Esttab output not showing correct variable names after using the "i."-command

[Josef Bialas]

Hello everyone,
I am doing an analysis and am struggling with the esttab feature, more specifically with the names for the variables:

I'm doing a regression that takes five continents into account, which I modelled by using the "i."-command. Now the problem is that the esttab command doesn't properly display the continent names anymore and I cannot find a way to change the variable names. When using the "label" command, it doesn't work and only puts out:

1bn.Countries' continent .
.

2.Countries' continent 1.210**
(3.04)

3.Countries' continent 0.365
(1.13)

4.Countries' continent 1.036*
(2.45)

5.Countries' continent


Which does not look nice, as the names should obviously be Africa, Europe, Americas, Asia, Oceania

I tried everything I could and also googled around but couldn't find a solution so I'm glad if anyone can point me in the right direction.


Thanks in advance and all best,

Josef

[Øyvind Snilsberg]

. clear all

. sysuse auto
(1978 automobile data)

. describe foreign

Variable      Storage   Display    Value
    name         type    format    label      Variable label
-------------------------------------------------------------------------------------------------------------------------------------------------------------
foreign         byte    %8.0g      origin     Car origin

. label list origin
origin:
           0 Domestic
           1 Foreign

. eststo: reg price i.foreign

      Source |       SS           df       MS      Number of obs   =        74
-------------+----------------------------------   F(1, 72)        =      0.17
       Model |  1507382.66         1  1507382.66   Prob > F        =    0.6802
    Residual |   633558013        72  8799416.85   R-squared       =    0.0024
-------------+----------------------------------   Adj R-squared   =   -0.0115
       Total |   635065396        73  8699525.97   Root MSE        =    2966.4

------------------------------------------------------------------------------
       price | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     foreign |
    Foreign  |   312.2587   754.4488     0.41   0.680    -1191.708    1816.225
       _cons |   6072.423    411.363    14.76   0.000     5252.386     6892.46
------------------------------------------------------------------------------
(est1 stored)

. esttab .,

----------------------------
                      (1)   
                    price   
----------------------------
0.foreign               0   
                      (.)   

1.foreign           312.3   
                   (0.41)   

_cons              6072.4***
                  (14.76)   
----------------------------
N                      74   
----------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

. esttab ., label

------------------------------------
                              (1)   
                            Price   
------------------------------------
Domestic                        0   
                              (.)   

Foreign                     312.3   
                           (0.41)   

Constant                   6072.4***
                          (14.76)   
------------------------------------
Observations                   74   
------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

. 
end of do-file

[Josef Bialas]

…

Thank you so much for your fast reply. For some reason, this approach does not give me the correct labels, here's my code and the output:

. label list
continnt_en:
           1 Africa
           2 Americas
           3 Asia
           4 Europe
           5 Oceania

reg log_gdp_n i.continent_en traditional_n kinship_n popdense_n latitude_n oil_rent_n, robust
eststo m4


esttab m1 m2 m3 m4, label varwidth(25) ///
        nonumbers mtitles("Model 1" "Model 2" "Model 3" "Model 4")

Output:
------------------------------------------------------------------------------------
                          Model 1         Model 2         Model 3         Model 4  
------------------------------------------------------------------------------------
traditional_n               0.973***                        0.803***        0.637***
                           (8.10)                          (6.64)          (4.20)  

Kinship index.. 2019                       -0.700***       -0.336**        -0.101  
                                          (-5.83)         (-3.16)         (-0.65)  

1bn.Continent                                                                   .  
                                                                                .  

2.Continent                                                                 1.210**
                                                                           (3.04)  

3.Continent                                                                 0.365  
                                                                           (1.13)  

4.Continent                                                                 1.036*  
                                                                           (2.45)  

5.Continent                                                                 2.316***
                                                                           (6.03)  

Population density~i                                                    0.0000748*  
                                                                           (2.62)  

Latitude of the co~y                                                      0.00683  
                                                                           (1.39)  

Oil Rent (% of ~2020                                                       0.0503  
                                                                           (1.82)  

Constant                    9.320***        8.872***        9.180***        8.180***
                         (110.83)         (75.77)        (100.48)         (33.19)  
------------------------------------------------------------------------------------
Observations                  106             104             104             102  
------------------------------------------------------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

Do you have any suggestion why I can't get this to work?

