Saving the gini coefficient [r(gini_k)]

[Felipe Weizenmann]

Hello friends,
I managed to generate the Gini coefficient I was looking for, however, I need to save them in a variable, the commands I gave were:

egen gini_grupo = group(sector municipio)
ineqdeco income, by(gini_grupo)
g gini = r(Gini_k)

But it just generates missings for me, any suggestions?
Thank you very much

[William Lisowski]

Perhaps the following example will show you where you have gone wrong, and start you in a useful direction.

sysuse auto, clear
label values foreign .
tab foreign
ineqdeco price, by(foreign)
return list
generate gini = .
foreach k in `r(levels)' {
    replace gini = r(gini_`k') if foreign==`k'
}
tab gini foreign, missing

. sysuse auto, clear
(1978 automobile data)

. label values foreign .

. tab foreign

 Car origin |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         52       70.27       70.27
          1 |         22       29.73      100.00
------------+-----------------------------------
      Total |         74      100.00

. ineqdeco price, by(foreign)
 
Percentile ratios

----------------------------------------------------------
  All obs |    p90/p10     p90/p50     p10/p50     p75/p25
----------+-----------------------------------------------
          |      2.923       2.274       0.778       1.512
----------------------------------------------------------
  
Generalized Entropy indices GE(a), where a = income difference
 sensitivity parameter, and Gini coefficient

----------------------------------------------------------------------
  All obs |     GE(-1)       GE(0)       GE(1)       GE(2)        Gini
----------+-----------------------------------------------------------
          |    0.08199     0.08605     0.09557     0.11289     0.23222
----------------------------------------------------------------------
   
Atkinson indices, A(e), where e > 0 is the inequality aversion parameter

----------------------------------------------
  All obs |     A(0.5)        A(1)        A(2)
----------+-----------------------------------
          |    0.04450     0.08245     0.14088
----------------------------------------------
  
Subgroup summary statistics, for each subgroup k = 1,...,K:
  

-------------------------------------------------------------------------------------
Car       |
origin    |   Popn. share           Mean  Relative mean   Income share      log(mean)
----------+--------------------------------------------------------------------------
        0 |       0.70270     6072.42308        0.98494        0.69212        8.71151
        1 |       0.29730     6384.68182        1.03559        0.30788        8.76166
-------------------------------------------------------------------------------------
  
Subgroup indices: GE_k(a) and Gini_k 

----------------------------------------------------------------------
Car       |
origin    |     GE(-1)       GE(0)       GE(1)       GE(2)        Gini
----------+-----------------------------------------------------------
        0 |    0.08706     0.09293     0.10534     0.12756     0.23777
        1 |    0.06834     0.06892     0.07273     0.08049     0.21108
----------------------------------------------------------------------
  
Within-group inequality, GE_W(a)

----------------------------------------------------------
  All obs |     GE(-1)       GE(0)       GE(1)       GE(2)
----------+-----------------------------------------------
          |    0.08173     0.08579     0.09530     0.11262
----------------------------------------------------------
              
Between-group inequality, GE_B(a):

----------------------------------------------------------
  All obs |     GE(-1)       GE(0)       GE(1)       GE(2)
----------+-----------------------------------------------
          |    0.00026     0.00026     0.00027     0.00027
----------------------------------------------------------
              
Subgroup Atkinson indices, A_k(e)

----------------------------------------------
Car       |
origin    |     A(0.5)        A(1)        A(2)
----------+-----------------------------------
        0 |    0.04848     0.08874     0.14829
        1 |    0.03488     0.06660     0.12025
----------------------------------------------
  
Within-group inequality, A_W(e)

----------------------------------------------
  All obs |     A(0.5)        A(1)        A(2)
----------+-----------------------------------
          |    0.04429     0.08192     0.13966
----------------------------------------------
 
Between-group inequality, A_B(e)

----------------------------------------------
  All obs |     A(0.5)        A(1)        A(2)
----------+-----------------------------------
          |    0.00022     0.00058     0.00142
----------------------------------------------

