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    Home / Central Data Catalog / IMPACT_EVALUATION / KEN_2004_GEHDS_V01_M_V01_A_RUF / variable [F43]
impact_evaluation

Greater Eldoret Health and Development Survey (Round 1) 2004 - Research Use Files

Kenya, 2004
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Reference ID
KEN_2004_GEHDS_v01_M_v01_A_RUF
DOI
https://doi.org/10.48529/6x0c-5y08
Producer(s)
Markus Goldstein and Harsha Thirumurthy
Collection(s)
Impact Evaluation Surveys
Metadata
DDI/XML JSON
Created on
Jul 22, 2011
Last modified
Jul 07, 2016
Page views
451033
Downloads
3448
  • Study Description
  • Data Description
  • Documentation
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  • Data files
  • aghead_a
  • aghead_b
  • aghead_c
  • aghead_d
  • aghead_e
  • aghead_e1_2
  • agspouse_a
  • agspouse_b
  • agspouse_c
  • agspouse_c_2
  • anthrop_a
  • anthrop_b
  • anthrop_c
  • assets
  • assets_I8
  • assets_I12
  • assets_I17
  • assets_II
  • assets_II5
  • assets_II11
  • assets_III
  • assets_III7
  • assets_III13
  • assets_IV
  • assets_V
  • assets_V6
  • assets_V12
  • assets_VI
  • behavior
  • behavior_c5
  • education
  • educexp
  • enterprise
  • food
  • health
  • health_c
  • health_c_I
  • health_c_II
  • health_c_III
  • health_c_IV
  • hh_roster
  • identification
  • income
  • iroster
  • othexp
  • polygamoushh
  • shocks
  • shocks_a3
  • shocks_a7
  • shocks_a11
  • shocks_a15
  • shocks_a19
  • shocks_a24
  • shocks_a27
  • shocks_b30
  • shocks_b33
  • shocks_b36
  • shocks_b40
  • shocks_c44
  • shocks_c49
  • shocks_c53
  • timealloc
  • transfers
  • transfers_a3
  • transfers_a9
  • transfers_a16
  • transfers_b3
  • transfers_d
  • youth

What did do for this work (inb02b)

Data file: income

Overview

Valid: 460
Invalid: 3347
Type: Discrete
Decimal: 0
Width: 2
Range: 1 - 99
Format: Numeric

Questions and instructions

Literal question
What did [NAME] do in this work? What kind of trade, industry or business is it connected with? Occupation Code.
Categories
Value Category Cases
1 Crop farmer 36
7.8%
2 Animal farmer 8
1.7%
3 Housewife 0
0%
4 Trader/merchant/salesperson 16
3.5%
5 Transport worker 29
6.3%
6 Construction worker 24
5.2%
7 Teacher/education professional 67
14.6%
8 Health professional/TBA/trad. Healer 3
0.7%
9 Secretary/clerical 13
2.8%
10 Factory worker 8
1.7%
11 Restaurant/bar/hotel 10
2.2%
12 Skilled trades (carpenter, tailor, etc.) 11
2.4%
13 Preacher/pastor 3
0.7%
14 Village elder 1
0.2%
15 Domestic worker 26
5.7%
16 Civil Servant/Government 54
11.7%
17 Other (specify) 151
32.8%
88 No activity/unemployed 0
0%
99 Don’t Know 0
0%
Sysmiss 3347
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.
Interviewer instructions
Write down the exact description of the job of the individual in block letters. Then find the code for the type of job that most closely fits the description. Write the code number in the column 2b, which is labeled "Occupation Code." For example, suppose that the individual is employed as a truck driver for a company. This means the individual occupation is "Transport worker - code 5." You should write the following:
Descprition: TRUCK DRIVER Occupation Code: 5

** If the individual worked as a wage or salaried employee in more than one job in the past 7 days, then you should begin by asking about the job in which he/she spent the most amount of time in the past 7 days.
Question post text
If more than one job of this type, choose the one that they spent the most time on in the past 12 months.

Description

Universe
All household members 8 years and older who worked as an EMPLOYEE in the past 7 days.
Source of information
Primary male respondent
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