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    Home / Central Data Catalog / LSMS / TZA_2004_KHDS_V01_M / variable [F22]
lsms

Kagera Health and Development Survey 2004 (Wave 5 Panel)

Tanzania, 2004
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Reference ID
TZA_2004_KHDS_v01_M
DOI
https://doi.org/10.48529/5ayf-re90
Producer(s)
Economic Development Initiatives
Collection(s)
Living Standards Measurement Study (LSMS)
Metadata
DDI/XML JSON
Created on
Mar 23, 2011
Last modified
Jun 16, 2017
Page views
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IF VERY BAD, why was it a very bad year? (s102000q3)

Data file: sec10

Overview

Valid: 316
Invalid: 2902
Type: Discrete
Decimal: 0
Width: 132
Range: 1 - 99
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 LOW CROP PRICES: low income due to low prices from crops myself and/or household I was living in 13
4.1%
2 POOR HARVEST (WEATHER): low income due to poor harvest from agricultural crops due to weather conditions 93
29.4%
3 POOR HARVEST(OTHER): low income due to poor harvest from agricultural crops due to pests and other non weather related circumstances 18
5.7%
4 LIVESTOCK: low income due to loss of livestock due to death or low income from livestock due to weather, disease 0
0%
5 WAGE EMPLOYMENT: low income due to loss of job and/or period of unemployment 17
5.4%
6 OFF-FARM EMPLOYMENT: low income due to collapse of business, or low income from continuing business activities 6
1.9%
7 REMITTANCES: low income due to lower transfers or remittances from individuals 5
1.6%
8 GIFTS AND SUPPORT BY ORGANISATIONS: low income due to withdrawal of support by development organisations 0
0%
9 EVICTION/RESETTLEMENT: loss of house and livelihood due to eviction, resettlement, forced migration 3
0.9%
10 DEATH OF FAMILY MEMBER: low income or asset losses linked to a death, due to illness or other causes 66
20.9%
11 SERIOUS ILLNESS: low income or asset losses linked to serious illness (even if leading to death, but most hardship during illness) 57
18%
12 LOSS OF ASSETS: due to crime, violence, theft, etc 15
4.7%
13 OTHER (SPECIFY) 23
7.3%
99 DK 0
0%
Sysmiss 2902
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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