Dear Statalist,
I'm trying to calculate the Gini of counties using the the population of 20+ income groups and the median income of said groups. An extract of the data I'm working on is as follows:
I've tried to find a sollution as to calculate the Gini with the data being shaped the way it is, but being the Stata novice I am I haven't had any luck. However, I believe that I could be able to use the
ginidesc command if I reshape my data the following way:
I.e. if I could reshape my data so that group (income group) becomes a variable 1 if income group is income group 1-19 (pop_1_19 in my original data), 2 if income group is income group 20-39 (pop_20_39 in my original data)etc... population is the value of the variable of pop_xx_xx in my original data for it's corresponding group and median is the median vage of corresponding income group. Any ideas on how I could proceed with the reshaping? Or if there is any way to calculate the gini of each county for each year using the shape of my current data? Thanks in advance.
I'm trying to calculate the Gini of counties using the the population of 20+ income groups and the median income of said groups. An extract of the data I'm working on is as follows:
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float countyid int(year pop_1_19 pop_20_39) double(median_1_19 median_20_39) 1 2015 1004 349 5.8 29.2 1 2016 926 380 5.9 30 1 2017 881 382 5.9 29.2 1 2018 931 381 6.1 29.3 1 2019 933 400 6.5 29.1 2 2015 1068 508 5.4 29.9 2 2016 1031 517 5.4 30.3 2 2017 959 489 6.5 29.1 2 2018 890 557 6.7 29.3 2 2019 860 490 7.1 29.7 3 2015 626 305 6.7 29.2 3 2016 586 292 6.9 29.5 3 2017 534 293 6.6 29.5 3 2018 638 294 7.1 29.8 3 2019 627 289 6.8 29.1 4 2015 143 95 8.2 28.4 4 2016 160 92 8.4 28.7 4 2017 123 88 8.3 27 4 2018 125 85 7.4 27.8 4 2019 134 97 7 30.2 5 2015 408 228 7.2 29.2 5 2016 388 229 6.5 29.9 5 2017 402 219 7 30.8 5 2018 411 209 7.8 28.6 5 2019 387 229 7.5 29.4 6 2015 78 37 7.1 26.7 6 2016 47 41 9.3 31.4 6 2017 55 29 8 30.3 6 2018 60 36 7.5 29.7 6 2019 63 30 8.2 32.2 7 2015 179 87 5.8 28.3 7 2016 159 77 5.6 31.1 7 2017 157 66 5.4 28.9 7 2018 149 71 7.6 29.7 7 2019 139 64 7.9 28.2 8 2015 702 413 7.5 28.9 8 2016 641 422 7.6 29.8 8 2017 588 383 8 29.5 8 2018 591 415 7.6 28.8 8 2019 570 393 7.4 30.3 9 2015 251 139 6.8 30.2 9 2016 248 116 7.3 28.3 9 2017 233 132 8 30.4 9 2018 220 140 7.8 29.2 9 2019 208 149 7.9 29.3 10 2015 533 326 9.1 29.2 10 2016 570 336 9.3 30 10 2017 631 325 9.1 28.5 10 2018 631 325 9.4 27.8 10 2019 551 306 9.6 29.7
ginidesc command if I reshape my data the following way:
Code:
countyid year group population median 1 2015 1 xxx xxx 1 2015 2 xxx xxx 1 2015 3 xxx xxx 1 2015 4 xxx xxx 1 2015 5 xxx xxx 1 2015 6 xxx xxx 1 2015 7 xxx xxx 1 2015 8 xxx xxx 1 2015 9 xxx xxx 1 2015 10 xxx xxx 1 2015 11 xxx xxx 1 2015 12 xxx xxx 1 2015 13 xxx xxx 1 2015 14 xxx xxx 1 2015 15 xxx xxx 1 2015 16 xxx xxx 1 2015 17 xxx xxx 1 2015 18 xxx xxx 1 2015 19 xxx xxx 1 2015 20 xxx xxx 1 2015 21 xxx xxx 1 2015 22 xxx xxx 1 2015 23 xxx xxx 1 2015 24 xxx xxx 1 2015 25 xxx xxx
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