[Øyvind Snilsberg]

what happens if you run,

clear all
sysuse auto
reg price i.foreign
esttab ., label

can you give a reproducible data example?

[Clyde Schechter]

Without a -dataex- example, I can't be sure. But my best guess is that in O.P.'s data set, although the value label continent_en is defined, it has not actually been applied to the variable continent_en. If this is correct, running -label values continent_en continent_en- and then redoing the regression and -esttab- will solve the problem.

[Josef Bialas]

Thanks to both of you for your help. For some frustrating reason, Stata still doesn't cooperate even though I did as you advised me to. So, here's a data example:

* Example generated by -dataex-. For more info, type help dataex
clear
input float log_gdp_n long continent_en str9 continent
 8.581699 4 "Europe"  
 8.104056 1 "Africa"  
  10.5299 4 "Europe"  
 9.057969 2 "Americas"
  8.35867 3 "Asia"    
10.852852 5 "Oceania" 
10.791166 4 "Europe"  
 8.350173 3 "Asia"    
 7.728128 3 "Asia"    
 8.788201 4 "Europe"  
 10.71864 4 "Europe"  
 8.051657 2 "Americas"
 8.713313 4 "Europe"  
  8.82701 2 "Americas"
 9.218328 4 "Europe"  
 6.755691 1 "Africa"  
10.674967 2 "Americas"
 9.489605 2 "Americas"
  9.25049 3 "Asia"    
  8.57795 2 "Americas"
 9.556302 4 "Europe"  
10.228559 4 "Europe"  
10.040398 4 "Europe"  
11.019683 4 "Europe"  
 8.635647 2 "Americas"
 8.180379 1 "Africa"  
10.045653 4 "Europe"  
 6.843164 1 "Africa"  
10.802873 4 "Europe"  
10.572294 4 "Europe"  
 8.356259 3 "Asia"    
10.741897 4 "Europe"  
 7.720973 1 "Africa"  
 10.62374 4 "Europe"  
 9.778391 4 "Europe"  
 8.434754 2 "Americas"
 7.149421 2 "Americas"
 10.73861 3 "Asia"    
 9.685143 4 "Europe"  
10.989775 4 "Europe"  
 7.567398 3 "Asia"    
 8.261413 3 "Asia"    
  7.92217 3 "Asia"    
8.4304905 3 "Asia"    
10.695995 3 "Asia"    
10.368352 4 "Europe"  
10.594612 3 "Asia"    
 8.362588 3 "Asia"    
 9.118514 3 "Asia"    
 7.535363 1 "Africa"  
  7.07625 3 "Asia"    
   9.7816 4 "Europe"  
 8.243491 3 "Asia"    
 8.937918 1 "Africa"  
 9.915085 4 "Europe"  
10.581626 3 "Asia"    
 9.250844 3 "Asia"    
 8.842909 3 "Asia"    
  6.76094 1 "Africa"  
 9.039868 2 "Americas"
 8.417762 4 "Europe"  
 8.309419 3 "Asia"    
 8.948408 4 "Europe"  
  8.02607 1 "Africa"  
 7.280465 3 "Asia"    
 8.673763 4 "Europe"  
10.866605 4 "Europe"  
10.635796 5 "Oceania" 
 7.550159 2 "Americas"
 7.648784 1 "Africa"  
11.117372 4 "Europe"  
 7.215618 3 "Asia"    
 8.719071 2 "Americas"
  8.10235 3 "Asia"    
  9.66418 4 "Europe"  
10.007648 4 "Europe"  
10.355546 2 "Americas"
10.822283 3 "Asia"    
 9.469435 4 "Europe"  
 9.226507 4 "Europe"  
 6.668612 1 "Africa"  
 9.913669 1 "Africa"  
 8.953083 4 "Europe"  
  11.0142 3 "Asia"    
 9.866176 4 "Europe"  
 10.14606 4 "Europe"  
 8.640626 1 "Africa"  
10.360865 3 "Asia"    
10.205717 4 "Europe"  
10.864775 4 "Europe"  
11.374828 4 "Europe"  
 6.749733 3 "Asia"    
 6.982371 1 "Africa"  
 8.876233 3 "Asia"    
 9.634754 2 "Americas"
 8.188194 1 "Africa"  
 9.052216 3 "Asia"    
  6.71299 1 "Africa"  
 8.230242 4 "Europe"  
 9.643409 2 "Americas"
end
label values continent_en continent_en
label def continent_en 1 "Africa", modify
label def continent_en 2 "Americas", modify
label def continent_en 3 "Asia", modify
label def continent_en 4 "Europe", modify
label def continent_en 5 "Oceania", modify

