Datasets:
Unnamed: 0 int64 | Unnamed..0 int64 | V0001 int64 | V0002 int64 | V0011 int64 | V0300 int64 | V0010 int64 | V6036 int64 | V0601 int64 | V0606 int64 | V6400 int64 | V0645 float64 | V6461 int64 | V6513 int64 | V0653 int64 | cluster int64 | cod_mun int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 5 | 1,400,027 |
2 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 1 | 1,400,027 |
3 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 6 | 1,400,027 |
4 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 8 | 1,400,027 |
5 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 2 | 1,400,027 |
6 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 4 | 1,400,027 |
7 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 3 | 1,400,027 |
8 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 0 | 1,400,027 |
9 | 0 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 32 | 1 | 4 | 2 | 1 | 3,111 | 840 | 40 | 7 | 1,400,027 |
10 | 1 | 14 | 27 | 1,400,027,001,001 | 32,063 | 32,404,390,791,905 | 10 | 1 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
11 | 2 | 14 | 27 | 1,400,027,001,001 | 33,553 | 82,141,663,811,173 | 19 | 2 | 5 | 2 | null | -1 | 0 | 0 | -1 | 1,400,027 |
12 | 3 | 14 | 27 | 1,400,027,001,001 | 33,553 | 82,141,663,811,173 | 9 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
13 | 4 | 14 | 27 | 1,400,027,001,001 | 33,553 | 82,141,663,811,173 | 8 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
14 | 5 | 14 | 27 | 1,400,027,001,001 | 33,553 | 82,141,663,811,173 | 5 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
15 | 6 | 14 | 27 | 1,400,027,001,001 | 33,553 | 82,141,663,811,173 | 43 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
16 | 7 | 14 | 27 | 1,400,027,001,001 | 33,553 | 82,141,663,811,173 | 45 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
17 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 2 | 1,400,027 |
18 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 3 | 1,400,027 |
19 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 5 | 1,400,027 |
20 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 4 | 1,400,027 |
21 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 1 | 1,400,027 |
22 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 6 | 1,400,027 |
23 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 0 | 1,400,027 |
24 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 7 | 1,400,027 |
25 | 8 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 51 | 2 | 1 | 1 | null | 6,121 | 0 | 30 | 8 | 1,400,027 |
26 | 9 | 14 | 27 | 1,400,027,001,001 | 59,796 | 39,530,525,787,656 | 12 | 1 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
27 | 10 | 14 | 27 | 1,400,027,001,001 | 72,594 | 27,362,736,646,511 | 66 | 1 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
28 | 11 | 14 | 27 | 1,400,027,001,001 | 72,594 | 27,362,736,646,511 | 93 | 2 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
29 | 12 | 14 | 27 | 1,400,027,001,001 | 72,594 | 27,362,736,646,511 | 58 | 2 | 1 | 3 | null | -1 | 0 | 0 | -1 | 1,400,027 |
30 | 13 | 14 | 27 | 1,400,027,001,001 | 75,850 | 56,874,307,533,603 | 41 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
31 | 14 | 14 | 27 | 1,400,027,001,001 | 75,850 | 56,874,307,533,603 | 13 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
32 | 15 | 14 | 27 | 1,400,027,001,001 | 75,850 | 56,874,307,533,603 | 15 | 2 | 5 | 2 | null | -1 | 0 | 0 | -1 | 1,400,027 |
33 | 16 | 14 | 27 | 1,400,027,001,001 | 75,850 | 56,874,307,533,603 | 36 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
34 | 17 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 16 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
35 | 18 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 0 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
36 | 19 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 13 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
37 | 20 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 0 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
38 | 21 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 2 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
39 | 22 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 1 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
40 | 23 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 8 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
41 | 24 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 5 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
42 | 25 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 40 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
43 | 26 | 14 | 27 | 1,400,027,001,001 | 76,541 | 74,913,435,757,065 | 49 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
44 | 27 | 14 | 27 | 1,400,027,001,001 | 109,056 | 24,675,590,245,055 | 58 | 2 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
45 | 28 | 14 | 27 | 1,400,027,001,001 | 109,056 | 24,675,590,245,055 | 9 | 2 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
46 | 29 | 14 | 27 | 1,400,027,001,001 | 109,056 | 24,675,590,245,055 | 13 | 2 | 1 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
47 | 30 | 14 | 27 | 1,400,027,001,001 | 109,056 | 24,675,590,245,055 | 77 | 1 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
48 | 31 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 23 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
49 | 32 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 19 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
50 | 33 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 21 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
51 | 34 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 3 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
52 | 35 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 17 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
53 | 36 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 6 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
54 | 37 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 4 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
55 | 38 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 56 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
56 | 39 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 30 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
57 | 40 | 14 | 27 | 1,400,027,001,001 | 144,286 | 66,040,428,840,629 | 10 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
58 | 41 | 14 | 27 | 1,400,027,001,001 | 154,260 | 52,721,106,510,749 | 54 | 1 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
