Panel data analysis error message insufficient observations

[Eszti Bambacht]

I have a problem running my panel data regression analysis. I want to examine the effect of terrorism on the M&A deals to a certain country in a specific year.

xtset dealid year, yearly


xtreg MA busterr target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log distance colony

Dealid is the number I assigned to all observations in my dataset.
Running this regression a got the following error message:

insufficient observations
r(2001);

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(dealid year MA) long busterr float(target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log) double distance byte colony
  1 1995       1  0  21.60889  26.82477 22.450573  27.11052 1652.2680196256638 0
  2 1999     4.7  0 21.951374 25.682894 22.635855   26.2123  451.4164096862793 0
  3 2000      16  0  22.01306  26.33266 22.700394  26.97888 1048.1704196635724 1
  4 2000      16  0  22.01306  26.33266 22.700394  26.97888 1048.1704196635724 1
  5 2003   2.287  0 22.471935  26.03116 22.874374  26.38604  451.4164096862793 0
  6 2004     126  0 22.713175  26.43006   22.9299  26.60881  848.8387590137959 0
  7 2005   6.712  0  22.82233 28.247644  22.98553  28.40054  722.9528244365692 0
  8 2006    40.8  0  22.91967 28.295065  23.03842 28.420404  722.9528244365692 0
  9 2007   2.863  0 23.093605 23.904543 23.095743 23.931263  1363.566163206029 0
 10 2007   156.9  0 23.093605 28.420866 23.095743 28.435036  722.9528244365692 0
 11 2007 161.117  0 23.093605  27.23912 23.095743 27.330397 1048.1704196635724 1
 12 2008   3.009  0 23.279047 26.593864  23.13266 26.525227  451.4164096862793 0
 13 2009 144.047  0  23.21185 26.052015  23.16564  26.03581 1037.8473058279037 0
 14 2009  62.137  0  23.21185  26.52236  23.16564 26.481266  451.4164096862793 0
 15 2009    7.95  0  23.21185  26.78495  23.16564  26.94359 2940.6366864788056 0
 16 2011  33.996  0 23.279785  28.21248  23.22725 28.140333  7842.518149364852 0
 17 2012      .5  0  23.23447  28.23221  23.24135  28.15764  7842.518149364852 0
 18 2014   4.144  0  23.30562   28.2184 23.268894 28.210243  7842.518149364852 0
 19 2016  44.699  0 23.196764         .  23.32406         .                  . .
 20 1991    .692  1   24.5457  27.87441  25.23287  28.28704 1233.8113884818076 1
 21 1999    42.3  3 24.607723  26.81452 25.390104 27.281206  1814.178711369133 0
 22 2000    22.5  7  24.72678  26.75262  25.42759 27.464983 16543.648305107497 0
 23 2000      50  7  24.72678 25.967733  25.42759  26.66139 4074.5293987268446 0
 24 2000      55  7  24.72678 29.961687  25.42759  30.17365  8125.746360914612 0
 25 2003   2.514  3  24.94077   25.1412  25.58135  25.72815   2670.09458589592 0
 26 2004     740  2 25.169733  26.30057 25.623466 26.711403  2776.679184100914 0
 27 2004      25  2 25.169733  28.50589 25.623466 28.476164 1897.1870314235687 0
 28 2006   18.26  4 25.485674  27.86574  25.69757 27.977964  806.5022329710483 0
 29 2007  46.853  7  25.62837  25.59448  25.73074 25.946846   2670.09458589592 0
 30 2008  82.319  5 25.864933  28.70379  25.75407 28.614775 1233.8113884818076 1
 31 2008  82.319  5 25.864933  28.70379  25.75407 28.614775 1233.8113884818076 1
 32 2010  20.194  3 25.805956  23.99759 25.805956  23.99759 3029.2130556757925 0
 33 2010  20.194  3 25.805956  23.99759 25.805956  23.99759 3029.2130556757925 0
 34 2013 1752.87  2 26.069206  27.53948 25.894957 27.522614 11682.658921694183 0
 35 2013    9.77  2 26.069206  27.93987 25.894957  27.93287  806.5022329710483 0
 36 2016      55  0  25.79248   28.6059  26.00156  28.64539                  . .
 37 2001      10  0         .  26.66054         .   27.4841                  . .
 38 2014  25.556  0 20.281654  27.97556 20.111086  27.84156                  . .
 39 2015    2.74  0 20.306234         .  20.12349         .                  . .
 40 2015   6.782  0 20.306234  30.03478  20.12349 29.818005                  . .
 41 2015  15.478  0 20.306234  26.45791  20.12349 26.300743                  . .
 42 1999   13.26  0  20.93828  28.14122 21.669924 28.334686 1140.9474403908252 0
 43 2000   6.067  0 21.084034 27.112503   21.7046  27.77034  519.3864007539153 0
 44 2012   11.82  0   21.8753  27.22762  21.87006  27.11959  701.2179800022125 0
 45 2016  32.768  0  21.77357   30.5555 21.916727  30.45954                  . .
 46 2001    19.1  3  22.91336  28.11438 24.306593 28.395796  7092.603116264343 0
 47 2005     175  0  24.06378 30.203154  24.55681  30.29881 12153.605614564514 0
 48 2006    .752  0  24.45591   27.3401  24.74524  27.65363 12954.905818159867 0
 49 2006    .675  0  24.45591  30.25973  24.74524  30.32513 12153.605614564514 0
 50 2012    15.3  0 25.471657  26.70552  25.22442  26.70519 2579.6722784971234 0
 51 2014    1520  0 25.565695         .  25.33726         . 10914.782185473632 0
 52 2010    18.7  0         . 26.155405         . 26.155405  15510.34696298828 0
 53 2016  11.275  0         .  20.48292         .  20.41951                  . .
 54 1991      12  0 19.992846 29.451374   20.3771 29.834637  3965.092480428505 0
 55 1998  24.064  0  20.40562 29.838104  20.62358 30.087757  3965.092480428505 0
 56 2000     5.5  0  20.53713  27.33301  20.72476  27.92573  4157.128729905128 0
 57 2001    12.5  0 20.501047  22.02631  20.67395 22.391563 1720.8136657287598 0
 58 2003  46.981  0 20.567364  26.86928 20.742954  27.55213  16622.68066688919 0
 59 2003  46.981  0 20.567364  26.86928 20.742954  27.55213  16622.68066688919 0
 60 2004      40  0 20.639425  30.13858 20.798735  30.26591  3965.092480428505 0
 61 2005   6.356  0 20.745214   27.2654  20.86089  27.62428  16622.68066688919 0
 62 2005 153.337  0 20.745214  28.55556  20.86089 28.506657 6539.8592375068665 1
 63 2005 153.337  0 20.745214  28.55556  20.86089 28.506657 6539.8592375068665 1
 64 2005 153.337  0 20.745214  28.55556  20.86089 28.506657 6539.8592375068665 1
 65 2006  84.681  0   20.8691  28.62153   20.9807  28.53092 6539.8592375068665 1
 66 2006     5.1  0   20.8691  30.25973   20.9807  30.32513  3965.092480428505 0
 67 2007   1.359  0  20.99436 30.303627 21.069254  30.34276  3965.092480428505 0
 68 2008       3  0  21.03693  27.68488  21.06895  27.72675  16622.68066688919 0
 69 2012       7  0  20.91505 26.390253  20.87863  26.28725  17456.16353701172 0
 70 2015    .911  0  21.03432  26.45791  20.96715 26.300743 15622.458910351563 0
 71 1990  18.592 20  25.67452  26.61175  25.99322 27.444164 19110.127210772705 0
 72 1990     571 20  25.67452  27.00572  25.99322 27.495367 10079.656656066894 1
 73 1990      80 20  25.67452  29.41937  25.99322 29.835377  8678.352271958924 0
 74 1991    97.9  3 25.968815 27.078676  26.11251  27.52051 10079.656656066894 1
 75 1991      23  3 25.968815 29.451374  26.11251 29.834637  8678.352271958924 0
 76 1992  13.029 14 26.156065 26.716227  26.22531 27.817595  2391.846403179836 0
 77 1992 396.155 14 26.156065  27.10743  26.22531   27.6323  9391.460933694458 0
 78 1992 396.155 14 26.156065  27.10743  26.22531   27.6323  9391.460933694458 0
 79 1992 233.078 14 26.156065  24.55113  26.22531 25.270695 1156.7258914702415 0
 80 1992 233.078 14 26.156065  24.55113  26.22531 25.270695 1156.7258914702415 0
 81 1992  15.958 14 26.156065  24.74836  26.22531  25.19811 10913.810616272734 0
 82 1992 281.352 14 26.156065  27.90547  26.22531 28.213743  11214.01020098114 0
 83 1992 281.352 14 26.156065  27.90547  26.22531 28.213743  11214.01020098114 0
 84 1992 281.352 14 26.156065  27.90547  26.22531 28.213743  11214.01020098114 0
 85 1992    .234 14 26.156065 25.436867  26.22531 25.836197 17137.094580753324 0
 86 1992   1.858 14 26.156065  27.79625  26.22531  28.12005 11136.962471050261 0
 87 1992 138.976 14 26.156065  29.50885  26.22531 29.869574  8678.352271958924 0
 88 1993  11.696  0 26.190235  26.46746   26.2827 27.179417 12044.573995607949 0
 89 1993  12.499  0 26.190235 26.805025   26.2827  27.86319  2391.846403179836 0
 90 1993  12.499  0 26.190235 26.805025   26.2827  27.86319  2391.846403179836 0
 91 1993  14.281  0 26.190235 27.081404   26.2827 27.658506  9391.460933694458 0
 92 1993  23.796  0 26.190235         .   26.2827         .  6251.536736663818 0
 93 1993  12.241  0 26.190235 24.621145   26.2827   25.3345 1156.7258914702415 0
 94 1993     1.7  0 26.190235 24.745085   26.2827  25.81582  4615.471325676345 0
 95 1993 238.328  0 26.190235  26.98409   26.2827  27.51939 10079.656656066894 1
 96 1993  48.743  0 26.190235   27.6906   26.2827  28.14501 11136.962471050261 0
 97 1993  48.743  0 26.190235   27.6906   26.2827  28.14501 11136.962471050261 0
 98 1993  43.814  0 26.190235 29.559454   26.2827  29.89666  8678.352271958924 0
 99 1993  43.814  0 26.190235 29.559454   26.2827  29.89666  8678.352271958924 0
100 1993  11.736  0 26.190235  24.78585   26.2827 26.337206  4886.742732406616 0
end
format %ty year

