Proper command for estimating a two-way fixed effects model

[Bernie konle]

I have a dataset for 37 countries and 19 time periods. The hausman specification test suggested I should use the fixed effects model. I further run a test for the significance of time fixed effect following Chris Baum (2006, p.225). That test also suggested the time effects are jointly significant and so should be included in the model. The procedure used for that test is below:
quietly tabulate annee, generate(an)
local j 0
forvalues i=96/13 {
local ++j
rename an'j' an'i'
quietly replace an'i'=an'i'-an19
}
drop an19
quietly xtreg lmortinf gdp_grwrate lndepsantehbt acces_eaupot vih vacc_roug dpt fert govmoy an*, fe.
test an1 an2 an3 an4 an5 an6 an7 an8 an9 an10 an11 an12 an13 an14 an15 an16 an17 an18

***Note that annee is my time variable.
I also run tests for serial autocorrelation and heteroskedasticity. And the results also proved the existence of serial autocorrelation and heteroskedasticity.
So in other to take into account the above mentioned problems and the econometric developments since Baum (2006), I would like to know whether there is another way to test for the significance of time time fixed effects and to include them in a model. And due to the structure of my data are there better stata commands than xtreg x1 x2 x3.....xn, fe. Some suggest xtgls, areg, xtpcse, reghdfe. Which command would be best for an N=37, T=19 dataset with serial autocorrelation and heteroskedasticity.

I would also like to include a dummy say dum and set dum=0 if gdp_grwrate<0 and dum=1 if gdp_grwrate>0. How do I interpret the coefficient of dum?
Below is a sample of my data.

