    Sweden 1992 6.8 3.616.063 6.369.524 847669
    Sweden 1993 6.8 4.048.039 694.711 877120
    Sweden 1994 1.5 4.615.953 7.262.576 906571
    Sweden 1995 1.5 471.252 7.551.237 936022
    Sweden 1996 1.5 4.619.715 7.360.445 949577.2
    Sweden 1997 1.5 5.193.072 7.567.169 963132.4
    Sweden 1998 .4 5.202.072 7.750.764 976687.6
    Sweden 1999 .4 5.393.328 8.105.626 990242.8
    Sweden 2000 .4 5.979.117 8.509.441 1003798
    Sweden 2001 .4 6.030.568 8.602.749 1028196.4
    Sweden 2002 1.4 5.774.562 8.599.578 1052594.8
    Sweden 2003 1.4 5.711.996 8.744.411 1076993.2
    Sweden 2004 1.4 5.990.871 8.914.307 1101391.6
    Sweden 2005 1.4 6.421.124 9.002.833 1125790
    Sweden 2006 2.9 6.569.646 9.170.577 1177617.8
    Sweden 2007 2.9 6.677.885 9.196.021 1229445.6
    Sweden 2008 2.9 6.896.519 901.746 1281273.4
    Sweden 2009 2.9 6.509.998 916.896 1333101.2
    Sweden 2010 5.7 6.613.988 9.122.641 1384929
    Sweden 2011 5.7 6.699.692 9.013.068 1435897.4
    Sweden 2012 5.7 6.716.846 9.063.956 1486865.8
    Sweden 2013 5.7 6.511.826 9.074.138 1537834.2
    Sweden 2014 12.9 6.599.894 9.055.646 1588802.6
    Sweden 2015 12.9 6.600.246 9.045.238 1639771
    Sweden 2016 12.9 6.533.605 9.028.532 1690739.4
    Sweden 2017 12.9 6.577.427 9.088.905 1741707.8
    Sweden 2018 17.5 677.769 9.077.025 1792676.2
    Sweden 2019 17.5 6.886.541 9.097.736 1843644.6
    How would you suggest I run this panel data analysis? Thank you in advance!
    Tags: None
  • #2
    Micheline:
    welcome to this forum.
    Some comments about your query;
    1) are you dealing with a N (cross-sectional dimension) >T (time-series dimension) panel or the other way round?
    2) the estimators you mention are not "one size fits all" tools;
    3) your concern about the results you got should not lead your research approach. Once the methological approach is correct, results are what they are and should be presented as such.
    Kind regards,
    Carlo
    (Stata 19.0)

    Comment

    • #3
      I presume you're an economist (although correct me if I'm wrong). Also, as Carlo stated, specifying whether N>T is very important as this will influence our responses concerning standard error estimation methods. How many countries and time periods do you have?

      In any case I would run a baseline two-way fixed effects (with unit and time fixed effects) with clustered standard errors and then take it from there.

      Then you could move to GMM if you have reason to believe that your dependent variable is dynamic.

      • 1 like

      Comment

      • #4
        Thank you for your response. My data is T>N. And what do you mean with the "one size fits all" tools, is there any way I can solve this?

        Comment

        • #5
          MIcheline:
          I meant that -xtreg- and -xtgls- are different beasts.
          For T>N panel datasets, Stata -xt- suite offers -xtgls- and -xtregar-, that differ from each other especially as far as the standard error options are concerned.
          Kind regards,
          Carlo
          (Stata 19.0)

          Comment

          • #6
            Seen as T>N, if T is very very large (tending to infinity) then potentially xtscc (Hoechle, 2007) would be interesting
            • 1 like

            Comment

            • #7
              Wait, stop. This is confusing. Let's start from the very beginning shall we?

              What question are you studying? What is the research question you're investigating? Before we talk modeling and sexy statistical ninjutsu, let's talk about the context and question you're interested in. All I see so far is country/ year panel data, but I've no context as to what you're doing with this.

              Comment

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