[Eszti Bambacht]

the first code was of random effects::
xtreg MA busterr target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log distance colony, re

for fixed effects:
xtreg MA busterr target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log distance colony, fe

and I got the following error for that:

note: busterr omitted because of collinearity
note: target_gdp_log omitted because of collinearity
note: acquiror_gdp_log omitted because of collinearity
note: target_gdpgrowth_log omitted because of collinearity
note: acquiror_gdpgrowth_log omitted because of collinearity
note: distance omitted because of collinearity
note: colony omitted because of collinearity

[Clyde Schechter]

This is a somewhat obscure problem, but I have encountered it before.

You are doing a random-effects regression, using -xtreg, re-. In Stata, -xtreg, re- is implemented by doing a combination of -xtreg, fe- and -xtreg, be- and then calculating a weighted average of the results.

But you have only one observation for each dealid, so the -xtreg, fe- part of this fails: with only one observation for each dealid it is impossible to estimate within-dealid effects. And with only one observation per dealid, every variable is necessarily colinear with the fixed effects! So Stata can't put that together with the -xtreg, be- results and -xtreg, re- thus fails. The error message does not really convey the gist of the problem. But that's what it's all about.

Now, having only one observation per dealid, you shouldn't be using panel estimators here: just use ordinary linear regression.

[Eszti Bambacht]

Okay, that makes sense. However, my supervisor told me to do a panel data analysis.
I tried to collapse all the data in my dataset, but then I will miss some information.

For example, when I have 3 deals from Albania to 3 diferent countries in 2007

year	acqnatname	acqnatcode	tarnatname	tarnatcode	dealvalue
2007	Italy	IT	Albania	AA	156.9
2007	Turkey	TK	Albania	AA	161.117
2007	Cyprus	CY	Albania	AA	2.863

I could collapse everything based on the target country, Albania, and the sum of the dealvalue. However, some of my other variables are country-pair specific. like the distance between the acquiror en the target country. So this is not possible.

And doing panel data with the target country)tarnatname) as group variable and year as time variable is not possible, because I will have multiple years in my panel data.

So, you are saying that panel data is not the right analysis for this research?

[Clyde Schechter]

No, what I'm saying is that you can't use dealid as the panel identifier. It seems to me that the natural panel identifier for your situation is the target-acquirer nation pair:

egen panel_id = group(tarnatname acqnatname)
xtset panel_id

Don't worry if you have multiple observations in the same time period within this panel identifier. The -xtset- command does not require a time variable--that's optional. And you only need the time variable specified if you are going to use time series operators like lags and leads, or model autoregressive correlation structures. It seems unlikely that your situation would call for those things (and they aren't possible in any case). So I think it's just a matter of getting the panel identifier properly set, and the code shown here will, I think, do it.

[Eric de Souza]

With the information you provided in your first post, there was no way of knowing what your panel variable was other than dealid which, as Clyde,said, has one observation for each value of dealid.

Now you are adding additional information, namely, that for each (?) year there is an acquisition country and a target country. So you have to set up your data accordingly

Sorry but I have to leave now, but it would help if you provide a few more observations with year, acqnatcode tarnatcode.

Also whether for you have data on acqnatcode and tarnatcode for every year.

Crossed with #5 where Clyde assumes what I thought is the case but wanted to be sure first. He has also told you what to do in that case to set up your data properly.

[Eszti Bambacht]

Thank you, I didn't know the panel identifier was wrong. What Clyde said is right, it is about the target-acquirer group. I ran my regression and it worked.
Eric de Souza Sorry for the lack of information. I have multiple deals per year, and thus multiple target-acquirer pairs.


I have to do a fixed effect regression, according to the Hausman test. Do I automatically control for time fixed-effects and country fixed effect within the analysis?


Furthermore, some of my variables are omitted because of collinearity. For example, the distance between the target and the acquirer is omitted. This is logical, because the distance doesn't change over time. But is there a way that it can still be included in the regression?

I did the following regression analysis:

xtreg MA terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distance acquiror_area target_area colony comcur comrelig, fe