* Example generated by -dataex-. To install: ssc install dataex
clear
input int annee str24 pays float(mort_inf mort_adlt gdp_grwrate pib_hbt depsante_hbt acces_eaupot urbanpop vih) byte(vacc_roug dpt) float(fert govmoy)
1996 "Angola"         224 428.1965   8.034612  3506.245  60.22758 45.9  29.57  1.1 62 28 7.051  -1.4708937
1997 "Angola"       222.6  425.836   4.952266 3679.8835   79.0387 45.8 30.268  1.2 78 41 7.017  -1.5583974
1998 "Angola"       220.8  419.904   3.900152 3823.4045  79.53523 45.7 30.975  1.3 61 46 6.981   -1.645901
1999 "Angola"       218.9 413.9725   .3107823  3835.287  82.08157 45.7 31.692  1.4 42 19 6.943  -1.6558653
2000 "Angola"       216.7  408.041 -.11177737      3831  69.20174 45.7 32.419  1.5 36 28 6.905  -1.6658294
2001 "Angola"       214.1 402.1095   .8447512 3863.3625 137.88118 45.7 33.152  1.6 65 38 6.866    -1.52737
2002 "Angola"       211.7 396.1775 -10.099722 3473.1736 103.88967 45.7 33.895  1.7 66 41 6.829  -1.3889103
2003 "Angola"       209.2  392.003   1.579595  3528.036 130.48369 45.8 34.645  1.8 52 40 6.792  -1.2494333
2004 "Angola"       206.7 387.8275   7.006726  3775.235 153.30067 45.9 35.405  1.8 52 40 6.755  -1.2643487
2005 "Angola"       203.9 383.6525   14.18509  4310.756 157.52116   46 36.169  1.9 32 38 6.716   -1.225804
2006 "Angola"       200.5 379.4775  16.642405  5028.169 209.61484 46.2 36.942    2 33 34 6.671  -1.1200725
2007 "Angola"       196.4 375.3025  18.487598  5957.757 189.90187 46.4 37.722    2 71 73 6.619  -1.1341099
2008 "Angola"         192  370.799  10.040818  6555.965 242.15427 46.6 38.509  2.1 61 69 6.559  -1.0476762
2009 "Angola"       187.3  366.295  -.9701917  6492.359  274.7345 46.9 39.299  2.1 57 60 6.492  -1.0257341
2010 "Angola"       182.5 361.7915  -.0028121  6492.177 215.70576 47.1 40.097  2.1 72 77 6.416  -1.0095861
2011 "Angola"       177.3  357.288   .4975891  6524.481  220.5003 47.5   40.9  2.2 64 71 6.335  -1.0491998
2012 "Angola"       172.2 352.7845  1.7098312  6636.039  223.2445 47.8 41.699  2.2 72 75 6.251   -.9950328
2013 "Angola"       167.1  348.914   3.339851  6857.672 301.98914 48.2  42.49  2.2 66 77 6.165  -1.0591317
2014 "Angola"       162.2  345.043  1.4332478   6955.96 239.01024 48.6 43.274  2.2 60 64  6.08  -1.0283822
1996 "Benin"        156.2 282.9655   1.103843 1511.2933  48.13155 62.6 37.071  1.1 60 66 6.284  -.10855488
1997 "Benin"        153.6 287.6425   2.659984 1551.4934  47.24747 63.4 37.385  1.2 66 66 6.205  -.06888309
1998 "Benin"        150.9 287.0615  1.0200866   1567.32  49.07447 64.3 37.699  1.3 67 70 6.128 -.029211296
1999 "Benin"        147.9 286.4805  2.3096182  1603.519   53.3141 65.1 38.015  1.4 69 74 6.051  -.02736326
2000 "Benin"        144.7  285.899    2.67819 1646.4645  52.45966   66 38.333  1.5 70 78 5.975  -.02551522
2001 "Benin"        141.1  285.318  2.0193248  1679.712   59.6444 66.9  38.65  1.5 68 76 5.898  -.11470078
2002 "Benin"        137.1 284.7375  1.2597008 1700.8712  55.80888 67.7 38.969  1.5 66 75 5.818  -.20388633
2003 "Benin"        133.1 280.0665  .05779146 1701.8542  61.96275 68.6 39.297  1.5 65 73 5.733  -.17008637
2004 "Benin"        129.2 275.3955  1.0406204  1719.564  62.57838 69.4 39.635  1.4 63 72 5.645  -.26072276
2005 "Benin"        125.5  270.725 -1.5149806  1693.513  66.76049 70.3 39.982  1.4 61 70 5.553  -.38180465
2006 "Benin"        122.1 266.0545   .7295833 1705.8685  69.42651 71.1 40.338  1.3 66 74 5.459   -.2226624
2007 "Benin"          119  261.384  2.7741675 1753.1923  69.19661   72 40.703  1.3 70 82 5.365  -.21898597
2008 "Benin"        116.3   259.34   1.785374 1784.4933  66.35791 72.8 41.078  1.2 66 75 5.272  -.23293996
2009 "Benin"        113.9  257.297  -.6421459  1773.034  70.92419 73.7 41.461  1.2 71 79 5.182  -.25481337
2010 "Benin"        111.6 255.2535  -.7697142  1759.387  79.34248 74.5 41.854  1.2 68 76 5.094   -.3046026
2011 "Benin"        109.3 253.2105  .12432854 1761.5743   88.2289 75.3 42.256  1.2 70 75 5.009  -.29603568
2012 "Benin"          107  251.167  1.9902444  1796.634  83.32962 76.2 42.667  1.1 75 81 4.927   -.3377893
2013 "Benin"        104.8 248.8745   4.363894  1875.037  82.24059   77 43.086  1.1 68 74 4.846   -.3250874
2014 "Benin"        102.1  246.582  3.5853064  1942.263  85.60836 77.8 43.514  1.1 68 75 4.766   -.3429743
1996 "Botswana"      73.5 493.8565   3.496567  9172.998 284.54446 93.9  49.83 22.2 89 96 3.866     .683143
1997 "Botswana"      76.5 540.7635   5.793682  9704.452  333.0036 94.1 50.677   24 89 96 3.746    .6822631
1998 "Botswana"        79 556.4125  -1.214586  9586.583 326.74155 94.3 51.525 25.1 89 98 3.631    .6813832
1999 "Botswana"        82  572.061   7.724918  10327.14  329.3767 94.5 52.372 25.8 90 97 3.519    .6696991
2000 "Botswana"      82.9 587.7095   .3308896  10361.31  381.3802 94.7 53.219   26 91 97 3.413    .6580151
2001 "Botswana"      81.6 603.3585 -1.2255436 10234.328  475.3578 94.9 54.062   26 91 97 3.312    .6552119
2002 "Botswana"      79.8  619.007  4.6363497 10708.827 570.63477   95 54.374 25.7 92 97 3.219    .6524087
2003 "Botswana"      78.1  566.552   3.252449 11057.126  431.4554 95.1 54.607 25.3 92 96 3.134    .8671644
2004 "Botswana"      75.8  514.097   1.289676 11199.728 537.03876 95.2 54.841 24.9 93 96  3.06    .7386777
2005 "Botswana"        69  461.642   2.971863 11532.568  577.4712 95.3 55.073 24.6 93 96 2.998    .7832966
2006 "Botswana"      63.4  409.187   6.553606 12288.367  555.9358 95.4 55.306 24.3 94 96 2.952    .6658836
