Enquête Permanente Auprès des Ménages 1985-1986, Wave 1 Panel

Côte d'Ivoire, 1985 - 1986
Living Standards Measurement Study (LSMS)

Central

Direction de la Statistique

CSV JSON

Name of the CILSS cluster (namclust)

Data file: INSPECT

Overview

Valid: 515

Invalid: 0

Type: Discrete

Width: 24

Range: -

Format: character

Questions and instructions

Categories

Value	Cases
ABENGOUROU	4	0.8%
ABOBO AVOCATIER/PK18 G	1	0.2%
ABOBO BAOULE	2	0.4%
ABOBO DERRIERE RAILS	2	0.4%
ABOBO MATERNIT/FROBEL	2	0.4%
ABOKOUMA	2	0.4%
ABONGOUA	2	0.4%
ABOUD KOUASSIKRO	5	1%
ADJAM	2	0.4%
ADJAM DALLAS	1	0.2%
ADJAM RAILS/NORD EST	2	0.4%
ADZOP	4	0.8%
AGBANIKRO	2	0.4%
AGBAOU	3	0.6%
AGBOVILLE	4	0.8%
AGNIBILKRO	2	0.4%
AHOUANOU	2	0.4%
AKA AOUSOUKRO	2	0.4%
AKAKRO-N'ZIKPRI	2	0.4%
AKANZAKRO	2	0.4%
AKOUP	3	0.6%
ALLUNAMOUENOU	2	0.4%
ANONO/ 2 PLATEAUX ENA	1	0.2%
ANYAMA	4	0.8%
ARRAH	3	0.6%
ASSAL KOUASSIKRO	2	0.4%
ASSOUBA	4	0.8%
ATTCOUB	2	0.4%
ATTCOUB CENTRE	2	0.4%
ATTHOU	6	1.2%
AUTRE ABOBO	2	0.4%
AUTRE ADJAM	2	0.4%
AUTRE MARCORY	3	0.6%
AUTRE TREICHVILLE	4	0.8%
BABRASSO	3	0.6%
BAH-BLAON	3	0.6%
BANGOLO	2	0.4%
BEBOU	4	0.8%
BELLEVILLE KOZOAN	2	0.4%
BIETRY	2	0.4%
BINGERVILLE	3	0.6%
BLODY	1	0.2%
BLOKOSSO/2 PLATEAUX	2	0.4%
BOCANDA	2	0.4%
BOGOUIN I	3	0.6%
BOUAFL	4	0.8%
BOUAK AIR FRANCE 1/2	3	0.6%
BOUAK AIR FRANCE 3	3	0.6%
BOUAK AIR FRANCE I LF	1	0.2%
BOUAK AIR-FRANCE I LF	1	0.2%
BOUAK GARE/DAR ES S2	4	0.8%
BOUAK N'GATTAKRO-KOKO	2	0.4%
BOUAK N'GATTAKRO-NIMB	3	0.6%
BOUAK SOKOURA	5	1%
BOUAK ZONE/DAR ES S2	4	0.8%
BOUNAFLA	2	0.4%
BOUNDIALI	2	0.4%
BOUSSOU	2	0.4%
BRAND-BASSAM	1	0.2%
BNIANKR	4	0.8%
COCODY CENTRE	3	0.6%
CORNICHE-LYCE TECHNIQ	3	0.6%
DABAKALA	1	0.2%
DABOU	2	0.4%
DABOU I	2	0.4%
DAGOBOUA	3	0.6%
DAKOUEPLEU	4	0.8%
DALOA	3	0.6%
DALOA CENTRE III	2	0.4%
DAM	3	0.6%
DAOUKRO	4	0.8%
DIENEDIAN	4	0.8%
DIHOUIN	1	0.2%
DIVO	4	0.8%
DOBIA	2	0.4%
DOUASSO	3	0.6%
DOUEN	2	0.4%
DUKOU	2	0.4%
EHUIKRO	3	0.6%
FERENTELLA	4	0.8%
FERKESSDOUGOU	2	0.4%
GADOUAN	2	0.4%
GAGNOA	6	1.2%
GBAMBIASSO	2	0.4%
GBOKORA	1	0.2%
GODJIBOU	4	0.8%
GOHOUO	3	0.6%
GOMEZAPLEU	2	0.4%
GOUANFLA	4	0.8%
GOULALEU	4	0.8%
