Bénin - Enquête Modulaire Intégrée sur les Conditions de Vie des Ménages 2015
ID de référence | DDI-BEN-INS-EMICoV-2015-V1.0 |
Année | 2015 |
Pays | Bénin |
Producteur(s) | Institut National de la Statique et de l'Analyse Economique - Ministère du Plan et du Développement |
Bailleur(s) | Budget National - - Appui logistique et financier |
Collection(s) | |
Métadonnées |
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Créé le | Dec 15, 2019 |
Dernière modification | Dec 17, 2019 |
Affichage par page | 1053900 |
Téléchargements | 228828 |
- Informations connexes
- Description de l'enquête
- Dictionnaire de données
- Charger les microdonnées
- related_citations
- REET0
- REET1
- REET2
- REMP
- Perception_HH
- RFON1
- RFON2
- RFON2_final
- RFON3
- RFON3A
- RFON4
- INSAE_EMICoV_RDEM_20
15 - INSAE_EMICoVRSEC_201
5 - INSAE_EMICoV_RCFA_cr
edit_2016 - INSAE_EMICoV_RCFBX_e
pargne_2016 - INSAE_EMICoV_RCFC_To
ntine_2016 - INSAE_EMICoV_Consomm
ation_2016 - INSAE_EMICoV_Individ
u_2016 - INSAE_EMICoV_menage_
2016 - RDEP
- RM00
- RM00_2
- RM00X
- RM01A
- RM01B
- RM03
- RM04A
- RM04B
- RM10
- RM11
- RM12
- RM12A
- RM13
- RM13A
- RM14
- RM14A
- RM15
- RM15A
- RM16
- RM16A
- RM17
- RM17A
- RM18
- RM18A
- RM19
- RM19A
- RM20
- RM20A
- RM21
- RM21A
- RM22
- RM23
- RM24
- RM24X
- RMAL
- RMCO
- RMCO_2
- RMEL
- RMFE
- RMPRS
- RSAL1
- RSAL2
- RSAL3
- RSAL4
- RSTA
{NB1_FN38_1} Montant investi il y a 5 ans dans la parcelle (Milliers Fcfa)
(NB1_FN38_1)
Fichier: RFON1
Fichier: RFON1
Aperçu
Type:
Discrète Format: numeric Largeur: 8 Décimales: 0 Intervalle: -7-999990 | Enregistrements valides: 16451 Invalide: 209200 Minimum: -7 Maximum: 999990 |
Catégories
Valeur | Catégorie | Enregistrements | |
---|---|---|---|
-7 | NSP | 2401 | ![]() |
0 | Rien | 6136 | ![]() |
1 | 15 | ![]() | |
2 | 21 | ![]() | |
3 | 10 | ![]() | |
4 | 11 | ![]() | |
5 | 86 | ![]() | |
6 | 18 | ![]() | |
7 | 31 | ![]() | |
8 | 41 | ![]() | |
9 | 10 | ![]() | |
10 | 262 | ![]() | |
11 | 12 | ![]() | |
12 | 75 | ![]() | |
13 | 21 | ![]() | |
14 | 35 | ![]() | |
15 | 217 | ![]() | |
16 | 46 | ![]() | |
17 | 20 | ![]() | |
18 | 37 | ![]() | |
19 | 4 | ![]() | |
20 | 462 | ![]() | |
21 | 12 | ![]() | |
22 | 32 | ![]() | |
23 | 34 | ![]() | |
24 | 26 | ![]() | |
25 | 211 | ![]() | |
26 | 18 | ![]() | |
27 | 25 | ![]() | |
28 | 57 | ![]() | |
29 | 5 | ![]() | |
30 | 453 | ![]() | |
31 | 6 | ![]() | |
32 | 37 | ![]() | |
33 | 28 | ![]() | |
34 | 34 | ![]() | |
35 | 164 | ![]() | |
36 | 36 | ![]() | |
37 | 11 | ![]() | |
38 | 46 | ![]() | |
39 | 3 | ![]() | |
40 | 381 | ![]() | |
41 | 1 | ![]() | |
42 | 30 | ![]() | |
43 | 14 | ![]() | |
44 | 9 | ![]() | |
45 | 257 | ![]() | |
46 | 23 | ![]() | |
47 | 8 | ![]() | |
48 | 41 | ![]() | |
49 | 8 | ![]() | |
50 | 523 | ![]() | |
51 | 2 | ![]() | |
52 | 6 | ![]() | |