. return list

scalars:
               r(ede2) =  5296.67182806118
               r(ede1) =  5656.906729539464
            r(edehalf) =  5890.891413030665
         r(between_a2) =  .0014220371069532
         r(between_a1) =  .000579863745803
      r(between_ahalf) =  .0002189045211916
          r(within_a2) =  .1396603860401734
          r(within_a1) =  .0819216302593577
       r(within_ahalf) =  .0442926433378639
               r(a2_1) =  .120251251326965
               r(a1_1) =  .0665967017412186
            r(ahalf_1) =  .0348828885410059
               r(a2_0) =  .148294201236304
               r(a1_0) =  .0887386575341225
            r(ahalf_0) =  .0484784087085215
        r(between_ge2) =  .0002679535178404
        r(between_ge1) =  .0002661615119775
        r(between_ge0) =  .0002644106835199
       r(between_gem1) =  .0002627002691232
         r(within_ge2) =  .1126217670888891
         r(within_ge1) =  .0953009106877201
         r(within_ge0) =  .0857881439463363
        r(within_gem1) =  .0817307625025281
             r(sumw_1) =  22
                r(v_1) =  .2972972972972973
           r(lambda_1) =  1.035590579611236
            r(theta_1) =  .3078782804249621
           r(lgmean_1) =  8.761656934520458
             r(mean_1) =  6384.681818181818
             r(gini_1) =  .2110814688824557
              r(ge2_1) =  .0804869266037308
              r(ge1_1) =  .072725769905224
              r(ge0_1) =  .0689179088113295
             r(gem1_1) =  .0683440877343363
             r(sumw_0) =  52
                r(v_0) =  .7027027027027027
           r(lambda_0) =  .9849424470875541
            r(theta_0) =  .692121719575038
           r(lgmean_0) =  8.711512993348268
             r(mean_0) =  6072.423076923077
             r(gini_0) =  .2377725910959381
              r(ge2_0) =  .1275629191851993
              r(ge1_0) =  .1053430684872671
              r(ge0_0) =  .0929255511188392
             r(gem1_0) =  .0870571748199685
                 r(a2) =  .140883820895806
                 r(a1) =  .082453991337858
              r(ahalf) =  .0445018519991732
                r(ge2) =  .1128897206067294
                r(ge1) =  .0955670721996976
                r(ge0) =  .0860525546298563
               r(gem1) =  .0819934627716512
               r(gini) =  .2322248019945887
             r(p75p50) =  1.266753220812943
             r(p25p50) =  .8379107160691102
             r(p10p50) =  .777988614800759
             r(p90p50) =  2.274043743133926
             r(p75p25) =  1.511799761620977
             r(p90p10) =  2.922978177150192
                r(p95) =  13466
                r(p90) =  11385
                r(p75) =  6342
                r(p50) =  5006.5
                r(p25) =  4195
                r(p10) =  3895
                 r(p5) =  3748
                r(max) =  15906
                r(min) =  3291
                  r(N) =  74
               r(sumw) =  74
                 r(sd) =  2949.495884768919
                r(Var) =  8699525.97426879
               r(mean) =  6165.256756756757

macros:
             r(levels) : "0 1"

. generate gini = .
(74 missing values generated)

. foreach k in `r(levels)' {
  2.     replace gini = r(gini_`k') if foreign==`k'
  3. }
(52 real changes made)
(22 real changes made)

. tab gini foreign, missing

           |      Car origin
      gini |         0          1 |     Total
-----------+----------------------+----------
  .2110815 |         0         22 |        22 
  .2377726 |        52          0 |        52 
-----------+----------------------+----------
     Total |        52         22 |        74 

.

[Felipe Weizenmann]

Perhaps the following example will show you where you have gone wrong, and start you in a useful direction.

sysuse auto, clear
label values foreign .
tab foreign
ineqdeco price, by(foreign)
return list
generate gini = .
foreach k in `r(levels)' {
replace gini = r(gini_`k') if foreign==`k'
}
tab gini foreign, missing

. sysuse auto, clear
(1978 automobile data)

. label values foreign .

. tab foreign

Car origin | Freq. Percent Cum.
------------+-----------------------------------
0 | 52 70.27 70.27
1 | 22 29.73 100.00
------------+-----------------------------------
Total | 74 100.00

. ineqdeco price, by(foreign)

Percentile ratios

----------------------------------------------------------
All obs | p90/p10 p90/p50 p10/p50 p75/p25
----------+-----------------------------------------------
| 2.923 2.274 0.778 1.512
----------------------------------------------------------

Generalized Entropy indices GE(a), where a = income difference
sensitivity parameter, and Gini coefficient

----------------------------------------------------------------------
All obs | GE(-1) GE(0) GE(1) GE(2) Gini
----------+-----------------------------------------------------------
| 0.08199 0.08605 0.09557 0.11289 0.23222
----------------------------------------------------------------------

Atkinson indices, A(e), where e > 0 is the inequality aversion parameter

----------------------------------------------
All obs | A(0.5) A(1) A(2)
----------+-----------------------------------
| 0.04450 0.08245 0.14088
----------------------------------------------

Subgroup summary statistics, for each subgroup k = 1,...,K:


-------------------------------------------------------------------------------------
Car |
origin | Popn. share Mean Relative mean Income share log(mean)
----------+--------------------------------------------------------------------------
0 | 0.70270 6072.42308 0.98494 0.69212 8.71151
1 | 0.29730 6384.68182 1.03559 0.30788 8.76166
-------------------------------------------------------------------------------------

