Migration Survey 2019
Senegal, 2019
Get Microdata
Reference ID
SEN_2019_MIG_v01_M
Producer(s)
The World Bank, CRES- Consortium for Economic and Social Research
Metadata
Created on
Oct 03, 2025
Last modified
Oct 03, 2025
Page views
68820
Downloads
681
- Data files
-
base
comunautaire_public.dta - Section0_public.dta
- Section1_public.dta
- Section2_public.dta
- Section3_menage_public.dta
- Section3_scolarité_public.dta
- Section4_public.dta
- Section5_menage_public.dta
- Section5_migrant_public.dta
- Section6_menage_public.dta
- Section6_migrant_public.dta
- Section7_public.dta
- Section8_public.dta
- Section9_migrant_potentiel_public.dta
- Section9_migrant_retour_public.dta
Le département du Sénégal dans lequel le migrant est né (p05_09_a)
Data file: Section5_migrant_public.dta
Overview
Valid:
2265
Invalid:
263
Minimum:
11
Maximum:
143
Mean:
59.3222958057395
Standard deviation:
42.6375073567417
Type:
Discrete
Decimal:
0
Start:
120
End:
122
Width:
3
Range:
11 - 143
Format:
Numeric
Questions and instructions
Literal question
Le département du Sénégal dans lequel le migrant est né?
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 11 | DAKAR | 531 |
23.4%
|
| 12 | PIKINE | 83 |
3.7%
|
| 13 | RUFISQUE | 35 |
1.5%
|
| 14 | GUEDIAWAYE | 38 |
1.7%
|
| 21 | BIGNONA | 38 |
1.7%
|
| 22 | OUSSOUYE | 6 |
0.3%
|
| 23 | ZIGUINCHOR | 39 |
1.7%
|
| 31 | BAMBEY | 50 |
2.2%
|
| 32 | DIOURBEL | 68 |
3%
|
| 33 | M’BACKE | 48 |
2.1%
|
| 41 | DAGANA | 15 |
0.7%
|
| 42 | PODOR | 86 |
3.8%
|
| 43 | SAINT LOUIS | 30 |
1.3%
|
| 51 | BAKEL | 44 |
1.9%
|
| 52 | TAMBACOUNDA | 51 |
2.3%
|
| 53 | GOUDIRY | 20 |
0.9%
|
| 54 | KOUPENTOUM | 7 |
0.3%
|
| 61 | KAOLACK | 81 |
3.6%
|
| 62 | NIORO | 16 |
0.7%
|
| 63 | GUINGUINEO | 1 |
0%
|
| 71 | M’BOUR | 32 |
1.4%
|
| 72 | THIES | 71 |
3.1%
|
| 73 | TIVAOUANE | 17 |
0.8%
|
| 81 | KEBEMER | 19 |
0.8%
|
| 82 | LINGUERE | 11 |
0.5%
|
| 83 | LOUGA | 56 |
2.5%
|
| 91 | FATICK | 38 |
1.7%
|
| 92 | FOUNDIOUGNE | 37 |
1.6%
|
| 93 | GOSSAS | 5 |
0.2%
|
| 101 | KOLDA | 54 |
2.4%
|
| 102 | VELINGARA | 63 |
2.8%
|
| 103 | MEDINA YORO FOULAH | 15 |
0.7%
|
| 111 | MATAM | 200 |
8.8%
|
| 112 | KANEL | 230 |
10.2%
|
| 113 | RANEROU | 0 |
0%
|
| 121 | KAFFRINE | 44 |
1.9%
|
| 122 | BIRKELANE | 1 |
0%
|
| 123 | KOUNGHEUL | 4 |
0.2%
|
| 124 | MALEM HODDAR | 0 |
0%
|
| 131 | KEDOUGOU | 20 |
0.9%
|
| 132 | SALEMATA | 3 |
0.1%
|
| 133 | SARAYA | 7 |
0.3%
|
| 141 | SEDHIOU | 14 |
0.6%
|
| 142 | BOUNKILING | 19 |
0.8%
|
| 143 | GOUDOMP | 18 |
0.8%
|
| Sysmiss | 263 |
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.