* Example generated by -dataex-. To install: ssc install dataex
clear
input float MA long(target acquiror) float(terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log) byte comlang double distance long(acquiror_area target_area) byte(colony comcur) float comrelig
      1 2 132   0  21.60889  26.82477 22.450573  27.11052 0 1652.2680196256638   41863   28748 0 0     .00205
    4.7 2  68   3 21.951374 25.682894 22.635855   26.2123 0  451.4164096862793  131621   28748 0 0    .003075
     16 2 188   2  22.01306  26.33266 22.700394  26.97888 0 1048.1704196635724  780576   28748 1 0     .20336
     16 2 188   2  22.01306  26.33266 22.700394  26.97888 0 1048.1704196635724  780576   28748 1 0     .20336
  2.287 2  68   1 22.471935  26.03116 22.874374  26.38604 0  451.4164096862793  131621   28748 0 0    .003075
    126 2  13   0 22.713175  26.43006   22.9299  26.60881 0  848.8387590137959   83858   28748 0 0     .00123
  6.712 2  89   0  22.82233 28.247644  22.98553  28.40054 0  722.9528244365692  301323   28748 0 0    .000205
   40.8 2  89   0  22.91967 28.295065  23.03842 28.420404 0  722.9528244365692  301323   28748 0 0    .000205
  2.863 2  43   0 23.093605 23.904543 23.095743 23.931263 0  1363.566163206029    9251   28748 0 0    .037925
  156.9 2  89   0 23.093605 28.420866 23.095743 28.435036 0  722.9528244365692  301323   28748 0 0    .000205
161.117 2 188   0 23.093605  27.23912 23.095743 27.330397 0 1048.1704196635724  780576   28748 1 0     .20336
  3.009 2  68   0 23.279047 26.593864  23.13266 26.525227 0  451.4164096862793  131621   28748 0 0    .003075
144.047 2  44   1  23.21185 26.052015  23.16564  26.03581 0 1037.8473058279037   78864   28748 0 0          0
 62.137 2  68   1  23.21185  26.52236  23.16564 26.481266 0  451.4164096862793  131621   28748 0 0    .003075
   7.95 2 158   1  23.21185  26.78495  23.16564  26.94359 0 2940.6366864788056 2153168   28748 0 0     .20254
 33.996 2  33   0 23.279785  28.21248  23.22725 28.140333 0  7842.518149364852 9976139   28748 0 0     .00123
     .5 2  33   0  23.23447  28.23221  23.24135  28.15764 0  7842.518149364852 9976139   28748 0 0     .00123
  4.144 2  33   2  23.30562   28.2184 23.268894 28.210243 0  7842.518149364852 9976139   28748 0 0     .00123
 44.699 2  27   2 23.196764         .  23.32406         . .                  .       .       . . .          .
   .692 3  61  30   24.5457  27.87441  25.23287  28.28704 1 1233.8113884818076  547026 2381741 1 0 .033549998
   42.3 3 132 106 24.607723  26.81452 25.390104 27.281206 0  1814.178711369133   41863 2381741 0 0     .01204
   22.5 3  12 138  24.72678  26.75262  25.42759 27.464983 0 16543.648305107497 7686848 2381741 0 0    .003462
     50 3 158 138  24.72678 25.967733  25.42759  26.66139 1 4074.5293987268446 2153168 2381741 0 0    .979113
     55 3 195 138  24.72678 29.961687  25.42759  30.17365 0  8125.746360914612 9529106 2381741 0 0    .009428
  2.514 3  51  75  24.94077   25.1412  25.58135  25.72815 1   2670.09458589592 1001449 2381741 0 0    .810648
    740 3 139  67 25.169733  26.30057 25.623466 26.711403 0  2776.679184100914  323752 2381741 0 0    .001006
     25 3 194  67 25.169733  28.50589 25.623466 28.476164 0 1897.1870314235687  244110 2381741 0 0    .014529
  18.26 3 170 152 25.485674  27.86574  25.69757 27.977964 0  806.5022329710483  505954 2381741 0 0    .004845
 46.853 3  51 124  25.62837  25.59448  25.73074 25.946846 1   2670.09458589592 1001449 2381741 0 0    .810648
 82.319 3  61 107 25.864933  28.70379  25.75407 28.614775 1 1233.8113884818076  547026 2381741 1 0 .033549998
 82.319 3  61 107 25.864933  28.70379  25.75407 28.614775 1 1233.8113884818076  547026 2381741 1 0 .033549998
 20.194 3  94 100 25.805956  23.99759 25.805956  23.99759 1 3029.2130556757925   91862 2381741 0 0    .921715
 20.194 3  94 100 25.805956  23.99759 25.805956  23.99759 1 3029.2130556757925   91862 2381741 0 0    .921715
1752.87 3  83  22 26.069206  27.53948 25.894957 27.522614 0 11682.658921694183 1933658 2381741 0 0    .430229
   9.77 3 170  22 26.069206  27.93987 25.894957  27.93287 0  806.5022329710483  505954 2381741 0 0    .004845
     55 3 194   9  25.79248   28.6059  26.00156  28.64539 .                  .       .       . . .          .
     10 4  12   0         .  26.66054         .   27.4841 .                  .       .       . . .          .
 25.556 4 168   0 20.281654  27.97556 20.111086  27.84156 .                  .       .       . . .          .
   2.74 4  27   0 20.306234         .  20.12349         . .                  .       .       . . .          .
  6.782 4  37   0 20.306234  30.03478  20.12349 29.818005 .                  .       .       . . .          .
 15.478 4  79   0 20.306234  26.45791  20.12349 26.300743 .                  .       .       . . .          .
  13.26 5 194   0  20.93828  28.14122 21.669924 28.334686 0 1140.9474403908252  244110     453 0 0       .131
  6.067 5 170   0 21.084034 27.112503   21.7046  27.77034 1  519.3864007539153  505954     453 0 1       .969
  11.82 5 180   0   21.8753  27.22762  21.87006  27.11959 0  701.2179800022125   41288     453 0 0       .528
 32.768 5 195   0  21.77357   30.5555 21.916727  30.45954 .                  .       .       . . .          .
   19.1 6 194  40  22.91336  28.11438 24.306593 28.395796 0  7092.603116264343  244110 1246700 0 0    .121875
    175 6 195   0  24.06378 30.203154  24.55681  30.29881 0 12153.605614564514 9529106 1246700 0 0    .292428
   .752 6  12   0  24.45591   27.3401  24.74524  27.65363 0 12954.905818159867 7686848 1246700 0 0    .249882
   .675 6 195   0  24.45591  30.25973  24.74524  30.32513 0 12153.605614564514 9529106 1246700 0 0    .292428
   15.3 6 167   0 25.471657  26.70552  25.22442  26.70519 0 2579.6722784971234 1219912 1246700 0 0  .14866799
   1520 6  34   0 25.565695         .  25.33726         . 0 10914.782185473632     262 1246700 0 0    .200814
   18.7 7  79   0         . 26.155405         . 26.155405 1  15510.34696298828    1092     102 0 0          .
 11.275 7 203   0         .  20.48292         .  20.41951 .                  .       .       . . .          .
     12 8 195   0 19.992846 29.451374   20.3771 29.834637 1  3965.092480428505 9529106     442 0 0    .214624
 24.064 8 195   0  20.40562 29.838104  20.62358 30.087757 1  3965.092480428505 9529106     442 0 0    .214624
    5.5 8  33   0  20.53713  27.33301  20.72476  27.92573 1  4157.128729905128 9976139     442 0 0    .172468
   12.5 8  22   0 20.501047  22.02631  20.67395 22.391563 1 1720.8136657287598      53     442 0 0    .132912
 46.981 8  12   0 20.567364  26.86928 20.742954  27.55213 1  16622.68066688919 7686848     442 0 0     .12937
 46.981 8  12   0 20.567364  26.86928 20.742954  27.55213 1  16622.68066688919 7686848     442 0 0     .12937
     40 8 195   0 20.639425  30.13858 20.798735  30.26591 1  3965.092480428505 9529106     442 0 0    .214624
  6.356 8  12   0 20.745214   27.2654  20.86089  27.62428 1  16622.68066688919 7686848     442 0 0     .12937
153.337 8 194   0 20.745214  28.55556  20.86089 28.506657 1 6539.8592375068665  244110     442 1 0     .08136
153.337 8 194   0 20.745214  28.55556  20.86089 28.506657 1 6539.8592375068665  244110     442 1 0     .08136
153.337 8 194   0 20.745214  28.55556  20.86089 28.506657 1 6539.8592375068665  244110     442 1 0     .08136
 84.681 8 194   0   20.8691  28.62153   20.9807  28.53092 1 6539.8592375068665  244110     442 1 0     .08136
    5.1 8 195   0   20.8691  30.25973   20.9807  30.32513 1  3965.092480428505 9529106     442 0 0    .214624
  1.359 8 195   0  20.99436 30.303627 21.069254  30.34276 1  3965.092480428505 9529106     442 0 0    .214624
      3 8  12   0  21.03693  27.68488  21.06895  27.72675 1  16622.68066688919 7686848     442 0 0     .12937
      7 8 164   0  20.91505 26.390253  20.87863  26.28725 1  17456.16353701172     646     442 0 0    .016462
   .911 8  79   0  21.03432  26.45791  20.96715 26.300743 1 15622.458910351563    1092     442 0 0    .039728
 18.592 9  37  31  25.67452  26.61175  25.99322 27.444164 0 19110.127210772705 9572378 2766889 0 0    .000048
    571 9 170  31  25.67452  27.00572  25.99322 27.495367 1 10079.656656066894  505954 2766889 1 0    .887631
     80 9 195  31  25.67452  29.41937  25.99322 29.835377 0  8678.352271958924 9529106 2766889 0 0  .28658798
   97.9 9 170  27 25.968815 27.078676  26.11251  27.52051 1 10079.656656066894  505954 2766889 1 0    .887631
     23 9 195  27 25.968815 29.451374  26.11251 29.834637 0  8678.352271958924 9529106 2766889 0 0  .28658798
 13.029 9  26  41 26.156065 26.716227  26.22531 27.817595 0  2391.846403179836 8511920 2766889 0 0     .80533
396.155 9  33  41 26.156065  27.10743  26.22531   27.6323 0  9391.460933694458 9976139 2766889 0 0     .43486
396.155 9  33  41 26.156065  27.10743  26.22531   27.6323 0  9391.460933694458 9976139 2766889 0 0     .43486
233.078 9  36  41 26.156065  24.55113  26.22531 25.270695 1 1156.7258914702415  756945 2766889 0 0    .752549
233.078 9  36  41 26.156065  24.55113  26.22531 25.270695 1 1156.7258914702415  756945 2766889 0 0    .752549
 15.958 9  86  41 26.156065  24.74836  26.22531  25.19811 0 10913.810616272734   70285 2766889 0 0    .873245
281.352 9  89  41 26.156065  27.90547  26.22531 28.213743 0  11214.01020098114  301323 2766889 0 0   .7622219
281.352 9  89  41 26.156065  27.90547  26.22531 28.213743 0  11214.01020098114  301323 2766889 0 0   .7622219
281.352 9  89  41 26.156065  27.90547  26.22531 28.213743 0  11214.01020098114  301323 2766889 0 0   .7622219
   .234 9 184  41 26.156065 25.436867  26.22531 25.836197 0 17137.094580753324  513115 2766889 0 0    .003796
  1.858 9 194  41 26.156065  27.79625  26.22531  28.12005 0 11136.962471050261  244110 2766889 0 0    .124371
138.976 9 195  41 26.156065  29.50885  26.22531 29.869574 0  8678.352271958924 9529106 2766889 0 0  .28658798
 11.696 9  12   1 26.190235  26.46746   26.2827 27.179417 0 12044.573995607949 7686848 2766889 0 0    .277485
 12.499 9  26   1 26.190235 26.805025   26.2827  27.86319 0  2391.846403179836 8511920 2766889 0 0     .80533
 12.499 9  26   1 26.190235 26.805025   26.2827  27.86319 0  2391.846403179836 8511920 2766889 0 0     .80533
 14.281 9  33   1 26.190235 27.081404   26.2827 27.658506 0  9391.460933694458 9976139 2766889 0 0     .43486
 23.796 9  34   1 26.190235         .   26.2827         . 0  6251.536736663818     262 2766889 0 0    .048764
 12.241 9  36   1 26.190235 24.621145   26.2827   25.3345 1 1156.7258914702415  756945 2766889 0 0    .752549
    1.7 9  38   1 26.190235 24.745085   26.2827  25.81582 1  4615.471325676345 1141748 2766889 0 0    .885103
238.328 9 170   1 26.190235  26.98409   26.2827  27.51939 1 10079.656656066894  505954 2766889 1 0    .887631
 48.743 9 194   1 26.190235   27.6906   26.2827  28.14501 0 11136.962471050261  244110 2766889 0 0    .124371
 48.743 9 194   1 26.190235   27.6906   26.2827  28.14501 0 11136.962471050261  244110 2766889 0 0    .124371
 43.814 9 195   1 26.190235 29.559454   26.2827  29.89666 0  8678.352271958924 9529106 2766889 0 0  .28658798
 43.814 9 195   1 26.190235 29.559454   26.2827  29.89666 0  8678.352271958924 9529106 2766889 0 0  .28658798
 11.736 9 201   1 26.190235  24.78585   26.2827 26.337206 1  4886.742732406616  911930 2766889 0 0    .868638
149.985 9  12  14  26.27405  26.50159  26.33942 27.219133 0 12044.573995607949 7686848 2766889 0 0    .277485
149.985 9  12  14  26.27405  26.50159  26.33942 27.219133 0 12044.573995607949 7686848 2766889 0 0    .277485
 19.857 9  33  14  26.27405  27.08308  26.33942  27.70246 0  9391.460933694458 9976139 2766889 0 0     .43486
 19.857 9  33  14  26.27405  27.08308  26.33942  27.70246 0  9391.460933694458 9976139 2766889 0 0     .43486
 19.857 9  33  14  26.27405  27.08308  26.33942  27.70246 0  9391.460933694458 9976139 2766889 0 0     .43486
 64.497 9  36  14  26.27405 24.766464  26.33942  25.38358 1 1156.7258914702415  756945 2766889 0 0    .752549
 64.497 9  36  14  26.27405 24.766464  26.33942  25.38358 1 1156.7258914702415  756945 2766889 0 0    .752549
239.996 9  61  14  26.27405  27.96866  26.33942 28.319946 0 10932.340734829711  547026 2766889 0 0    .700532
 32.986 9  86  14  26.27405 24.769226  26.33942  25.28064 0 10913.810616272734   70285 2766889 0 0    .873245
 32.986 9  86  14  26.27405 24.769226  26.33942  25.28064 0 10913.810616272734   70285 2766889 0 0    .873245
 32.986 9  86  14  26.27405 24.769226  26.33942  25.28064 0 10913.810616272734   70285 2766889 0 0    .873245
 44.996 9  89  14  26.27405 27.722315  26.33942  28.22646 0  11214.01020098114  301323 2766889 0 0   .7622219
  99.99 9 117  14  26.27405  26.99107  26.33942 27.315214 1   7533.98598147583 1967210 2766889 0 0    .867776
 109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
 109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
 109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
 109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
 52.768 9  26  16  26.27635  27.38977 26.310556  27.95838 0  2391.846403179836 8511920 2766889 0 0     .80533
 52.768 9  26  16  26.27635  27.38977 26.310556  27.95838 0  2391.846403179836 8511920 2766889 0 0     .80533
 96.111 9  33  16  26.27635  27.12689 26.310556 27.728886 0  9391.460933694458 9976139 2766889 0 0     .43486
 96.111 9  33  16  26.27635  27.12689 26.310556 27.728886 0  9391.460933694458 9976139 2766889 0 0     .43486
 96.111 9  33  16  26.27635  27.12689 26.310556 27.728886 0  9391.460933694458 9976139 2766889 0 0     .43486
    475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
    475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
    475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
    475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
   20.7 9  61  16  26.27635  28.10719 26.310556 28.340584 0 10932.340734829711  547026 2766889 0 0    .700532
     50 9  65  16  26.27635 28.583303 26.310556 28.675167 0  11646.03295689621  357325 2766889 0 0   .3331284
  96.96 9 117  16  26.27635 26.563305 26.310556 27.255903 1   7533.98598147583 1967210 2766889 0 0    .867776
 74.999 9 143  16  26.27635   22.9823 26.310556   23.2874 1  5126.518599275684   75648 2766889 0 0    .780094
156.231 9 170  16  26.27635 27.141533 26.310556  27.57014 1 10079.656656066894  505954 2766889 1 0    .887631
  5.001 9 194  16  26.27635 27.920116 26.310556  28.20747 0 11136.962471050261  244110 2766889 0 0    .124371
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
  173.7 9  20  19  26.32962 26.362894  26.36435   26.6171 0   11305.2858804924   33114 2766889 0 0     .82453
  173.7 9  20  19  26.32962 26.362894  26.36435   26.6171 0   11305.2858804924   33114 2766889 0 0     .82453
  173.7 9  20  19  26.32962 26.362894  26.36435   26.6171 0   11305.2858804924   33114 2766889 0 0     .82453
end
label values acquiror countrynames
label values target countrynames