2007 "Botswana"      62.6  356.732   6.327096 13065.863  580.1953 95.5 55.539 24.1 95 96 2.921    .6829954
2008 "Botswana"      61.7 345.9235   4.224315 13617.807  737.2376 95.7 55.772 23.9 95 96 2.903    .6985549
2009 "Botswana"      57.3 335.1155  -9.462539 12329.217  750.4744 95.8 56.004 23.6 96 96 2.895    .6494777
2010 "Botswana"      53.5 324.3075   6.410258  13119.55  779.7747 95.9 56.235 23.5 96 95 2.893    .6657927
2011 "Botswana"      51.8 313.4995  3.9232454 13634.264  697.8672   96 56.467 23.3 97 95  2.89    .6775687
2012 "Botswana"      49.5  302.691  2.3445365 13953.924  878.7249 96.1 56.699 23.1 97 95 2.881    .7124613
2013 "Botswana"      46.6  303.292    7.65484 15022.074  893.1657 96.2 56.938 22.8 97 95 2.864    .6761068
2014 "Botswana"      44.8  303.893  1.1860176 15200.238   870.837 96.2 57.187 22.5 97 95 2.836    .6325759
1996 "Burkina Faso"   197  336.544    7.98666  964.5812 35.773926 52.5 15.407  3.4 40 37 6.801   -.5374672
1997 "Burkina Faso"   194  337.854   3.396481  997.3431   37.5725 54.3 15.875  3.2 41 39 6.754  -.51940936
1998 "Burkina Faso" 191.3 334.8245   4.340499 1040.6327  40.64801 56.2  16.51  2.9 24 15 6.704  -.50135154
1999 "Burkina Faso" 188.5 331.7945   4.345997 1085.8586  42.68723   58 17.166  2.7 36 15  6.65   -.4114849
2000 "Burkina Faso" 185.7  328.765  -.9635816 1075.3955  41.95066 59.9 17.844  2.4 48 45 6.592   -.3216183
2001 "Burkina Faso" 182.4  325.735   3.615984 1114.2816   42.9474 61.8  18.54  2.2 63 62 6.531   -.3619675
2002 "Burkina Faso" 178.3 322.7055  1.4048307 1129.9353  47.61087 63.6 19.258  1.9 64 69 6.468   -.4023167
2003 "Burkina Faso" 173.1 317.0825   4.729717  1183.378  54.18895 65.4 19.996  1.7 76 79 6.403  -.30998605
2004 "Burkina Faso" 166.3  311.459  1.4595864 1200.6505  64.98684 67.3 20.757  1.6 78 79 6.335   -.3568161
2005 "Burkina Faso" 158.3 305.8365   5.472989  1266.362 75.389694 69.1 21.537  1.4 84 82 6.265  -.35784775
2006 "Burkina Faso" 149.4 300.2135   3.086761 1305.4515  76.27145   71 22.339  1.3 88 86 6.192   -.3384232
2007 "Burkina Faso" 139.9 294.5905   .9742676   1318.17  81.26638 72.8 23.163  1.2 94 89 6.116  -.29700413
2008 "Burkina Faso" 130.4 290.0395   2.599113  1352.431  88.02504 74.6 23.993  1.1 94 93 6.036  -.25391927
2009 "Burkina Faso" 121.4  285.488 -.13966903  1350.542   96.9035 76.4 24.828  1.1 94 92 5.953  -.25779772
2010 "Burkina Faso" 113.5  280.936   5.212027 1420.9326  99.91912 78.2 25.665    1 92 91 5.867  -.28285697
2011 "Burkina Faso" 106.9  276.385   3.483812  1470.435  76.01353   80 26.505    1 89 91  5.78   -.3912467
2012 "Burkina Faso" 101.4  271.833   3.347399 1519.6565  82.40362 81.7 27.346   .9 87 90 5.693   -.4308761
2013 "Burkina Faso"  96.6 268.0425   2.653787  1559.985  96.72003 81.9 28.186   .9 82 88 5.607   -.5003924
2014 "Burkina Faso"  92.4  264.252  1.0456479  1576.297  82.30537 82.1 29.024   .9 88 91 5.521   -.5225256
1996 "Burundi"      167.7 357.9225  -9.371049  753.3027 30.871094 70.6  7.412  2.7 79 73 7.267  -1.7493588
1997 "Burundi"      164.4  353.237  -2.923235  731.2819  27.88372 70.9  7.618  2.9 77 74 7.217    -1.70157
1998 "Burundi"      160.5  353.831  3.2777715  755.2516  31.84791 71.2   7.83  3.1 68 65 7.165  -1.6537815
1999 "Burundi"      156.4 354.4245  -2.680635   735.006  30.70991 71.5  8.036  3.2 70 79 7.112  -1.5783404
2000 "Burundi"      152.2 355.0185  -2.957293  713.2698  28.14572 71.8  8.246  3.2 72 80 7.057  -1.5028993
2001 "Burundi"      147.8  355.612  -.5834269  709.1083  28.51732 72.1  8.461  3.1 73 81     7   -1.476642
2002 "Burundi"      143.2  356.206  1.3364574  718.5853 30.483673 72.4  8.682  2.9 75 81 6.939   -1.450385
2003 "Burundi"      138.3 353.0265 -4.4440665  686.6509  30.25594 72.7  8.908  2.7 76 82 6.873  -1.4694716
2004 "Burundi"        133 349.8475  1.2706385  695.3757  42.60213   73  9.139  2.5 78 83 6.803  -1.4845086
2005 "Burundi"      127.1  346.668  -2.566675  677.5277  59.34786 73.3  9.375  2.3 87 87 6.729  -1.1397492
2006 "Burundi"      120.9  343.489   1.744609  689.3479  72.70313 73.5  9.617  2.2 92 92 6.649  -1.0736809
2007 "Burundi"      114.5 340.3095  1.1368152  697.1845 65.868484 73.8  9.864    2 88 99 6.566  -1.1216149
2008 "Burundi"      108.6  333.527   1.389842  706.8743  53.37726 74.1 10.118  1.8 84 92  6.48   -1.123118
2009 "Burundi"      103.5  326.744 -.10958474  706.0997  48.57511 74.4 10.376  1.6 91 94 6.391  -1.0641489
2010 "Burundi"       98.8 319.9615  .23904864  707.7876  61.32776 74.7 10.641  1.5 92 96 6.302  -1.1726482
2011 "Burundi"       94.9 313.1785   .6898832  712.6705  61.53007   75 10.912  1.4 93 96 6.212  -1.1668588
2012 "Burundi"       91.2  306.396  .58354026  716.8292  60.80011 75.3 11.189  1.3 93 96 6.123  -1.2251824
2013 "Burundi"       87.8  301.627  1.1823219  725.3044  60.26276 75.5 11.472  1.2 98 96 6.035  -1.1031541
2014 "Burundi"       84.6 296.8585   1.265698  734.4846  58.01862 75.8 11.761  1.1 94 95 5.948   -.9663085
1996 "Cabo Verde"      53 173.7865   8.461328 2628.1355  94.66525 79.9 49.704  1.4 84 88 4.389   .51188874
1997 "Cabo Verde"      49  168.616     8.3264  2846.964 102.44161 80.5 50.637  1.5 83 87 4.216    .3729435
1998 "Cabo Verde"    44.3 164.5125   9.816393 3126.4336 125.90977 81.1 51.572  1.5 84 88 4.036    .3994993
1999 "Cabo Verde"    39.6  160.408   8.713267  3398.848 123.41257 81.8 52.505  1.6 85 89 3.852    .4424858
2000 "Cabo Verde"    35.5  156.304  11.898556  3803.262 144.97372 82.4 53.435  1.6 86 90 3.666   .48547235
end