Subgroup indices: GE_k(a) and Gini_k

----------------------------------------------------------------------
Car |
origin | GE(-1) GE(0) GE(1) GE(2) Gini
----------+-----------------------------------------------------------
0 | 0.08706 0.09293 0.10534 0.12756 0.23777
1 | 0.06834 0.06892 0.07273 0.08049 0.21108
----------------------------------------------------------------------

Within-group inequality, GE_W(a)

----------------------------------------------------------
All obs | GE(-1) GE(0) GE(1) GE(2)
----------+-----------------------------------------------
| 0.08173 0.08579 0.09530 0.11262
----------------------------------------------------------

Between-group inequality, GE_B(a):

----------------------------------------------------------
All obs | GE(-1) GE(0) GE(1) GE(2)
----------+-----------------------------------------------
| 0.00026 0.00026 0.00027 0.00027
----------------------------------------------------------

Subgroup Atkinson indices, A_k(e)

----------------------------------------------
Car |
origin | A(0.5) A(1) A(2)
----------+-----------------------------------
0 | 0.04848 0.08874 0.14829
1 | 0.03488 0.06660 0.12025
----------------------------------------------

Within-group inequality, A_W(e)

----------------------------------------------
All obs | A(0.5) A(1) A(2)
----------+-----------------------------------
| 0.04429 0.08192 0.13966
----------------------------------------------

Between-group inequality, A_B(e)

----------------------------------------------
All obs | A(0.5) A(1) A(2)
----------+-----------------------------------
| 0.00022 0.00058 0.00142
----------------------------------------------

. return list

scalars:
r(ede2) = 5296.67182806118
r(ede1) = 5656.906729539464
r(edehalf) = 5890.891413030665
r(between_a2) = .0014220371069532
r(between_a1) = .000579863745803
r(between_ahalf) = .0002189045211916
r(within_a2) = .1396603860401734
r(within_a1) = .0819216302593577
r(within_ahalf) = .0442926433378639
r(a2_1) = .120251251326965
r(a1_1) = .0665967017412186
r(ahalf_1) = .0348828885410059
r(a2_0) = .148294201236304
r(a1_0) = .0887386575341225
r(ahalf_0) = .0484784087085215
r(between_ge2) = .0002679535178404
r(between_ge1) = .0002661615119775
r(between_ge0) = .0002644106835199
r(between_gem1) = .0002627002691232
r(within_ge2) = .1126217670888891
r(within_ge1) = .0953009106877201
r(within_ge0) = .0857881439463363
r(within_gem1) = .0817307625025281
r(sumw_1) = 22
r(v_1) = .2972972972972973
r(lambda_1) = 1.035590579611236
r(theta_1) = .3078782804249621
r(lgmean_1) = 8.761656934520458
r(mean_1) = 6384.681818181818
 r(gini_1) = .2110814688824557
r(ge2_1) = .0804869266037308
r(ge1_1) = .072725769905224
r(ge0_1) = .0689179088113295
r(gem1_1) = .0683440877343363
r(sumw_0) = 52
r(v_0) = .7027027027027027
r(lambda_0) = .9849424470875541
r(theta_0) = .692121719575038
r(lgmean_0) = 8.711512993348268
r(mean_0) = 6072.423076923077
r(gini_0) = .2377725910959381
r(ge2_0) = .1275629191851993
r(ge1_0) = .1053430684872671
r(ge0_0) = .0929255511188392
r(gem1_0) = .0870571748199685
r(a2) = .140883820895806
r(a1) = .082453991337858
r(ahalf) = .0445018519991732
r(ge2) = .1128897206067294
r(ge1) = .0955670721996976
r(ge0) = .0860525546298563
r(gem1) = .0819934627716512
r(gini) = .2322248019945887
r(p75p50) = 1.266753220812943
r(p25p50) = .8379107160691102
r(p10p50) = .777988614800759
r(p90p50) = 2.274043743133926
r(p75p25) = 1.511799761620977
r(p90p10) = 2.922978177150192
r(p95) = 13466
r(p90) = 11385
r(p75) = 6342
r(p50) = 5006.5
r(p25) = 4195
r(p10) = 3895
r(p5) = 3748
r(max) = 15906
r(min) = 3291
r(N) = 74
r(sumw) = 74
r(sd) = 2949.495884768919
r(Var) = 8699525.97426879
r(mean) = 6165.256756756757

macros:
 r(levels) : "0 1"

. generate gini = .
(74 missing values generated)

. foreach k in `r(levels)' {
2. replace gini = r(gini_`k') if foreign==`k'
3. }
(52 real changes made)
(22 real changes made)

. tab gini foreign, missing

| Car origin
gini | 0 1 | Total
-----------+----------------------+----------
 .2110815 | 0 22 | 22
.2377726 | 52 0 | 52
-----------+----------------------+----------
Total | 52 22 | 74

.

Thank you so much for this great help!