[Carlo Lazzaro]

Eszti:
I was not able to replicate your panel data regression, as the reported example of your dataset does not seem to include -panelvar- and -timevar-.
That said:
- fe- estimator gets rid of time-invariant heterogeneity, but is comes at the cost of making the estimate of time-invariant coefficients unfeasible;
- if, as it is often the case, you want to estimate the coefficients of time-invariant predictors, you may want to consider -mundlak-, that relaxes one of the overrestrictions of -re- specification, that is the uncorrelation of the ui term with the vector of regressors.

[Eszti Bambacht]

I included panel_id and year in the dataex.
So I need to use mundlak instead of Hausman?

xtset panel_id
xtreg MA terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distance acquiror_area target_area colony comcur comrelig, fe

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(panel_id year MA) long(target acquiror) float(terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log) byte comlang double distance long(acquiror_area target_area) byte(colony comcur) float comrelig
 8 1995       1 2 132   0  21.60889  26.82477 22.450573  27.11052 0 1652.2680196256638   41863   28748 0 0     .00205
 6 1999     4.7 2  68   3 21.951374 25.682894 22.635855   26.2123 0  451.4164096862793  131621   28748 0 0    .003075
10 2000      16 2 188   2  22.01306  26.33266 22.700394  26.97888 0 1048.1704196635724  780576   28748 1 0     .20336
10 2000      16 2 188   2  22.01306  26.33266 22.700394  26.97888 0 1048.1704196635724  780576   28748 1 0     .20336
 6 2003   2.287 2  68   1 22.471935  26.03116 22.874374  26.38604 0  451.4164096862793  131621   28748 0 0    .003075
 1 2004     126 2  13   0 22.713175  26.43006   22.9299  26.60881 0  848.8387590137959   83858   28748 0 0     .00123
 7 2005   6.712 2  89   0  22.82233 28.247644  22.98553  28.40054 0  722.9528244365692  301323   28748 0 0    .000205
 7 2006    40.8 2  89   0  22.91967 28.295065  23.03842 28.420404 0  722.9528244365692  301323   28748 0 0    .000205
 4 2007   2.863 2  43   0 23.093605 23.904543 23.095743 23.931263 0  1363.566163206029    9251   28748 0 0    .037925
 7 2007   156.9 2  89   0 23.093605 28.420866 23.095743 28.435036 0  722.9528244365692  301323   28748 0 0    .000205
10 2007 161.117 2 188   0 23.093605  27.23912 23.095743 27.330397 0 1048.1704196635724  780576   28748 1 0     .20336
 6 2008   3.009 2  68   0 23.279047 26.593864  23.13266 26.525227 0  451.4164096862793  131621   28748 0 0    .003075
 5 2009 144.047 2  44   1  23.21185 26.052015  23.16564  26.03581 0 1037.8473058279037   78864   28748 0 0          0
 6 2009  62.137 2  68   1  23.21185  26.52236  23.16564 26.481266 0  451.4164096862793  131621   28748 0 0    .003075
 9 2009    7.95 2 158   1  23.21185  26.78495  23.16564  26.94359 0 2940.6366864788056 2153168   28748 0 0     .20254
 3 2011  33.996 2  33   0 23.279785  28.21248  23.22725 28.140333 0  7842.518149364852 9976139   28748 0 0     .00123
 3 2012      .5 2  33   0  23.23447  28.23221  23.24135  28.15764 0  7842.518149364852 9976139   28748 0 0     .00123
 3 2014   4.144 2  33   2  23.30562   28.2184 23.268894 28.210243 0  7842.518149364852 9976139   28748 0 0     .00123
 2 2016  44.699 2  27   2 23.196764         .  23.32406         . .                  .       .       . . .          .
13 1991    .692 3  61  30   24.5457  27.87441  25.23287  28.28704 1 1233.8113884818076  547026 2381741 1 0 .033549998
16 1999    42.3 3 132 106 24.607723  26.81452 25.390104 27.281206 0  1814.178711369133   41863 2381741 0 0     .01204
11 2000    22.5 3  12 138  24.72678  26.75262  25.42759 27.464983 0 16543.648305107497 7686848 2381741 0 0    .003462
18 2000      50 3 158 138  24.72678 25.967733  25.42759  26.66139 1 4074.5293987268446 2153168 2381741 0 0    .979113
21 2000      55 3 195 138  24.72678 29.961687  25.42759  30.17365 0  8125.746360914612 9529106 2381741 0 0    .009428
12 2003   2.514 3  51  75  24.94077   25.1412  25.58135  25.72815 1   2670.09458589592 1001449 2381741 0 0    .810648
17 2004     740 3 139  67 25.169733  26.30057 25.623466 26.711403 0  2776.679184100914  323752 2381741 0 0    .001006
20 2004      25 3 194  67 25.169733  28.50589 25.623466 28.476164 0 1897.1870314235687  244110 2381741 0 0    .014529
19 2006   18.26 3 170 152 25.485674  27.86574  25.69757 27.977964 0  806.5022329710483  505954 2381741 0 0    .004845
12 2007  46.853 3  51 124  25.62837  25.59448  25.73074 25.946846 1   2670.09458589592 1001449 2381741 0 0    .810648
13 2008  82.319 3  61 107 25.864933  28.70379  25.75407 28.614775 1 1233.8113884818076  547026 2381741 1 0 .033549998
13 2008  82.319 3  61 107 25.864933  28.70379  25.75407 28.614775 1 1233.8113884818076  547026 2381741 1 0 .033549998
15 2010  20.194 3  94 100 25.805956  23.99759 25.805956  23.99759 1 3029.2130556757925   91862 2381741 0 0    .921715
15 2010  20.194 3  94 100 25.805956  23.99759 25.805956  23.99759 1 3029.2130556757925   91862 2381741 0 0    .921715
14 2013 1752.87 3  83  22 26.069206  27.53948 25.894957 27.522614 0 11682.658921694183 1933658 2381741 0 0    .430229
19 2013    9.77 3 170  22 26.069206  27.93987 25.894957  27.93287 0  806.5022329710483  505954 2381741 0 0    .004845
20 2016      55 3 194   9  25.79248   28.6059  26.00156  28.64539 .                  .       .       . . .          .
22 2001      10 4  12   0         .  26.66054         .   27.4841 .                  .       .       . . .          .
26 2014  25.556 4 168   0 20.281654  27.97556 20.111086  27.84156 .                  .       .       . . .          .
23 2015    2.74 4  27   0 20.306234         .  20.12349         . .                  .       .       . . .          .
24 2015   6.782 4  37   0 20.306234  30.03478  20.12349 29.818005 .                  .       .       . . .          .
25 2015  15.478 4  79   0 20.306234  26.45791  20.12349 26.300743 .                  .       .       . . .          .
29 1999   13.26 5 194   0  20.93828  28.14122 21.669924 28.334686 0 1140.9474403908252  244110     453 0 0       .131
27 2000   6.067 5 170   0 21.084034 27.112503   21.7046  27.77034 1  519.3864007539153  505954     453 0 1       .969
28 2012   11.82 5 180   0   21.8753  27.22762  21.87006  27.11959 0  701.2179800022125   41288     453 0 0       .528
30 2016  32.768 5 195   0  21.77357   30.5555 21.916727  30.45954 .                  .       .       . . .          .
34 2001    19.1 6 194  40  22.91336  28.11438 24.306593 28.395796 0  7092.603116264343  244110 1246700 0 0    .121875
35 2005     175 6 195   0  24.06378 30.203154  24.55681  30.29881 0 12153.605614564514 9529106 1246700 0 0    .292428
31 2006    .752 6  12   0  24.45591   27.3401  24.74524  27.65363 0 12954.905818159867 7686848 1246700 0 0    .249882
35 2006    .675 6 195   0  24.45591  30.25973  24.74524  30.32513 0 12153.605614564514 9529106 1246700 0 0    .292428
33 2012    15.3 6 167   0 25.471657  26.70552  25.22442  26.70519 0 2579.6722784971234 1219912 1246700 0 0  .14866799
32 2014    1520 6  34   0 25.565695         .  25.33726         . 0 10914.782185473632     262 1246700 0 0    .200814
36 2010    18.7 7  79   0         . 26.155405         . 26.155405 1  15510.34696298828    1092     102 0 0          .
37 2016  11.275 7 203   0         .  20.48292         .  20.41951 .                  .       .       . . .          .
44 1991      12 8 195   0 19.992846 29.451374   20.3771 29.834637 1  3965.092480428505 9529106     442 0 0    .214624
44 1998  24.064 8 195   0  20.40562 29.838104  20.62358 30.087757 1  3965.092480428505 9529106     442 0 0    .214624
40 2000     5.5 8  33   0  20.53713  27.33301  20.72476  27.92573 1  4157.128729905128 9976139     442 0 0    .172468
39 2001    12.5 8  22   0 20.501047  22.02631  20.67395 22.391563 1 1720.8136657287598      53     442 0 0    .132912
38 2003  46.981 8  12   0 20.567364  26.86928 20.742954  27.55213 1  16622.68066688919 7686848     442 0 0     .12937
38 2003  46.981 8  12   0 20.567364  26.86928 20.742954  27.55213 1  16622.68066688919 7686848     442 0 0     .12937
44 2004      40 8 195   0 20.639425  30.13858 20.798735  30.26591 1  3965.092480428505 9529106     442 0 0    .214624
38 2005   6.356 8  12   0 20.745214   27.2654  20.86089  27.62428 1  16622.68066688919 7686848     442 0 0     .12937
43 2005 153.337 8 194   0 20.745214  28.55556  20.86089 28.506657 1 6539.8592375068665  244110     442 1 0     .08136