Thanks in advance, looking forward to your helpful suggestions.
Bernie Konle

[Phil Bromiley]

Thank you for providing Stata code and data.
I suspect you didn't get a quick answer because you have a complex, long question. A few observations:
1. I don't really understand what you're doing in the loop. Normally, we'd enter time dummies with i.year in the regression.
2. There have been several discussions of related issues in recent days on this list serve. Search for xtreg and xtgls in the listserve. With few panels, long panels, people prefer xtgls, and with more panels but shorter panels xtreg. However, I'm not sure your sample is an obvious call. Sometimes, I like xtregar when there is serial correlation.
3. xtreg with robust standard errors is the normal choice. xtgls is also possible.
4. xtgls, areg, xtpcse, reghdfe. areg is pretty much xtreg,fe so you don't need to worry about it. reghdfe is for higher order effects, but with fixed effects and only year and country, you can include year as dummies and country as panel in xtreg. xtpcse allows more complex error covariances including cross-panel correlations.
4. When you include a continuous variable like gdp_grwrate and a dummy based on that, the dummy is allowing a step function at the point where you're creating it. So, dum=0 if gdp_grwrate<0 and dum=1 if gdp_grwrate>0 will allow for the below and above zero values to have a break. It is essentially testing for a discontinuity at zero.
5. You might also want to allow for different parameters on positive versus negative gdp_grwrate. You do with with factor variable notation: dum##c.dep_grwrate . The ## means it includes the main effects automatically.

