I have income data for two populations (population id=1 and 2). I have collapsed my data into the form of cross-tabulation because in my research I assume all people in the same cell has exactly the same income. My original data is pasted at the end of this post. I want to calculate income share of each decile in each of the 2 populations separately. I have tried pshare (by Ben Jann) and sumdist (By Stephen Jenkins). Both can be installed by "ssc install ...". However, their estimates are slightly different. I was wondering if it is due to my incorrect usage of these commands?
For example, the income share of the top 10% in population with id=1 is 25.35% by pshare but 25.31 by sumdist. I also do not understand why there is an additional row with "." in the first column in the output of sumdist.
Thank you in advance!
Code:
. pshare estimate income [iw=freq], over(id) n(10) gini
(variance estimation not supported with iweights)
Percentile shares (proportion) Number of obs = 40
1: id = 1
2: id = 2
--------------------------------------------------------------
income | Coef. Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
1 |
0-10 | .0193008 . . .
10-20 | .034384 . . .
20-30 | .0535935 . . .
30-40 | .0679086 . . .
40-50 | .0808105 . . .
50-60 | .0935073 . . .
60-70 | .1067746 . . .
70-80 | .12858 . . .
80-90 | .1615961 . . .
90-100 | .2535447 . . .
-------------+------------------------------------------------
2 |
0-10 | .0844804 . . .
10-20 | .087861 . . .
20-30 | .0886734 . . .
30-40 | .0904544 . . .
40-50 | .0927363 . . .
50-60 | .0940319 . . .
60-70 | .0971719 . . .
70-80 | .1013188 . . .
80-90 | .1245144 . . .
90-100 | .1387574 . . .
--------------------------------------------------------------
-------------------------
| Gini
-------------+-----------
1 | .3525345
2 | .0837606
-------------------------
. sumdist income [aw=freq] if id==1, ngps(10)
Distributional summary statistics, 10 quantile groups
---------------------------------------------------------------------------
Quantile |
group | Quantile % of median Share, % L(p), % GL(p)
----------+----------------------------------------------------------------
1 | 15090.00 22.30 1.93 1.93 1510.64
2 | 31181.00 46.07 3.44 5.38 4204.04
3 | 44526.00 65.79 5.37 10.75 8401.91
4 | 53645.00 79.27 6.78 17.52 13700.59
5 | 67677.00 100.00 8.09 25.62 20027.01
6 | 76289.00 112.73 9.36 34.98 27347.58
7 | 85703.00 126.64 10.65 45.63 35676.55
8 | 104176.00 153.93 12.87 58.51 45741.38
9 | 131401.00 194.16 16.18 74.69 58393.76
10 | 25.31 100.00 78183.37
. | 0.00 100.00 78183.37
---------------------------------------------------------------------------
. sumdist income [aw=freq] if id==2, ngps(10)
Distributional summary statistics, 10 quantile groups
---------------------------------------------------------------------------
Quantile |
group | Quantile % of median Share, % L(p), % GL(p)
----------+----------------------------------------------------------------
1 | 66284.00 92.84 11.99 11.99 9144.18
2 | 67528.00 94.59 7.39 19.37 14777.63
3 | 67677.00 94.80 7.08 26.45 20178.05
4 | 70314.00 98.49 8.77 35.22 26866.54
5 | 71393.00 100.00 13.36 48.58 37056.61
6 | 74037.00 103.70 10.45 59.03 45026.36
7 | 74224.00 103.97 5.40 64.43 49145.43
8 | 82858.00 116.06 11.07 75.50 57592.88
9 | 97434.00 136.48 10.66 86.16 65721.22
10 | 13.84 100.00 76281.04
. | 0.00 100.00 76281.04
---------------------------------------------------------------------------Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(income freq id) 58340 46 2 63079 35 2 66056 132 2 66284 175 2 67528 230 2 67677 220 2 67773 88 2 68921 79 2 70314 100 2 70686 196 2 70696 56 2 71393 144 2 71651 123 2 72303 11 2 74037 167 2 74224 153 2 75841 188 2 82858 109 2 97434 230 2 105867 275 2 15090 276 1 17279 0 1 24071 166 1 29035 0 1 31181 110 1 32539 0 1 34466 0 1 38506 0 1 38660 122 1 39778 0 1 39786 0 1 40480 0 1 44162 0 1 44190 0 1 44421 0 1 44526 154 1 45027 0 1 47497 0 1 47751 0 1 48988 0 1 50961 0 1 51042 0 1 51800 78 1 51840 0 1 51950 0 1 52751 0 1 53645 197 1 53694 0 1 55029 0 1 57285 0 1 57428 0 1 57832 0 1 58306 0 1 58340 0 1 59029 0 1 59230 0 1 59411 34 1 59767 0 1 62126 0 1 62644 0 1 63079 0 1 63122 0 1 63521 230 1 66056 0 1 66284 0 1 67528 0 1 67677 12 1 67773 0 1 68921 0 1 70314 0 1 70686 0 1 70696 0 1 71393 0 1 71651 0 1 72303 219 1 74037 0 1 74161 0 1 74224 0 1 75841 0 1 76289 57 1 76468 0 1 78953 0 1 79146 0 1 81072 0 1 81112 0 1 82224 174 1 82370 0 1 82858 0 1 83180 0 1 83960 0 1 85703 101 1 86941 0 1 88456 0 1 88713 0 1 91106 0 1 91921 0 1 93882 0 1 96068 0 1 96173 0 1 96513 131 1 97434 0 1 98657 0 1 98719 0 1 102264 0 1 104176 145 1 104184 0 1 104435 0 1 105847 0 1 105867 0 1 105867 0 1 111956 0 1 112972 0 1 115492 87 1 116767 0 1 118917 0 1 120198 0 1 121313 0 1 121679 0 1 122757 0 1 130627 0 1 131401 189 1 133087 0 1 134584 0 1 135674 0 1 144051 0 1 145649 0 1 147470 0 1 150625 0 1 159560 45 1 205999 230 1 15090 0 2 17279 0 2 24071 0 2 29035 0 2 31181 0 2 32539 0 2 34466 0 2 38506 0 2 38660 0 2 39778 0 2 39786 0 2 40480 0 2 44162 0 2 44190 0 2 44421 0 2 44526 0 2 45027 0 2 47497 0 2 47751 0 2 48988 0 2 50961 0 2 51042 0 2 51800 0 2 51840 0 2 51950 0 2 52751 0 2 53645 0 2 53694 0 2 55029 0 2 57285 0 2 57428 0 2 57832 0 2 58306 0 2 59029 0 2 59230 0 2 59411 0 2 59767 0 2 62126 0 2 62644 0 2 63122 0 2 63521 0 2 74161 0 2 76289 0 2 76468 0 2 78953 0 2 79146 0 2 81072 0 2 81112 0 2 82224 0 2 82370 0 2 83180 0 2 83960 0 2 85703 0 2 86941 0 2 88456 0 2 88713 0 2 91106 0 2 91921 0 2 93882 0 2 96068 0 2 96173 0 2 96513 0 2 98657 0 2 98719 0 2 102264 0 2 104176 0 2 104184 0 2 104435 0 2 105847 0 2 105867 0 2 111956 0 2 112972 0 2 115492 0 2 116767 0 2 118917 0 2 120198 0 2 121313 0 2 121679 0 2 122757 0 2 130627 0 2 131401 0 2 133087 0 2 134584 0 2 135674 0 2 144051 0 2 145649 0 2 147470 0 2 150625 0 2 159560 0 2 205999 0 2 end
0 Response to discrepancies in estimates between sumdist and pshare
Post a Comment