43 2005 153.337 8 194   0 20.745214  28.55556  20.86089 28.506657 1 6539.8592375068665  244110     442 1 0     .08136
43 2005 153.337 8 194   0 20.745214  28.55556  20.86089 28.506657 1 6539.8592375068665  244110     442 1 0     .08136
43 2006  84.681 8 194   0   20.8691  28.62153   20.9807  28.53092 1 6539.8592375068665  244110     442 1 0     .08136
44 2006     5.1 8 195   0   20.8691  30.25973   20.9807  30.32513 1  3965.092480428505 9529106     442 0 0    .214624
44 2007   1.359 8 195   0  20.99436 30.303627 21.069254  30.34276 1  3965.092480428505 9529106     442 0 0    .214624
38 2008       3 8  12   0  21.03693  27.68488  21.06895  27.72675 1  16622.68066688919 7686848     442 0 0     .12937
42 2012       7 8 164   0  20.91505 26.390253  20.87863  26.28725 1  17456.16353701172     646     442 0 0    .016462
41 2015    .911 8  79   0  21.03432  26.45791  20.96715 26.300743 1 15622.458910351563    1092     442 0 0    .039728
54 1990  18.592 9  37  31  25.67452  26.61175  25.99322 27.444164 0 19110.127210772705 9572378 2766889 0 0    .000048
78 1990     571 9 170  31  25.67452  27.00572  25.99322 27.495367 1 10079.656656066894  505954 2766889 1 0    .887631
85 1990      80 9 195  31  25.67452  29.41937  25.99322 29.835377 0  8678.352271958924 9529106 2766889 0 0  .28658798
78 1991    97.9 9 170  27 25.968815 27.078676  26.11251  27.52051 1 10079.656656066894  505954 2766889 1 0    .887631
85 1991      23 9 195  27 25.968815 29.451374  26.11251 29.834637 0  8678.352271958924 9529106 2766889 0 0  .28658798
49 1992  13.029 9  26  41 26.156065 26.716227  26.22531 27.817595 0  2391.846403179836 8511920 2766889 0 0     .80533
51 1992 396.155 9  33  41 26.156065  27.10743  26.22531   27.6323 0  9391.460933694458 9976139 2766889 0 0     .43486
51 1992 396.155 9  33  41 26.156065  27.10743  26.22531   27.6323 0  9391.460933694458 9976139 2766889 0 0     .43486
53 1992 233.078 9  36  41 26.156065  24.55113  26.22531 25.270695 1 1156.7258914702415  756945 2766889 0 0    .752549
53 1992 233.078 9  36  41 26.156065  24.55113  26.22531 25.270695 1 1156.7258914702415  756945 2766889 0 0    .752549
63 1992  15.958 9  86  41 26.156065  24.74836  26.22531  25.19811 0 10913.810616272734   70285 2766889 0 0    .873245
65 1992 281.352 9  89  41 26.156065  27.90547  26.22531 28.213743 0  11214.01020098114  301323 2766889 0 0   .7622219
65 1992 281.352 9  89  41 26.156065  27.90547  26.22531 28.213743 0  11214.01020098114  301323 2766889 0 0   .7622219
65 1992 281.352 9  89  41 26.156065  27.90547  26.22531 28.213743 0  11214.01020098114  301323 2766889 0 0   .7622219
82 1992    .234 9 184  41 26.156065 25.436867  26.22531 25.836197 0 17137.094580753324  513115 2766889 0 0    .003796
84 1992   1.858 9 194  41 26.156065  27.79625  26.22531  28.12005 0 11136.962471050261  244110 2766889 0 0    .124371
85 1992 138.976 9 195  41 26.156065  29.50885  26.22531 29.869574 0  8678.352271958924 9529106 2766889 0 0  .28658798
45 1993  11.696 9  12   1 26.190235  26.46746   26.2827 27.179417 0 12044.573995607949 7686848 2766889 0 0    .277485
49 1993  12.499 9  26   1 26.190235 26.805025   26.2827  27.86319 0  2391.846403179836 8511920 2766889 0 0     .80533
49 1993  12.499 9  26   1 26.190235 26.805025   26.2827  27.86319 0  2391.846403179836 8511920 2766889 0 0     .80533
51 1993  14.281 9  33   1 26.190235 27.081404   26.2827 27.658506 0  9391.460933694458 9976139 2766889 0 0     .43486
52 1993  23.796 9  34   1 26.190235         .   26.2827         . 0  6251.536736663818     262 2766889 0 0    .048764
53 1993  12.241 9  36   1 26.190235 24.621145   26.2827   25.3345 1 1156.7258914702415  756945 2766889 0 0    .752549
55 1993     1.7 9  38   1 26.190235 24.745085   26.2827  25.81582 1  4615.471325676345 1141748 2766889 0 0    .885103
78 1993 238.328 9 170   1 26.190235  26.98409   26.2827  27.51939 1 10079.656656066894  505954 2766889 1 0    .887631
84 1993  48.743 9 194   1 26.190235   27.6906   26.2827  28.14501 0 11136.962471050261  244110 2766889 0 0    .124371
84 1993  48.743 9 194   1 26.190235   27.6906   26.2827  28.14501 0 11136.962471050261  244110 2766889 0 0    .124371
85 1993  43.814 9 195   1 26.190235 29.559454   26.2827  29.89666 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1993  43.814 9 195   1 26.190235 29.559454   26.2827  29.89666 0  8678.352271958924 9529106 2766889 0 0  .28658798
88 1993  11.736 9 201   1 26.190235  24.78585   26.2827 26.337206 1  4886.742732406616  911930 2766889 0 0    .868638
45 1994 149.985 9  12  14  26.27405  26.50159  26.33942 27.219133 0 12044.573995607949 7686848 2766889 0 0    .277485
45 1994 149.985 9  12  14  26.27405  26.50159  26.33942 27.219133 0 12044.573995607949 7686848 2766889 0 0    .277485
51 1994  19.857 9  33  14  26.27405  27.08308  26.33942  27.70246 0  9391.460933694458 9976139 2766889 0 0     .43486
51 1994  19.857 9  33  14  26.27405  27.08308  26.33942  27.70246 0  9391.460933694458 9976139 2766889 0 0     .43486
51 1994  19.857 9  33  14  26.27405  27.08308  26.33942  27.70246 0  9391.460933694458 9976139 2766889 0 0     .43486
53 1994  64.497 9  36  14  26.27405 24.766464  26.33942  25.38358 1 1156.7258914702415  756945 2766889 0 0    .752549
53 1994  64.497 9  36  14  26.27405 24.766464  26.33942  25.38358 1 1156.7258914702415  756945 2766889 0 0    .752549
57 1994 239.996 9  61  14  26.27405  27.96866  26.33942 28.319946 0 10932.340734829711  547026 2766889 0 0    .700532
63 1994  32.986 9  86  14  26.27405 24.769226  26.33942  25.28064 0 10913.810616272734   70285 2766889 0 0    .873245
63 1994  32.986 9  86  14  26.27405 24.769226  26.33942  25.28064 0 10913.810616272734   70285 2766889 0 0    .873245
63 1994  32.986 9  86  14  26.27405 24.769226  26.33942  25.28064 0 10913.810616272734   70285 2766889 0 0    .873245
65 1994  44.996 9  89  14  26.27405 27.722315  26.33942  28.22646 0  11214.01020098114  301323 2766889 0 0   .7622219
68 1994   99.99 9 117  14  26.27405  26.99107  26.33942 27.315214 1   7533.98598147583 1967210 2766889 0 0    .867776
85 1994  109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1994  109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1994  109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1994  109.95 9 195  14  26.27405 29.620094  26.33942 29.936243 0  8678.352271958924 9529106 2766889 0 0  .28658798
49 1995  52.768 9  26  16  26.27635  27.38977 26.310556  27.95838 0  2391.846403179836 8511920 2766889 0 0     .80533
49 1995  52.768 9  26  16  26.27635  27.38977 26.310556  27.95838 0  2391.846403179836 8511920 2766889 0 0     .80533
51 1995  96.111 9  33  16  26.27635  27.12689 26.310556 27.728886 0  9391.460933694458 9976139 2766889 0 0     .43486
51 1995  96.111 9  33  16  26.27635  27.12689 26.310556 27.728886 0  9391.460933694458 9976139 2766889 0 0     .43486
51 1995  96.111 9  33  16  26.27635  27.12689 26.310556 27.728886 0  9391.460933694458 9976139 2766889 0 0     .43486
53 1995     475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
53 1995     475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
53 1995     475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
53 1995     475 9  36  16  26.27635  25.01983 26.310556 25.469145 1 1156.7258914702415  756945 2766889 0 0    .752549
57 1995    20.7 9  61  16  26.27635  28.10719 26.310556 28.340584 0 10932.340734829711  547026 2766889 0 0    .700532
58 1995      50 9  65  16  26.27635 28.583303 26.310556 28.675167 0  11646.03295689621  357325 2766889 0 0   .3331284
68 1995   96.96 9 117  16  26.27635 26.563305 26.310556 27.255903 1   7533.98598147583 1967210 2766889 0 0    .867776
71 1995  74.999 9 143  16  26.27635   22.9823 26.310556   23.2874 1  5126.518599275684   75648 2766889 0 0    .780094
78 1995 156.231 9 170  16  26.27635 27.141533 26.310556  27.57014 1 10079.656656066894  505954 2766889 1 0    .887631
84 1995   5.001 9 194  16  26.27635 27.920116 26.310556  28.20747 0 11136.962471050261  244110 2766889 0 0    .124371
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
85 1995 771.179 9 195  16  26.27635  29.66756 26.310556  29.96307 0  8678.352271958924 9529106 2766889 0 0  .28658798
47 1996   173.7 9  20  19  26.32962 26.362894  26.36435   26.6171 0   11305.2858804924   33114 2766889 0 0     .82453
47 1996   173.7 9  20  19  26.32962 26.362894  26.36435   26.6171 0   11305.2858804924   33114 2766889 0 0     .82453
47 1996   173.7 9  20  19  26.32962 26.362894  26.36435   26.6171 0   11305.2858804924   33114 2766889 0 0     .82453
end
label values acquiror countrynames
label values target countrynames