[Carlo Lazzaro]

Bernie:
you cannot -xtset- a string variable (see -help encode- on how to solve that issue);
you cannot use clustered standard errors in the dataset example you posted: you can read the reason why in -help j_robustsingular-.
That said, you can replace -cluster()- with -bootstrap- standard errors, like in the following example (which elaborate on your data excerpt):

. encode pays , generate( pays_2 )

. xtset pays_2 annee
       panel variable:  pays_2 (unbalanced)
        time variable:  annee, 1996 to 2014
                delta:  1 unit

. xtreg mort_inf gdp_grwrate depsante_hbt acces_eaupot vih vacc_roug dpt fert govmoy i.annee, fe vce(cluster pays_2)

Fixed-effects (within) regression               Number of obs     =        100
Group variable: pays_2                          Number of groups  =          6

R-sq:                                           Obs per group:
     within  = 0.9681                                         min =          5
     between = 0.5741                                         avg =       16.7
     overall = 0.5261                                         max =         19

                                                F(5,5)            =          .
corr(u_i, Xb)  = -0.0810                        Prob > F          =          .

                                 (Std. Err. adjusted for 6 clusters in pays_2)
------------------------------------------------------------------------------
             |               Robust
    mort_inf |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 gdp_grwrate |   .1723221   .1773506     0.97   0.376    -.2835722    .6282165
depsante_hbt |   .0234119   .0172428     1.36   0.233    -.0209121     .067736
acces_eaupot |  -1.763489   .5968262    -2.95   0.032     -3.29768   -.2292988
         vih |   4.854203   2.248275     2.16   0.083    -.9251708    10.63358
   vacc_roug |   .2461231   .1118072     2.20   0.079    -.0412863    .5335326
         dpt |  -.1661317   .1250074    -1.33   0.241    -.4874735    .1552101
        fert |   10.61804   7.160853     1.48   0.198    -7.789517     29.0256
      govmoy |  -26.60366   4.843767    -5.49   0.003    -39.05496   -14.15236
             |
       annee |
       1997  |  -2.935606   2.299967    -1.28   0.258    -8.847858    2.976647
       1998  |  -2.882678   4.741586    -0.61   0.570    -15.07131    9.305958
       1999  |  -3.218226   6.218245    -0.52   0.627    -19.20274    12.76628
       2000  |  -2.141578    8.04523    -0.27   0.801     -22.8225    18.53934
       2001  |  -4.552925   9.082478    -0.50   0.637    -27.90018    18.79433
       2002  |  -5.250977   10.07545    -0.52   0.625    -31.15074    20.64879
       2003  |  -3.359763   10.54849    -0.32   0.763    -30.47551    23.75598
       2004  |  -7.570902   11.31906    -0.67   0.533    -36.66746    21.52566
       2005  |  -9.091876   10.94486    -0.83   0.444    -37.22652    19.04277
       2006  |  -12.08319   11.38906    -1.06   0.337    -41.35971    17.19334
       2007  |  -14.86438   10.53287    -1.41   0.217    -41.93998    12.21122
       2008  |  -16.67577   11.84402    -1.41   0.218     -47.1218    13.77026
       2009  |  -19.11316    11.9995    -1.59   0.172    -49.95884    11.73253
       2010  |  -23.29474   12.54155    -1.86   0.122    -55.53383    8.944347
       2011  |  -25.13095   12.55364    -2.00   0.102    -57.40111    7.139197
       2012  |  -27.93473   13.79482    -2.03   0.099    -63.39545    7.525982
       2013  |   -30.4602   14.25336    -2.14   0.086    -67.09963    6.179231
       2014  |  -30.91351   13.51807    -2.29   0.071    -65.66282    3.835795
             |
       _cons |   156.6173   47.33727     3.31   0.021     34.93296    278.3016
-------------+----------------------------------------------------------------
     sigma_u |  36.796019
     sigma_e |  5.0487249
         rho |  .98152172   (fraction of variance due to u_i)
------------------------------------------------------------------------------