GRAND LAHOU	4	0.8%
GRAND-BASSAM	3	0.6%
GUIBROUA	1	0.2%
GUIGLO	4	0.8%
GUINGLO-ZAGNA	2	0.4%
HERMANKONO	2	0.4%
KAGNAMANKO	2	0.4%
KAKUOUA-KIPROUA	3	0.6%
KANAKORO	4	0.8%
KATADJI	4	0.8%
KATIOLA	3	0.6%
KOFFI-BADOUKRO	2	0.4%
KOGBERA	1	0.2%
KORHOGO	2	0.4%
KOUAMFLA	5	1%
KOUMASSI BIDONVILLE	2	0.4%
KOUMASSI CENTRE	3	0.6%
KOUMASSI SGI/KANKOURA	1	0.2%
KOUMASSI SOPIM	2	0.4%
LABEGUEKAHA	2	0.4%
LAKOTA	4	0.8%
LILIYO	1	0.2%
LOKOLO	4	0.8%
LOPOU	1	0.2%
M'BAHIAKRO	2	0.4%
M'BATTO	1	0.2%
MAMA	2	0.4%
MAN	3	0.6%
MANTONGOUIN	2	0.4%
MARCORY ANOUMABO	2	0.4%
MARCORY CHAMPROUX	3	0.6%
MARCORY GFCI/VRIDI	1	0.2%
MARCORY RSIDENTIEL	3	0.6%
MOLONOU	4	0.8%
MORONOU	2	0.4%
N'BAZO	3	0.6%
N'BRAKRO-N'DRANOUAN	2	0.4%
N'DAKRO	2	0.4%
N'DOUCI	2	0.4%
N'GRIBO	1	0.2%
NANGOUNKAHA	2	0.4%
NATIOKOBADARA	2	0.4%
NIAMAYO	4	0.8%
NIANGON/SOGEFIHA	4	0.8%
NIME BELLEVILLE	3	0.6%
NOUVEL OUSROU	2	0.4%
NBO	3	0.6%
NGUPI	4	0.8%
OUEGNINKRO	4	0.8%
OUROUTARA	2	0.4%
PAKOUABO	4	0.8%
PANGBABO	2	0.4%
POKOUKRO	1	0.2%
PORT BOUET/MARCORY	1	0.2%
PORT-BOUET HOPITAL	4	0.8%
PORT-BOUET/MARCORY	1	0.2%
PRISON/ANDOKOUA	2	0.4%
PROSIBLANFLA	3	0.6%
RUBINO	1	0.2%
SAIOUA	2	0.4%
SAKPL	2	0.4%
SALEU	2	0.4%
SAN PDRO	4	0.8%
SATIKAN	4	0.8%
SEBAZON	1	0.2%
SEBOLO	2	0.4%
SEPIKAHA	4	0.8%
SEYDOUGOU	2	0.4%
SIFI	6	1.2%
SIGOUKOU	2	0.4%
SODEPALM-BOUBO	2	0.4%
SOKOURALA	3	0.6%
SOMANA	3	0.6%
SONGON-T	1	0.2%
SORI BOUAFLA	4	0.8%
SGULA	1	0.2%
TANDA	6	1.2%
TANGULAN	1	0.2%
TANHASSO	4	0.8%
TAPGUH	2	0.4%
TCHONKAHA	3	0.6%
TIASSAL	2	0.4%
TIGBA	1	0.2%
TININGBOU	2	0.4%
TOIT ROUGE/KM 18	3	0.6%
TOIT ROUGE/SOGEFIHA	1	0.2%
TOLATANOKRO	1	0.2%
TOUKOUZOU	1	0.2%
TRAFESSO	1	0.2%
TRANSUA	1	0.2%
TREICHVILLE COLE RG	4	0.8%
TREICHVILLE/BIAFRAIS	2	0.4%
YAFFO ATTI	2	0.4%
YAMBLGU	1	0.2%
YAMOUSSOUKRO	5	1%
YEREBODI	1	0.2%
YOBOU N'DOLIKRO	2	0.4%
YOPOUGON ANDONKOUA	3	0.6%
YOPOUGON GARE ET CENTR	4	0.8%
YOPOUGON LEM/ATTCOUB	1	0.2%
YOPOUGON NOUVEAU QUART	1	0.2%
YOPOUGON-SELMER	2	0.4%
YOPOUGON-SICOGI	3	0.6%
ZAGN	4	0.8%
ZAGUINASSO	1	0.2%
ZEL	1	0.2%
ZOUGOUSSOU	4	0.8%
ZOUKOUBOU	4	0.8%
ZAL	4	0.8%
ZGO	1	0.2%
BOU	4	0.8%

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.