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    Home / Central Data Catalog / DIME / KEN_2013-2014_MFNIE_V01_M / variable [F7]
dime

Estimating the Impacts of Microfranchising on Young Women in Nairobi 2013-2015, Baseline, Midline and Endline Surveys

Kenya, 2013 - 2015
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Reference ID
KEN_2013-2014_MFNIE_v01_M
DOI
https://doi.org/10.48529/mccx-9c96
Producer(s)
Pamela Jakiela, Owen Ozier
Collection(s)
Development Impact Evaluation (DIME) Impact Evaluation Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Dec 14, 2018
Last modified
Apr 22, 2019
Page views
33043
Downloads
1278
  • Study Description
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  • gem_baseline_nopii_nov2018release
  • gem_midline_nopii_nov2018release
  • gem_endline_nopii_nov2018release

Item 2: During the last 30 days what were the major health and education expense (e_q524a)

Data file: gem_endline_nopii_nov2018release

Overview

Valid: 62
Invalid: 0
Type: Discrete
Start: 2779
End: 2853
Width: 75
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
0 1
1.6%
Afya 1
1.6%
Buy drugs 1
1.6%
Buying medication 1
1.6%
Buying medicine. 2
3.2%
Childs school fees 1
1.6%
Education 9
14.5%
Education expenses 1
1.6%
Educational expense. 2
3.2%
Elimu 1
1.6%
Fee balance 1
1.6%
For medication 2
3.2%
Health 1
1.6%
Health cost 1
1.6%
Health expenses 2
3.2%
Her mother medicine. 1
1.6%
Her tution fee. 1
1.6%
Hoispital bill for myself 1
1.6%
Hospitak bill 1
1.6%
Hospital 1
1.6%
Hospital bill 2
3.2%
Hospital bill for child 1
1.6%
Hospital bill. 1
1.6%
Kiafya 1
1.6%
Kielimu 1
1.6%
Medical expense 1
1.6%
Medical expense. 1
1.6%
Medical expenses. 1
1.6%
Medical expeses. 1
1.6%
Medication 1
1.6%
Medication for her child. 1
1.6%
Medicine 1
1.6%
Mother's healthcare 1
1.6%
Niece 1
1.6%
Pay school fee 1
1.6%
School fees 4
6.5%
School fees for child 1
1.6%
School fees. 1
1.6%
Schoolfees 1
1.6%
Tuition fee. 1
1.6%
Tution for her child. 1
1.6%
Went to hospital 1
1.6%
Younger brother was ill contributed moneybto help pay for his medical bills 1
1.6%
education 1
1.6%
health 1
1.6%
school fee 1
1.6%
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.
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