. xtreg mort_inf gdp_grwrate depsante_hbt acces_eaupot vih vacc_roug dpt fert govmoy i.annee, fe vce(bootstrap, reps(200))
(running xtreg on estimation sample)

Bootstrap replications (200)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
..................................................    50
..................................................   100
..................................................   150
..................................................   200

Fixed-effects (within) regression               Number of obs     =        100
Group variable: pays_2                          Number of groups  =          6

R-sq:                                           Obs per group:
     within  = 0.9681                                         min =          5
     between = 0.5741                                         avg =       16.7
     overall = 0.5261                                         max =         19

                                                Wald chi2(26)     =     172.99
corr(u_i, Xb)  = -0.0810                        Prob > chi2       =     0.0000

                                  (Replications based on 6 clusters in pays_2)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
    mort_inf |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 gdp_grwrate |   .1723221   .2148601     0.80   0.423    -.2487959    .5934402
depsante_hbt |   .0234119   .0459209     0.51   0.610    -.0665914    .1134153
acces_eaupot |  -1.763489   2.968252    -0.59   0.552    -7.581157    4.054178
         vih |   4.854203   8.331961     0.58   0.560    -11.47614    21.18455
   vacc_roug |   .2461231   .2298003     1.07   0.284    -.2042772    .6965235
         dpt |  -.1661317   .2005474    -0.83   0.407    -.5591973    .2269339
        fert |   10.61804   37.78516     0.28   0.779    -63.43951    84.67559
      govmoy |  -26.60366   12.69064    -2.10   0.036    -51.47685    -1.73047
             |
       annee |
       1997  |  -2.935606   2.878315    -1.02   0.308       -8.577    2.705788
       1998  |  -2.882678    5.47045    -0.53   0.598    -13.60456    7.839206
       1999  |  -3.218226   7.791552    -0.41   0.680    -18.48939    12.05294
       2000  |  -2.141578   10.32279    -0.21   0.836    -22.37387    18.09071
       2001  |  -4.552925   13.18836    -0.35   0.730    -30.40163    21.29578
       2002  |  -5.250977   15.87435    -0.33   0.741    -36.36412    25.86217
       2003  |  -3.359763   18.19378    -0.18   0.853    -39.01892     32.2994
       2004  |  -7.570902   20.95743    -0.36   0.718    -48.64671     33.5049
       2005  |  -9.091876   23.86354    -0.38   0.703    -55.86356    37.67981
       2006  |  -12.08319   26.77779    -0.45   0.652    -64.56668    40.40031
       2007  |  -14.86438   29.61581    -0.50   0.616    -72.91029    43.18153
       2008  |  -16.67577   33.09654    -0.50   0.614     -81.5438    48.19226
       2009  |  -19.11316     36.363    -0.53   0.599    -90.38333    52.15702
       2010  |  -23.29474   39.55801    -0.59   0.556     -100.827    54.23752
       2011  |  -25.13095   42.30669    -0.59   0.552    -108.0505    57.78863
       2012  |  -27.93473   45.58333    -0.61   0.540    -117.2764    61.40695
       2013  |   -30.4602   48.72307    -0.63   0.532    -125.9557    65.03525
       2014  |  -30.91351   50.91944    -0.61   0.544    -130.7138    68.88675
             |
       _cons |   156.6173   368.9304     0.42   0.671     -566.473    879.7076
-------------+----------------------------------------------------------------
     sigma_u |  36.796019
     sigma_e |  5.0487249
         rho |  .98152172   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. testparm(i.annee )

 ( 1)  1997.annee = 0
 ( 2)  1998.annee = 0
 ( 3)  1999.annee = 0
 ( 4)  2000.annee = 0
 ( 5)  2001.annee = 0
 ( 6)  2002.annee = 0
 ( 7)  2003.annee = 0
 ( 8)  2004.annee = 0
 ( 9)  2005.annee = 0
 (10)  2006.annee = 0
 (11)  2007.annee = 0
 (12)  2008.annee = 0
 (13)  2009.annee = 0
 (14)  2010.annee = 0
 (15)  2011.annee = 0
 (16)  2012.annee = 0
 (17)  2013.annee = 0
 (18)  2014.annee = 0

           chi2( 18) =   26.93
         Prob > chi2 =    0.0803

.

[Bernie konle]

Thanks to all of you for your helpful comments. Phil, I agree with on the length and complexity of my questions. It came to my mind when I checked and there were still no reply. But I couldn't edit it any longer.

Thanks so much to both of you.