Home / Central Data Catalog / KEN_2004_GEHDS_V01_M / variable [F96]
central

Greater Eldoret Health and Development Survey (Round 1) 2004

Kenya, 2004
Markus Goldstein and Harsha Thirumurthy
Created on June 01, 2022 Last modified June 01, 2022 Page views 926414 Metadata DDI/XML JSON
CSV JSON

Business - Description (en02a)

Data file: enterprise

Overview

Valid: 511
Invalid: 0
Type: Discrete
Width: 10
Range: -
Format: character

Questions and instructions

Literal question
Business Description. What type of business is this? What kind of trade or occupation is it connected with? Description.
Categories
Value Category Cases
98 2
0.4%
A TRADER 3
0.6%
A/FEEDS 1
0.2%
AGRO-CHEM 1
0.2%
ALCOHOL 1
0.2%
B S VEGES 1
0.2%
B&S BANANA 1
0.2%
B&S BEANS 1
0.2%
B&S CATTLE 3
0.6%
B&S CHICK 1
0.2%
B&S CLOTHS 2
0.4%
B&S COAL 1
0.2%
B&S COWS 2
0.4%
B&S FISH 1
0.2%
B&S GOODS 1
0.2%
B&S MAIZE 11
2.2%
B&S MILK 5
1%
B&S POTATO 1
0.2%
B&S SHOES 1
0.2%
B&S VEG 3
0.6%
B&S VEGES 5
1%
B/S BEANS 1
0.2%
B/S CABBAG 1
0.2%
B/S CATTLE 3
0.6%
B/S CLOTH 1
0.2%
B/S CLOTHS 1
0.2%
B/S EGGS 4
0.8%
B/S FRUITS 3
0.6%
B/S GOODS 1
0.2%
B/S MAIZE 7
1.4%
B/S MILK 3
0.6%
B/S OIL 1
0.2%
B/S SHEEP 1
0.2%
B/S SODAS 1
0.2%
B/S TIMBER 2
0.4%
B/S VEG 3
0.6%
B/S VEGES 10
2%
B/SCHICKEN 1
0.2%
BAKING 1
0.2%
BAR 1
0.2%
BARBER 1
0.2%
BAT CHARGE 1
0.2%
BODABODA 4
0.8%
BOOKSHOP 1
0.2%
BOUTIQUE 2
0.4%
BREAD 1
0.2%
BREWING 26
5.1%
BRICK BUSS 1
0.2%
BRICK MAKE 1
0.2%
BUSAA 1
0.2%
BUTCHER 1
0.2%
BUTCHERY 4
0.8%
B\S CLOTHE 1
0.2%
CAPENTER 1
0.2%
CARPENTER 1
0.2%
CARPENTRY 3
0.6%
CHANGAA 6
1.2%
CHARCOAL 14
2.7%
CHARCOAL B 1
0.2%
CHARCOAL/D 1
0.2%
CHEMIST 1
0.2%
CHICKEN 4
0.8%
CLOTHES 1
0.2%
COM/SEX 1
0.2%
CONSTRUCT 1
0.2%
CONTRACT 1
0.2%
COOKS FOOD 1
0.2%
CUT TIMBER 1
0.2%
DAIRYKIOSK 1
0.2%
DE/TIMBER 1
0.2%
DEALER 1
0.2%
DISTRIBUTO 1
0.2%
DUKA 5
1%
ELECTRICIA 2
0.4%
FOODKIOSK 1
0.2%
GROCERY 2
0.4%
HAIR DRESS 1
0.2%
HARDWARE 4
0.8%
HERBALIST 1
0.2%
HIDE/D 1
0.2%
HOTEL 8
1.6%
KINYOZI 2
0.4%
KIOSK 33
6.5%
LANDLORD 2
0.4%
LIVESTOCK 2
0.4%
LUMBERING 1
0.2%
M WORKSHOP 1
0.2%
M/SELLER 3
0.6%
M/TRADER 2
0.4%
MAIZE TRAD 1
0.2%
MAKE MATS 1
0.2%
MAKE NDAZI 1
0.2%