[Carlo Lazzaro]

Eszti:
I would scrutiny my data carefully if I noticed that the same -panelid- (85) has the repeated values for the dependent variable -MA- during 1993-1995:

. list panel_id year MA if panel_id==85

     +---------------------------+
     | panel_id   year        MA |
     |---------------------------|
 58. |       85   1991        23 |
 71. |       85   1993    43.814 |
 72. |       85   1993    43.814 |
 90. |       85   1990        80 |
100. |       85   1994    109.95 |
     |---------------------------|
101. |       85   1994    109.95 |
102. |       85   1994    109.95 |
103. |       85   1994    109.95 |
105. |       85   1992   138.976 |
134. |       85   1995   771.179 |
     |---------------------------|
135. |       85   1995   771.179 |
136. |       85   1995   771.179 |
137. |       85   1995   771.179 |
138. |       85   1995   771.179 |
139. |       85   1995   771.179 |
     |---------------------------|
140. |       85   1995   771.179 |
141. |       85   1995   771.179 |
142. |       85   1995   771.179 |
143. |       85   1995   771.179 |
144. |       85   1995   771.179 |
     |---------------------------|
145. |       85   1995   771.179 |
146. |       85   1995   771.179 |
147. |       85   1995   771.179 |
148. |       85   1995   771.179 |
     +---------------------------+

.

[Eszti Bambacht]

Yes, MA is the sum of all dealvalues per country per year, as it defined as the M&A deal flow from acquirer country to target country in time t in millions of dollars.
Do you think that that is incorrect?

I think I need to take the deal value as dependent variable...