53 | 6 | ![]() | |
54 | 18 | ![]() | |
55 | 73 | ![]() | |
56 | 42 | ![]() | |
57 | 8 | ![]() | |
58 | 20 | ![]() | |
59 | 3 | ![]() | |
60 | 404 | ![]() | |
62 | 5 | ![]() | |
63 | 6 | ![]() | |
64 | 11 | ![]() | |
65 | 73 | ![]() | |
66 | 2 | ![]() | |
67 | 17 | ![]() | |
68 | 4 | ![]() | |
69 | 2 | ![]() | |
70 | 197 | ![]() | |
71 | 1 | ![]() | |
72 | 8 | ![]() | |
73 | 1 | ![]() | |
74 | 4 | ![]() | |
75 | 79 | ![]() | |
76 | 6 | ![]() | |
77 | 9 | ![]() | |
78 | 8 | ![]() | |
79 | 5 | ![]() | |
80 | 279 | ![]() | |
81 | 1 | ![]() | |
82 | 1 | ![]() | |
83 | 2 | ![]() | |
84 | 5 | ![]() | |
85 | 30 | ![]() | |
86 | 6 | ![]() | |
87 | 8 | ![]() | |
88 | 6 | ![]() | |
89 | 6 | ![]() | |
90 | 110 | ![]() | |
91 | 1 | ![]() | |
92 | 1 | ![]() | |
94 | 3 | ![]() | |
95 | 15 | ![]() | |
96 | 4 | ![]() | |
98 | 3 | ![]() | |
99 | 2 | ![]() | |
100 | 505 | ![]() | |
101 | 1 | ![]() | |
102 | 3 | ![]() | |
103 | 2 | ![]() | |
104 | 3 | ![]() | |
105 | 5 | ![]() | |
106 | 1 | ![]() | |
108 | 3 | ![]() | |
109 | 1 | ![]() | |
110 | 28 | ![]() | |
111 | 1 | ![]() | |
112 | 5 | ![]() | |
113 | 1 | ![]() | |
114 | 1 | ![]() | |
115 | 7 | ![]() | |
120 | 204 | ![]() | |
122 | 4 | ![]() | |
123 | 3 | ![]() | |
125 | 14 | ![]() | |
129 | 1 | ![]() | |
130 | 39 | ![]() | |
132 | 1 | ![]() | |
133 | 1 | ![]() | |
135 | 2 | ![]() | |
138 | 1 | ![]() | |
139 | 1 | ![]() | |
140 | 31 | ![]() | |
141 | 2 | ![]() | |
144 | 4 | ![]() | |
145 | 9 | ![]() | |
146 | 1 | ![]() | |
148 | 1 | ![]() | |
150 | 196 | ![]() | |
152 | 1 | ![]() | |
153 | 1 | ![]() | |
154 | 5 | ![]() | |
156 | 1 | ![]() | |
160 | 24 | ![]() | |
162 | 3 | ![]() | |
163 | 1 | ![]() | |
164 | 2 | ![]() | |
165 | 2 | ![]() | |
166 | 2 | ![]() | |
167 | 1 | ![]() | |
170 | 8 | ![]() | |
172 | 1 | ![]() | |
173 | 2 | ![]() | |
175 | 2 | ![]() | |
176 | 1 | ![]() | |
180 | 39 | ![]() | |
185 | 2 | ![]() | |
190 | 8 | ![]() | |
195 | 1 | ![]() | |
199 | 2 | ![]() | |
200 | 261 | ![]() | |
204 | 1 | ![]() | |
205 | 2 | ![]() | |
207 | 1 | ![]() | |
208 | 3 | ![]() | |
209 | 2 | ![]() | |
210 | 3 | ![]() | |
215 | 1 | ![]() | |
217 | 1 | ![]() | |
220 | 11 | ![]() | |
224 | 1 | ![]() | |
226 | 1 | ![]() | |
228 | 1 | ![]() | |
230 | 13 | ![]() | |
234 | 1 | ![]() | |
235 | 2 | ![]() | |
236 | 1 | ![]() | |
238 | 1 | ![]() | |
240 | 20 | ![]() | |
245 | 3 | ![]() | |
248 | 1 | ![]() | |
250 | 76 | ![]() | |
255 | 1 | ![]() | |
260 | 4 | ![]() | |
263 | 2 | ![]() | |
270 | 4 | ![]() | |
274 | 1 | ![]() | |
276 | 2 | ![]() | |
280 | 9 | ![]() | |
285 | 1 | ![]() | |
288 | 1 | ![]() | |
300 | 125 | ![]() | |
302 | 1 | ![]() | |
303 | 1 | ![]() | |
308 | 1 | ![]() | |
309 | 1 | ![]() | |
310 | 1 | ![]() | |
312 | 3 | ![]() | |
314 | 1 | ![]() | |
315 | 3 | ![]() | |
318 | 1 | ![]() | |
320 | 7 | ![]() | |
322 | 1 | ![]() | |
