Hello to all statalist users,
I have a question about how to create a base of individuals that belong to the 1st percentile or 5th percentile or etc from a total base of individuals. Let's say that to describe the percentiles, are the percentiles belonging to the salary variable.
Explaining a little more, suppose we have a base of individuals per year and quarter with the main variable: salary ("salary"). All these individuals pentenecen to any of the percentiles of salary distribution (salary). So, I want to generate a base of only the individuals that belong to the 1st percentile.
I happen to generate a dummy of the individuals that belong to the 1st percentile of salary distribution (salary). But I do not know how to create this variable, do you have any suggestions for it?
Proporciono una base de datos corta, usándola ¿podría darme una sugerencia?
Greetings and thank you very much for the suggestions you can offer.
Alexis Rodas
I have a question about how to create a base of individuals that belong to the 1st percentile or 5th percentile or etc from a total base of individuals. Let's say that to describe the percentiles, are the percentiles belonging to the salary variable.
Explaining a little more, suppose we have a base of individuals per year and quarter with the main variable: salary ("salary"). All these individuals pentenecen to any of the percentiles of salary distribution (salary). So, I want to generate a base of only the individuals that belong to the 1st percentile.
I happen to generate a dummy of the individuals that belong to the 1st percentile of salary distribution (salary). But I do not know how to create this variable, do you have any suggestions for it?
Proporciono una base de datos corta, usándola ¿podría darme una sugerencia?
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(salary id) 0 1 385.43 2 784.14 3 690.34 4 282.05 5 466.36 6 367.69 7 324.61 8 1361.05 9 374.62 10 493.78 11 703.49 12 173.29 13 156.78 14 159.63 15 1013.57 16 1144.06 17 1598.38 18 794.49 19 301.05 20 591.91 21 178.36 22 244.45 23 261.33 24 403.7 25 749.98 26 799.55 27 425.66 28 1843.76 29 934.07 30 941.99 31 869.07 32 605.05 33 1107.17 34 407.3 35 410.82 36 1907.82 37 1236.35 38 398.51 39 512.37 40 847.88 41 1587.29 42 493.93 43 113.86 44 627.84 45 1061.01 46 310.71 47 97.2 48 60 49 80 50 611.56 51 56.93 52 403.19 53 525.04 54 149.32 55 63 56 207.7 57 226.46 58 1063.21 59 766.41 60 229.94 61 579.08 62 97.75 63 368.45 64 151.1 65 125.48 66 241.95 67 156.78 68 434.1 69 168.74 70 96.96 71 132.56 72 65.84 73 166.84 74 218.18 75 62.71 76 133.33 77 166.66 78 416.6 79 167.23 80 245.62 81 175.66 82 627.12 83 281.97 84 245.62 85 393.06 86 389.94 87 308.37 88 2335.64 89 2766.72 90 1115.49 91 684.15 92 1089.42 93 2350.87 94 2533.81 95 722.58 96 807.47 97 1212.98 98 2509.3 99 2956.91 100 end
Greetings and thank you very much for the suggestions you can offer.
Alexis Rodas
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