[Carlo Lazzaro]

Eszti:
as per your data, I've compared -xtreg, fe- vs -xtrteg, re-; -hausman- points you to the -re- specification:

. xtset panel_id*///no time_variable included in -xtset-, since your data show repeated  time values within panel///*
       panel variable:  panel_id (unbalanced)

. xtreg MA terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distance acquiror_area target_area colony comcur comrelig, fe
note: comlang omitted because of collinearity
note: distance omitted because of collinearity
note: acquiror_area omitted because of collinearity
note: target_area omitted because of collinearity
note: colony omitted because of collinearity
note: comcur omitted because of collinearity
note: comrelig omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =        138
Group variable: panel_id                        Number of groups  =         52

R-sq:                                           Obs per group:
     within  = 0.1495                                         min =          1
     between = 0.0070                                         avg =        2.7
     overall = 0.0013                                         max =         24

                                                F(5,81)           =       2.85
corr(u_i, Xb)  = -0.9980                        Prob > F          =     0.0203

----------------------------------------------------------------------------------------
                    MA |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
             terrorism |  -.4579036   1.414701    -0.32   0.747    -3.272716    2.356909
        target_gdp_log |   319.2614   298.5694     1.07   0.288    -274.7981    913.3209
      acquiror_gdp_log |  -13.90121   250.4335    -0.06   0.956    -512.1854     484.383
  target_gdpgrowth_log |   -1549.95   683.8539    -2.27   0.026    -2910.605   -189.2955
acquiror_gdpgrowth_log |   1772.477   755.8768     2.34   0.021     268.5195    3276.435
               comlang |          0  (omitted)
              distance |          0  (omitted)
         acquiror_area |          0  (omitted)
           target_area |          0  (omitted)
                colony |          0  (omitted)
                comcur |          0  (omitted)
              comrelig |          0  (omitted)
                 _cons |  -17870.66   12448.25    -1.44   0.155    -42638.78    6897.463
-----------------------+----------------------------------------------------------------
               sigma_u |  3758.2506
               sigma_e |  190.24873
                   rho |    .997444   (fraction of variance due to u_i)
----------------------------------------------------------------------------------------
F test that all u_i=0: F(51, 81) = 2.84                      Prob > F = 0.0000

. quietly xtreg MA terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distance acquiror_area target_area colony comcur comrelig, fe

. estimates store fe

. quietly xtreg MA terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distan
> ce acquiror_area target_area colony comcur comrelig, re

. estimates store re

. hausman fe re

                 ---- Coefficients ----
             |      (b)          (B)            (b-B)     sqrt(diag(V_b-V_B))
             |       fe           re         Difference          S.E.
-------------+----------------------------------------------------------------
   terrorism |   -.4579036     .0573741       -.5152777        1.025302
target~p_log |    319.2614     126.1217        193.1397         266.256
acquir~p_log |   -13.90121     208.7029       -222.6041        207.3297
target~h_log |    -1549.95    -182.9994       -1366.951        660.8338
acquir~h_log |    1772.477     -199.274        1971.751        739.6979
------------------------------------------------------------------------------
                           b = consistent under Ho and Ha; obtained from xtreg
            B = inconsistent under Ha, efficient under Ho; obtained from xtreg

    Test:  Ho:  difference in coefficients not systematic

                  chi2(5) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                          =       10.06
                Prob>chi2 =      0.0735

.

[Eszti Bambacht]

Thank you, but you point out to me that the dependent variable is wrong. So When I ran the same data with the dealvalue per deal I got the following

. quietly xtreg dealvalue terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distance acquiror_area target_area colony comcur comre
> lig, fe

. estimates store fe

. quietly xtreg dealvalue terrorism target_gdp_log acquiror_gdp_log target_gdpgrowth_log acquiror_gdpgrowth_log comlang distance acquiror_area target_area colony comcur comre
> lig, re

. estimates store re

. hausman fe re


                 ---- Coefficients ----
             |      (b)          (B)            (b-B)     sqrt(diag(V_b-V_B))
             |       fe           re         Difference          S.E.
-------------+----------------------------------------------------------------
   terrorism |   -.2494523     -.117104       -.1323483        .0893803
target~p_log |    19.21576     204.0325       -184.8168        35.81623
acquir~p_log |   -27.75121    -62.54509        34.79388        37.15646
target~h_log |      145.76    -175.9878        321.7478        84.45698
acquir~h_log |    167.1853     97.11443        70.07088        89.63202
      comcur |    112.9841     94.58087        18.40327        51.85264
------------------------------------------------------------------------------
                           b = consistent under Ho and Ha; obtained from xtreg
            B = inconsistent under Ha, efficient under Ho; obtained from xtreg



    Test:  Ho:  difference in coefficients not systematic


                  chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                          =       40.48
                Prob>chi2 =      0.0000

MA is the sum of all the dealvalues per country per year, and i matched them with all the deals in that year per country. The dealvalue is specific for all the deals. So I think I need to use that one as my dependent variable.