323 | 1 | ![]() | |
325 | 1 | ![]() | |
326 | 1 | ![]() | |
330 | 3 | ![]() | |
340 | 6 | ![]() | |
345 | 1 | ![]() | |
350 | 40 | ![]() | |
360 | 16 | ![]() | |
367 | 1 | ![]() | |
370 | 2 | ![]() | |
379 | 1 | ![]() | |
380 | 4 | ![]() | |
384 | 1 | ![]() | |
385 | 1 | ![]() | |
396 | 1 | ![]() | |
400 | 46 | ![]() | |
410 | 3 | ![]() | |
420 | 1 | ![]() | |
430 | 3 | ![]() | |
440 | 1 | ![]() | |
450 | 15 | ![]() | |
455 | 1 | ![]() | |
471 | 1 | ![]() | |
475 | 1 | ![]() | |
480 | 2 | ![]() | |
485 | 1 | ![]() | |
500 | 77 | ![]() | |
503 | 1 | ![]() | |
511 | 1 | ![]() | |
512 | 1 | ![]() | |
535 | 1 | ![]() | |
540 | 2 | ![]() | |
543 | 1 | ![]() | |
550 | 5 | ![]() | |
560 | 2 | ![]() | |
570 | 2 | ![]() | |
578 | 1 | ![]() | |
600 | 37 | ![]() | |
650 | 2 | ![]() | |
660 | 1 | ![]() | |
675 | 1 | ![]() | |
685 | 1 | ![]() | |
700 | 25 | ![]() | |
720 | 1 | ![]() | |
726 | 1 | ![]() | |
728 | 1 | ![]() | |
750 | 5 | ![]() | |
765 | 1 | ![]() | |
780 | 1 | ![]() | |
800 | 43 | ![]() | |
825 | 1 | ![]() | |
850 | 2 | ![]() | |
900 | 11 | ![]() | |
1000 | 38 | ![]() | |
1050 | 1 | ![]() | |
1100 | 1 | ![]() | |
1120 | 2 | ![]() | |
1190 | 1 | ![]() | |
1200 | 6 | ![]() | |
1300 | 1 | ![]() | |
1321 | 1 | ![]() | |
1400 | 1 | ![]() | |
1460 | 1 | ![]() | |
1500 | 16 | ![]() | |
1700 | 1 | ![]() | |
1750 | 1 | ![]() | |
1765 | 1 | ![]() | |
1800 | 1 | ![]() | |
2000 | 17 | ![]() | |
2200 | 2 | ![]() | |
2300 | 1 | ![]() | |
2500 | 5 | ![]() | |
2800 | 1 | ![]() | |
3000 | 12 | ![]() | |
3500 | 2 | ![]() | |
3550 | 1 | ![]() | |
4000 | 6 | ![]() | |
4500 | 1 | ![]() | |
5000 | 16 | ![]() | |
5700 | 1 | ![]() | |
6000 | 3 | ![]() | |
6753 | 1 | ![]() | |
6789 | 1 | ![]() | |
6900 | 1 | ![]() | |
7000 | 3 | ![]() | |
7500 | 1 | ![]() | |
8000 | 6 | ![]() | |
9000 | 2 | ![]() | |
10000 | 23 | ![]() | |
12000 | 8 | ![]() | |
12500 | 2 | ![]() | |
12750 | 1 | ![]() | |
13250 | 1 | ![]() | |
14000 | 3 | ![]() | |
15000 | 3 | ![]() | |
16000 | 2 | ![]() | |
17000 | 2 | ![]() | |
18000 | 3 | ![]() | |
19000 | 3 | ![]() | |
20000 | 14 | ![]() | |
21000 | 1 | ![]() | |
22000 | 2 | ![]() | |
25000 | 2 | ![]() | |
27000 | 3 | ![]() | |
28000 | 1 | ![]() | |
30000 | 9 | ![]() | |
35000 | 2 | ![]() | |
40000 | 6 | ![]() | |
44000 | 1 | ![]() | |
45000 | 2 | ![]() | |
46000 | 2 | ![]() | |
50000 | 13 | ![]() | |
55000 | 2 | ![]() | |
57500 | 1 | ![]() | |
60000 | 7 | ![]() | |
67000 | 1 | ![]() | |
70000 | 3 | ![]() | |
70850 | 1 | ![]() | |
75000 | 1 | ![]() | |
80000 | 4 | ![]() | |
999990 | 90 Millions et plus | 7 | ![]() |
Sysmiss | 209200 |
Avertissement: ces statistiques indiquent le nombre d'enregistrements trouvés dans les fichiers de données, et non des nombres pondérés. Ils ne peuvent pas être interpretés comme étant représentatifs de la population concernée.