//Regression table: 
reg log_gdp_n i.continent_en 
eststo m1 
esttab m1, label

Clyde, I see that you already suggested the -label values continent_en continent_en- command which the dataex-command also put out, but it still does not work. Can anyone figure out what's wrong?

[Clyde Schechter]

I am unable to reproduce the error you are getting:

. * Example generated by -dataex-. For more info, type help dataex
. clear

. input float log_gdp_n long continent_en str9 continent

     log_gdp_n  continent_en  continent
  1.  8.581699 4 "Europe"  
  2.  8.104056 1 "Africa"  
  3.   10.5299 4 "Europe"  
  4.  9.057969 2 "Americas"
  5.   8.35867 3 "Asia"    
  6. 10.852852 5 "Oceania"
  7. 10.791166 4 "Europe"  
  8.  8.350173 3 "Asia"    
  9.  7.728128 3 "Asia"    
 10.  8.788201 4 "Europe"  
 11.  10.71864 4 "Europe"  
 12.  8.051657 2 "Americas"
 13.  8.713313 4 "Europe"  
 14.   8.82701 2 "Americas"
 15.  9.218328 4 "Europe"  
 16.  6.755691 1 "Africa"  
 17. 10.674967 2 "Americas"
 18.  9.489605 2 "Americas"
 19.   9.25049 3 "Asia"    
 20.   8.57795 2 "Americas"
 21.  9.556302 4 "Europe"  
 22. 10.228559 4 "Europe"  
 23. 10.040398 4 "Europe"  
 24. 11.019683 4 "Europe"  
 25.  8.635647 2 "Americas"
 26.  8.180379 1 "Africa"  
 27. 10.045653 4 "Europe"  
 28.  6.843164 1 "Africa"  
 29. 10.802873 4 "Europe"  
 30. 10.572294 4 "Europe"  
 31.  8.356259 3 "Asia"    
 32. 10.741897 4 "Europe"  
 33.  7.720973 1 "Africa"  
 34.  10.62374 4 "Europe"  
 35.  9.778391 4 "Europe"  
 36.  8.434754 2 "Americas"
 37.  7.149421 2 "Americas"
 38.  10.73861 3 "Asia"    
 39.  9.685143 4 "Europe"  
 40. 10.989775 4 "Europe"  
 41.  7.567398 3 "Asia"    
 42.  8.261413 3 "Asia"    
 43.   7.92217 3 "Asia"    
 44. 8.4304905 3 "Asia"    
 45. 10.695995 3 "Asia"    
 46. 10.368352 4 "Europe"  
 47. 10.594612 3 "Asia"    
 48.  8.362588 3 "Asia"    
 49.  9.118514 3 "Asia"    
 50.  7.535363 1 "Africa"  
 51.   7.07625 3 "Asia"    
 52.    9.7816 4 "Europe"  
 53.  8.243491 3 "Asia"    
 54.  8.937918 1 "Africa"  
 55.  9.915085 4 "Europe"  
 56. 10.581626 3 "Asia"    
 57.  9.250844 3 "Asia"    
 58.  8.842909 3 "Asia"    
 59.   6.76094 1 "Africa"  
 60.  9.039868 2 "Americas"
 61.  8.417762 4 "Europe"  
 62.  8.309419 3 "Asia"    
 63.  8.948408 4 "Europe"  
 64.   8.02607 1 "Africa"  
 65.  7.280465 3 "Asia"    
 66.  8.673763 4 "Europe"  
 67. 10.866605 4 "Europe"  
 68. 10.635796 5 "Oceania"
 69.  7.550159 2 "Americas"
 70.  7.648784 1 "Africa"  
 71. 11.117372 4 "Europe"  
 72.  7.215618 3 "Asia"    
 73.  8.719071 2 "Americas"
 74.   8.10235 3 "Asia"    
 75.   9.66418 4 "Europe"  
 76. 10.007648 4 "Europe"  
 77. 10.355546 2 "Americas"
 78. 10.822283 3 "Asia"    
 79.  9.469435 4 "Europe"  
 80.  9.226507 4 "Europe"  
 81.  6.668612 1 "Africa"  
 82.  9.913669 1 "Africa"  
 83.  8.953083 4 "Europe"  
 84.   11.0142 3 "Asia"    
 85.  9.866176 4 "Europe"  
 86.  10.14606 4 "Europe"  
 87.  8.640626 1 "Africa"  
 88. 10.360865 3 "Asia"    
 89. 10.205717 4 "Europe"  
 90. 10.864775 4 "Europe"  
 91. 11.374828 4 "Europe"  
 92.  6.749733 3 "Asia"    
 93.  6.982371 1 "Africa"  
 94.  8.876233 3 "Asia"    
 95.  9.634754 2 "Americas"
 96.  8.188194 1 "Africa"  
 97.  9.052216 3 "Asia"    
 98.   6.71299 1 "Africa"  
 99.  8.230242 4 "Europe"  
100.  9.643409 2 "Americas"
101. end