59 | 42 | 14 | 27 | 1,400,027,001,001 | 154,260 | 52,721,106,510,749 | 68 | 1 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
60 | 43 | 14 | 27 | 1,400,027,001,001 | 158,247 | 59,374,560,947,329 | 17 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
61 | 44 | 14 | 27 | 1,400,027,001,001 | 158,247 | 59,374,560,947,329 | 35 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
62 | 45 | 14 | 27 | 1,400,027,001,001 | 158,247 | 59,374,560,947,329 | 1 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
63 | 46 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 4 | 2 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
64 | 47 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 1 | 2 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
65 | 48 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 20 | 2 | 4 | 3 | null | -1 | 0 | 0 | -1 | 1,400,027 |
66 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 8 | 1,400,027 |
67 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 1 | 1,400,027 |
68 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 6 | 1,400,027 |
69 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 5 | 1,400,027 |
70 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 2 | 1,400,027 |
71 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 0 | 1,400,027 |
72 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 4 | 1,400,027 |
73 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 3 | 1,400,027 |
74 | 49 | 14 | 27 | 1,400,027,001,001 | 159,111 | 58,487,504,122,840 | 40 | 1 | 4 | 4 | 1 | 2,341 | 2,900 | 40 | 7 | 1,400,027 |
75 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 8 | 1,400,027 |
76 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 6 | 1,400,027 |
77 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 0 | 1,400,027 |
78 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 1 | 1,400,027 |
79 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 4 | 1,400,027 |
80 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 2 | 1,400,027 |
81 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 3 | 1,400,027 |
82 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 5 | 1,400,027 |
83 | 50 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 28 | 1 | 4 | 4 | 2 | 2,221 | 3,700 | 80 | 7 | 1,400,027 |
84 | 51 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 0 | 2 | 4 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
85 | 52 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 3 | 2 | 1 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
86 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 8 | 1,400,027 |
87 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 1 | 1,400,027 |
88 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 3 | 1,400,027 |
89 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 2 | 1,400,027 |
90 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 0 | 1,400,027 |
91 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 6 | 1,400,027 |
92 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 4 | 1,400,027 |
93 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 5 | 1,400,027 |
94 | 53 | 14 | 27 | 1,400,027,001,001 | 168,890 | 19,404,086,471,535 | 30 | 2 | 4 | 4 | 1 | 2,351 | 1,600 | 40 | 7 | 1,400,027 |
95 | 54 | 14 | 27 | 1,400,027,001,001 | 210,932 | 67,584,345,188,419 | 14 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
96 | 55 | 14 | 27 | 1,400,027,001,001 | 210,932 | 67,584,345,188,419 | 12 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
97 | 56 | 14 | 27 | 1,400,027,001,001 | 210,932 | 67,584,345,188,419 | 16 | 1 | 5 | 2 | null | -1 | 0 | 0 | -1 | 1,400,027 |
98 | 57 | 14 | 27 | 1,400,027,001,001 | 210,932 | 67,584,345,188,419 | 36 | 1 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
99 | 58 | 14 | 27 | 1,400,027,001,001 | 210,932 | 67,584,345,188,419 | 10 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
100 | 59 | 14 | 27 | 1,400,027,001,001 | 210,932 | 67,584,345,188,419 | 37 | 2 | 5 | 1 | null | -1 | 0 | 0 | -1 | 1,400,027 |
🗺️ Base Municipal de Desigualdade Racial (Brasil)
Repositório: atlas-da-saude-mental/Base_Municipal_Desigualdade_Racial
Idioma: Português (pt-BR)
Licença: CC BY 4.0
📘 Descrição
A Base Municipal de Desigualdade Racial reúne microdados socioeconômicos modelados com modelos lineares mistos para estimar disparidades de renda associadas à raça, gênero e escolaridade nos municípios brasileiros.
O conjunto foi construído a partir de microdados de pesquisas como a PNAD Contínua (IBGE) e contém variáveis que permitem avaliar como o efeito de ser mulher negra, homem negro, mulher branca, etc. sobre a renda horária varia entre municípios.
O objetivo central é oferecer um score padronizado de discriminação racial municipal (RDS_Mun), permitindo comparações espaciais e temporais do grau de desigualdade racial no mercado de trabalho brasileiro.
🧩 Estrutura dos dados
1. Base_Municipal_Desigualdade_Racial.csv
| Coluna | Descrição |
|---|---|
cod_mun |
Código do município (IBGE) |
cluster |
Identificador do cluster de amostragem |
ln_renda_horaria |
Logaritmo da renda horária individual |
V6036 |
Idade do indivíduo |
idade_2 |
Idade ao quadrado |
superior, medio, fundamental |
Indicadores binários de escolaridade |
mulher_negra, homem_negro, mulher_branca |
Variáveis dummies de raça e gênero |
negra, mulher |
Dummies básicas de raça e gênero |
faixa_etaria |
Faixa etária categorizada |
cluster, cod_mun |
Fatores hierárquicos utilizados no modelo |
2. Coef_Discriminacao_Racial_Mun.csv
| Coluna | Descrição |
|---|---|
cod_mun |
Código do município (IBGE) |
Efeito_Mulher_Negra |
Coeficiente estimado para o efeito de ser mulher negra |
Efeito_Homem_Negro |
Coeficiente estimado para o efeito de ser homem negro |
RDS_Mun |
Score padronizado de discriminação racial (quanto menor, maior a igualdade) |
⚙️ Metodologia
Modelagem Estatística
O modelo principal ajustado foi um modelo linear misto, com efeitos fixos de raça, gênero e escolaridade, e efeitos aleatórios para clusters amostrais e municípios:
ln(renda_horaria)_ijk = β0 + β1(mulher_negra) + β2(homem_negro) + β3(mulher_branca)
+ β4(educação) + β5(idade) + β6(idade²)
+ u_j + u_k + ε_ijk
u_j: efeito aleatório do cluster amostralu_k: efeito aleatório do municípioε_ijk: erro residual
Cálculo do Score (RDS_Mun)
O score municipal de discriminação racial é derivado da média ponderada dos coeficientes de mulher_negra e homem_negro em cada município, padronizado em z-score:
RDS_Mun = ((β_mulher_negra + β_homem_negro) / 2 - μ) / σ
Valores mais baixos indicam menor desigualdade racial (maior igualdade de rendimentos entre grupos raciais).
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