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    Home / Central Data Catalog / IMPACT_EVALUATION / NPL_2013-2016_SSNP-RCT_V01_M / variable [F4]
impact_evaluation

Baseline, Midline, Endline and Follow-up Surveys on Community Challenge Fund, 2013-2016
The Role of Information and Cash Transfers on Early Childhood Development

Nepal, 2013 - 2016
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Reference ID
NPL_2013-2016_SSNP-RCT_v01_M
Producer(s)
Levere, Michael, Gayatri Acharya, Prashant Bharadwaj
Collection(s)
Impact Evaluation Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 27, 2022
Last modified
Nov 22, 2022
Page views
113663
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  • Study Description
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  • cosampling
  • SEC01
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309. Occupation: A. Main occupation (q03_309a)

Data file: SEC03

Overview

Valid: 29537
Invalid: 7408
Minimum: 1
Maximum: 36
Type: Discrete
Decimal: 0
Width: 35
Range: 1 - 36
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Self-agri 4345
11.8%
2 Self-livestock 559
1.5%
3 Agri (other) 923
2.5%
4 Self/other agri 501
1.4%
5 Self-trade/service 821
2.2%
6 Self-small/cottage industry 93
0.3%
7 Self-middle/big industry 22
0.1%
8 Self-construction 60
0.2%
9 Self-transportation 46
0.1%
10 Self-other 163
0.4%
11 Wage-agri 1764
4.8%
12 Wage-construction skill labour 513
1.4%
13 Wage-construction unskilled labour 378
1%
14 Wage-manufacturing skill labour 388
1.1%
15 Wage-manufacturing unskilled labour 182
0.5%
16 Wage-other skilled labour 430
1.2%
17 Wage-other unskilled labour 252
0.7%
18 Labour of transport sector 171
0.5%
19 Goverment employee (NIJAMATI) 35
0.1%
20 Security force 157
0.4%
21 Employee on corporation sector 34
0.1%
22 Employee on financial sector 26
0.1%
23 Employee of education sector 168
0.5%
24 Employee of healthe service 33
0.1%
25 Lawer 10
0%
26 Employee of NGOs/CBOs 20
0.1%
27 Student 6454
17.5%
28 Household duties/child care 6302
17.1%
29 Retired/old age 380
1%
30 Disable, can work 94
0.3%
31 Disable, can not work 402
1.1%
32 Unemployed/seeking work 269
0.7%
33 Small age (too young) 1642
4.4%
35 Foreign employee 1809
4.9%
36 Other 91
0.2%
Sysmiss 7408
20.1%
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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