. label values continent_en continent_en

. label def continent_en 1 "Africa", modify

. label def continent_en 2 "Americas", modify

. label def continent_en 3 "Asia", modify

. label def continent_en 4 "Europe", modify

. label def continent_en 5 "Oceania", modify

.
. //Regression table:
. reg log_gdp_n i.continent_en

      Source |       SS           df       MS      Number of obs   =       100
-------------+----------------------------------   F(4, 95)        =     16.03
       Model |  64.9435127         4  16.2358782   Prob > F        =    0.0000
    Residual |  96.2130357        95   1.0127688   R-squared       =    0.4030
-------------+----------------------------------   Adj R-squared   =    0.3778
       Total |  161.156548        99  1.62784392   Root MSE        =    1.0064

------------------------------------------------------------------------------
   log_gdp_n | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
continent_en |
   Americas  |   1.196548   .3616849     3.31   0.001      .478513    1.914584
       Asia  |   1.084591   .3134025     3.46   0.001      .462408    1.706773
     Europe  |   2.208593   .2999164     7.36   0.000     1.613183    2.804002
    Oceania  |   3.018086   .7547731     4.00   0.000     1.519672      4.5165
             |
       _cons |   7.726237    .251591    30.71   0.000     7.226766    8.225709
------------------------------------------------------------------------------

. eststo m1

. esttab m1, label

------------------------------------
                              (1)   
                        log_gdp_n   
------------------------------------
Africa                          0   
                              (.)   

Americas                    1.197**
                           (3.31)   

Asia                        1.085***
                           (3.46)   

Europe                      2.209***
                           (7.36)   

Oceania                     3.018***
                           (4.00)   

Constant                    7.726***
                          (30.71)   
------------------------------------
Observations                  100   
------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

In a situation like this, it is hard to advise. Some generic things one does is make sure your Stata is competely up to date and that you have the latest version of -esttab-. So -update all- and -adoupdate, update-. Then try again. If that does not work, try re-booting your computer. If none of that works, then I think you will need to bump this up to Stata technical support.

[Josef Bialas]

Clyde, thank you so much. The last update line (adoupdate, update) FINALLY fixed it. Thanks again, this took me forever for such a silly reason and I'm glad this is finally fixed. Have a good one!