MANDAZI 1
0.2%
MATATU 2
0.4%
MECHANIC 1
0.2%
MILK 2
0.4%
MILK TRADE 2
0.4%
MILKSELLER 1
0.2%
MILKSUPPLY 1
0.2%
MILKVENDER 1
0.2%
MILKVENDOR 3
0.6%
MITUMBA 5
1%
MK SAMOSA 1
0.2%
NEWSPAPER 1
0.2%
PHOTOGRAPH 1
0.2%
PLAITING 1
0.2%
PLOUGHING 3
0.6%
POSHO MILL 7
1.4%
POSHOMILL 2
0.4%
POSHOMILLS 1
0.2%
R/VENDOR 1
0.2%
RENT HOUSE 2
0.4%
RENTAL HSE 1
0.2%
RETAIL 2
0.4%
RETAILER 1
0.2%
RETAILSHOP 2
0.4%
ROASTMAIZE 1
0.2%
RUNS KIOSK 3
0.6%
S CEREALS 1
0.2%
S KIOSK 1
0.2%
S LIVESTOC 1
0.2%
S MATERIAL 1
0.2%
S PORRIDGE 1
0.2%
S SAMOSA 2
0.4%
S SAMOSAS 1
0.2%
S TIMBER 2
0.4%
S/FRUITS 1
0.2%
S/KAIMATI 1
0.2%
S/MILK 2
0.4%
S/PARAFFIN 1
0.2%
S/SAMOSA 1
0.2%
S/TRADER 1
0.2%
S/VEGES 2
0.4%
SALESMAN 2
0.4%
SALON 1
0.2%
SALONIST 1
0.2%
SALOONIST 1
0.2%
SAMOSASALE 1
0.2%
SCHOOL 1
0.2%
SEL FRUITS 1
0.2%
SEL MOLASE 1
0.2%
SEL SAMOSA 1
0.2%
SELL BEANS 2
0.4%
SELL BUSAA 2
0.4%
SELL CLOTH 6
1.2%
SELL CORN 1
0.2%
SELL DRUGS 1
0.2%
SELL EGGS 3
0.6%
SELL FISH 1
0.2%
SELL FOOD 2
0.4%
SELL FRUIT 2
0.4%
SELL GRAIN 1
0.2%
SELL HENS 1
0.2%
SELL KIOSK 1
0.2%
SELL MAIZE 20
3.9%
SELL MATS 1
0.2%
SELL MILK 3
0.6%
SELL ROPES 1
0.2%
SELL SAMSA 1
0.2%
SELL SHOES 1
0.2%
SELL SOAP 1
0.2%
SELL VEG 3
0.6%
SELL VEGES 21
4.1%
SELL VEGS 2
0.4%
SELLER 2
0.4%
SELLING 2
0.4%
SELLS MILK 1
0.2%
SELLSAMOSA 1
0.2%
SELLSNACKS 1
0.2%
SEWING 1
0.2%
SHEEP TRAD 1
0.2%
SHOE MAKER 1
0.2%
SHOE REPAI 1
0.2%
SHOEPOLISH 1
0.2%
SHOP 14
2.7%
SHOPKEEPER 10
2%
SLL TIMBER 1
0.2%
TAILOR 5
1%
TAILORING 3
0.6%
TAXI 1
0.2%
TEA LEAVES 1
0.2%
TIMBER 2
0.4%
TOMATOES 1
0.2%
TRADE COWS 1
0.2%
TRADER 13
2.5%
TRADING 1
0.2%
TRANSPORT 2
0.4%
UTENSILS 1
0.2%
V/SELLER 1
0.2%
V/VENDOR 2
0.4%
VEG SELLER 5
1%
VEG TRADER 1
0.2%
VEG VENDER 13
2.5%
VEG VENDOR 8
1.6%
VENDER 1
0.2%
W/DIGGER 1
0.2%
WATCH TECH 1
0.2%
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.
var_qstn_ivuinstr
Write a description of the business (like duka in town, or restaurant in town, etc.) and an occupation code (like trader/merchant/salesperson, or restaurant/bar/hotel).

Description

Source of information
Either the household head or the spouse, whoever is best able to respond about each business.