* Example generated by -dataex-. To install: ssc install dataex
clear
input float panel_id double dealvalue float(MA year) long(acquiror target busterr) double buscas long nonbusterr double nonbuscas float(target_gdp_log acquiror_gdp_log) byte comlang double distance byte(colony comcur) float comrelig
 8       1       1 1995 132 2  0  0   0    0  21.60889  26.82477 0 1652.2680196256638 0 0     .00205
 6     4.7     4.7 1999  68 2  0  0   3   11 21.951374 25.682894 0  451.4164096862793 0 0    .003075
10      10      16 2000 188 2  0  0   2    0  22.01306  26.33266 0 1048.1704196635724 1 0     .20336
10       6      16 2000 188 2  0  0   2    0  22.01306  26.33266 0 1048.1704196635724 1 0     .20336
 6   2.287   2.287 2003  68 2  0  0   1    0 22.471935  26.03116 0  451.4164096862793 0 0    .003075
 1     126     126 2004  13 2  0  0   0    0 22.713175  26.43006 0  848.8387590137959 0 0     .00123
 7   6.712   6.712 2005  89 2  0  0   0    0  22.82233 28.247644 0  722.9528244365692 0 0    .000205
 7    40.8    40.8 2006  89 2  0  0   0    0  22.91967 28.295065 0  722.9528244365692 0 0    .000205
 4   2.863   2.863 2007  43 2  0  0   0    0 23.093605 23.904543 0  1363.566163206029 0 0    .037925
 7   156.9   156.9 2007  89 2  0  0   0    0 23.093605 28.420866 0  722.9528244365692 0 0    .000205
10 161.117 161.117 2007 188 2  0  0   0    0 23.093605  27.23912 0 1048.1704196635724 1 0     .20336
 6   3.009   3.009 2008  68 2  0  0   0    0 23.279047 26.593864 0  451.4164096862793 0 0    .003075
 5 144.047 144.047 2009  44 2  0  0   1    0  23.21185 26.052015 0 1037.8473058279037 0 0          0
 6  62.137  62.137 2009  68 2  0  0   1    0  23.21185  26.52236 0  451.4164096862793 0 0    .003075
 9    7.95    7.95 2009 158 2  0  0   1    0  23.21185  26.78495 0 2940.6366864788056 0 0     .20254
 3  33.996  33.996 2011  33 2  0  0   0    0 23.279785  28.21248 0  7842.518149364852 0 0     .00123
 3      .5      .5 2012  33 2  0  0   0    0  23.23447  28.23221 0  7842.518149364852 0 0     .00123
 3   4.144   4.144 2014  33 2  0  0   2    3  23.30562   28.2184 0  7842.518149364852 0 0     .00123
 2  44.699  44.699 2016  27 2  0  0   2    0 23.196764         . .                  . . .          .
13    .692    .692 1991  61 3  1  0  29  115   24.5457  27.87441 1 1233.8113884818076 1 0 .033549998
16    42.3    42.3 1999 132 3  3 46 103  690 24.607723  26.81452 0  1814.178711369133 0 0     .01204
11    22.5    22.5 2000  12 3  7 76 131  691  24.72678  26.75262 0 16543.648305107497 0 0    .003462
18      50      50 2000 158 3  7 76 131  691  24.72678 25.967733 1 4074.5293987268446 0 0    .979113
21      55      55 2000 195 3  7 76 131  691  24.72678 29.961687 0  8125.746360914612 0 0    .009428
12   2.514   2.514 2003  51 3  3  2  72  348  24.94077   25.1412 1   2670.09458589592 0 0    .810648
17     740     740 2004 139 3  2  4  65  343 25.169733  26.30057 0  2776.679184100914 0 0    .001006
20      25      25 2004 194 3  2  4  65  343 25.169733  28.50589 0 1897.1870314235687 0 0    .014529
19   18.26   18.26 2006 170 3  4  6 148  445 25.485674  27.86574 0  806.5022329710483 0 0    .004845
12  46.853  46.853 2007  51 3  7 13 117  879  25.62837  25.59448 1   2670.09458589592 0 0    .810648
13   14.31  82.319 2008  61 3  5 32 102  545 25.864933  28.70379 1 1233.8113884818076 1 0 .033549998
13  68.009  82.319 2008  61 3  5 32 102  545 25.864933  28.70379 1 1233.8113884818076 1 0 .033549998
15   1.694  20.194 2010  94 3  3  9  97  307 25.805956  23.99759 1 3029.2130556757925 0 0    .921715
15    18.5  20.194 2010  94 3  3  9  97  307 25.805956  23.99759 1 3029.2130556757925 0 0    .921715
14 1752.87 1752.87 2013  83 3  2 80  20   69 26.069206  27.53948 0 11682.658921694183 0 0    .430229
19    9.77    9.77 2013 170 3  2 80  20   69 26.069206  27.93987 0  806.5022329710483 0 0    .004845
20      55      55 2016 194 3  0  0   9   11  25.79248   28.6059 .                  . . .          .
22      10      10 2001  12 4  0  0   0    0         .  26.66054 .                  . . .          .
26  25.556  25.556 2014 168 4  0  0   0    0 20.281654  27.97556 .                  . . .          .
23    2.74    2.74 2015  27 4  0  0   0    0 20.306234         . .                  . . .          .
24   6.782   6.782 2015  37 4  0  0   0    0 20.306234  30.03478 .                  . . .          .
25  15.478  15.478 2015  79 4  0  0   0    0 20.306234  26.45791 .                  . . .          .
29   13.26   13.26 1999 194 5  0  0   0    0  20.93828  28.14122 0 1140.9474403908252 0 0       .131
27   6.067   6.067 2000 170 5  0  0   0    0 21.084034 27.112503 1  519.3864007539153 0 1       .969
28   11.82   11.82 2012 180 5  0  0   0    0   21.8753  27.22762 0  701.2179800022125 0 0       .528
30  32.768  32.768 2016 195 5  0  0   0    0  21.77357   30.5555 .                  . . .          .
34    19.1    19.1 2001 194 6  3 22  37 1162  22.91336  28.11438 0  7092.603116264343 0 0    .121875
35     175     175 2005 195 6  0  0   0    0  24.06378 30.203154 0 12153.605614564514 0 0    .292428
31    .752    .752 2006  12 6  0  0   0    0  24.45591   27.3401 0 12954.905818159867 0 0    .249882
35    .675    .675 2006 195 6  0  0   0    0  24.45591  30.25973 0 12153.605614564514 0 0    .292428
33    15.3    15.3 2012 167 6  0  0   0    0 25.471657  26.70552 0 2579.6722784971234 0 0  .14866799
32    1520    1520 2014  34 6  0  0   0    0 25.565695         . 0 10914.782185473632 0 0    .200814
36    18.7    18.7 2010  79 7  0  0   0    0         . 26.155405 1  15510.34696298828 0 0          .
37  11.275  11.275 2016 203 7  0  0   0    0         .  20.48292 .                  . . .          .
44      12      12 1991 195 8  0  0   0    0 19.992846 29.451374 1  3965.092480428505 0 0    .214624
44  24.064  24.064 1998 195 8  0  0   0    0  20.40562 29.838104 1  3965.092480428505 0 0    .214624
40     5.5     5.5 2000  33 8  0  0   0    0  20.53713  27.33301 1  4157.128729905128 0 0    .172468
39    12.5    12.5 2001  22 8  0  0   0    0 20.501047  22.02631 1 1720.8136657287598 0 0    .132912
38  14.981  46.981 2003  12 8  0  0   0    0 20.567364  26.86928 1  16622.68066688919 0 0     .12937
38      32  46.981 2003  12 8  0  0   0    0 20.567364  26.86928 1  16622.68066688919 0 0     .12937
44      40      40 2004 195 8  0  0   0    0 20.639425  30.13858 1  3965.092480428505 0 0    .214624
38   6.356   6.356 2005  12 8  0  0   0    0 20.745214   27.2654 1  16622.68066688919 0 0     .12937
43      96 153.337 2005 194 8  0  0   0    0 20.745214  28.55556 1 6539.8592375068665 1 0     .08136
43  16.457 153.337 2005 194 8  0  0   0    0 20.745214  28.55556 1 6539.8592375068665 1 0     .08136
43   40.88 153.337 2005 194 8  0  0   0    0 20.745214  28.55556 1 6539.8592375068665 1 0     .08136
43  84.681  84.681 2006 194 8  0  0   0    0   20.8691  28.62153 1 6539.8592375068665 1 0     .08136
44     5.1     5.1 2006 195 8  0  0   0    0   20.8691  30.25973 1  3965.092480428505 0 0    .214624
44   1.359   1.359 2007 195 8  0  0   0    0  20.99436 30.303627 1  3965.092480428505 0 0    .214624
38       3       3 2008  12 8  0  0   0    0  21.03693  27.68488 1  16622.68066688919 0 0     .12937
42       7       7 2012 164 8  0  0   0    0  20.91505 26.390253 1  17456.16353701172 0 0    .016462
41    .911    .911 2015  79 8  0  0   0    0  21.03432  26.45791 1 15622.458910351563 0 0    .039728
54  18.592  18.592 1990  37 9 20  1  11    1  25.67452  26.61175 0 19110.127210772705 0 0    .000048
78     571     571 1990 170 9 20  1  11    1  25.67452  27.00572 1 10079.656656066894 1 0    .887631
85      80      80 1990 195 9 20  1  11    1  25.67452  29.41937 0  8678.352271958924 0 0  .28658798
78    97.9    97.9 1991 170 9  3  0  24    8 25.968815 27.078676 1 10079.656656066894 1 0    .887631
85      23      23 1991 195 9  3  0  24    8 25.968815 29.451374 0  8678.352271958924 0 0  .28658798
49  13.029  13.029 1992  26 9 14  2  27  254 26.156065 26.716227 0  2391.846403179836 0 0     .80533
51 252.985 396.155 1992  33 9 14  2  27  254 26.156065  27.10743 0  9391.460933694458 0 0     .43486
51  143.17 396.155 1992  33 9 14  2  27  254 26.156065  27.10743 0  9391.460933694458 0 0     .43486
53 143.077 233.078 1992  36 9 14  2  27  254 26.156065  24.55113 1 1156.7258914702415 0 0    .752549
53  90.001 233.078 1992  36 9 14  2  27  254 26.156065  24.55113 1 1156.7258914702415 0 0    .752549
63  15.958  15.958 1992  86 9 14  2  27  254 26.156065  24.74836 0 10913.810616272734 0 0    .873245
65 258.267 281.352 1992  89 9 14  2  27  254 26.156065  27.90547 0  11214.01020098114 0 0   .7622219
65    2.06 281.352 1992  89 9 14  2  27  254 26.156065  27.90547 0  11214.01020098114 0 0   .7622219
65  21.025 281.352 1992  89 9 14  2  27  254 26.156065  27.90547 0  11214.01020098114 0 0   .7622219
82    .234    .234 1992 184 9 14  2  27  254 26.156065 25.436867 0 17137.094580753324 0 0    .003796
84   1.858   1.858 1992 194 9 14  2  27  254 26.156065  27.79625 0 11136.962471050261 0 0    .124371
85 138.976 138.976 1992 195 9 14  2  27  254 26.156065  29.50885 0  8678.352271958924 0 0  .28658798
45  11.696  11.696 1993  12 9  1  0   0    0 26.190235  26.46746 0 12044.573995607949 0 0    .277485
49   7.999  12.499 1993  26 9  1  0   0    0 26.190235 26.805025 0  2391.846403179836 0 0     .80533
49     4.5  12.499 1993  26 9  1  0   0    0 26.190235 26.805025 0  2391.846403179836 0 0     .80533
51  14.281  14.281 1993  33 9  1  0   0    0 26.190235 27.081404 0  9391.460933694458 0 0     .43486
52  23.796  23.796 1993  34 9  1  0   0    0 26.190235         . 0  6251.536736663818 0 0    .048764
53  12.241  12.241 1993  36 9  1  0   0    0 26.190235 24.621145 1 1156.7258914702415 0 0    .752549
55     1.7     1.7 1993  38 9  1  0   0    0 26.190235 24.745085 1  4615.471325676345 0 0    .885103
78 238.328 238.328 1993 170 9  1  0   0    0 26.190235  26.98409 1 10079.656656066894 1 0    .887631
84  24.745  48.743 1993 194 9  1  0   0    0 26.190235   27.6906 0 11136.962471050261 0 0    .124371
84  23.998  48.743 1993 194 9  1  0   0    0 26.190235   27.6906 0 11136.962471050261 0 0    .124371
85    8.11  43.814 1993 195 9  1  0   0    0 26.190235 29.559454 0  8678.352271958924 0 0  .28658798
85  35.704  43.814 1993 195 9  1  0   0    0 26.190235 29.559454 0  8678.352271958924 0 0  .28658798
88  11.736  11.736 1993 201 9  1  0   0    0 26.190235  24.78585 1  4886.742732406616 0 0    .868638
end
label values acquiror countrynames
label values target countrynames

[Carlo Lazzaro]

Eszti:
I actually warned you about the repeated values in your dependent variable, that looked weird to me; however, as MA in not my research field, I cannot say whether MA values are right or wrong.
That said, the -hausman- test that you performed on the revised version of your code points you out to the -fe- specification.

[Eszti Bambacht]

Yes, because you point out the repeated values I checked and came to the conclusion I should use dealvaue as my dependent variable.
Is there another solution for the omitted variables, when I do the fixed effect regression?