Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F261]
agricultural-surveys

Household Risk and Vulnerability Survey 2016-2018

Nepal, 2016 - 2018
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Reference ID
NPL_2016-2018_HRVS_v01_EN_M_v01_A_OCS
Producer(s)
The World Bank
Collections
Agricultural Surveys
Metadata
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Created on
Oct 06, 2020
Last modified
Nov 08, 2022
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Place of residence (s08q04)

Data file: Section_8

Overview

Valid: 300
Invalid: 3826
Type: Discrete
Decimal: 2
Start: 99
End: 103
Width: 5
Range: 1 - 97
Format: Numeric

Questions and instructions

Question pretext
For those working in agriculture or no-agriculture sectors on wage or salary basis.
Literal question
8.4. Where? (job localtion)
Categories
Value Category Cases
1 Taplejung 0
0%
2 Panchthar 0
0%
3 Ilam 1
0.3%
4 Jhapa 0
0%
5 Morang 3
1%
6 Sunsari 1
0.3%
7 Dhankuta 4
1.3%
8 Tehrathum 0
0%
9 Sankhuwasabha 3
1%
10 Bhojpur 0
0%
11 Solukhumbu 7
2.3%
12 Okhaldhunga 2
0.7%
13 Khotang 2
0.7%
14 Udayapur 2
0.7%
15 Saptari 0
0%
16 Siraha 0
0%
17 Dhanusha 0
0%
18 Mahottari 1
0.3%
19 Sarlahi 0
0%
20 Sindhuli 4
1.3%
21 Ramechhap 1
0.3%
22 Dolakha 5
1.7%
23 Sindhupalchok 2
0.7%
24 Kabhrepalanchok 1
0.3%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 35
11.7%
28 Nuwakot 5
1.7%
29 Rasuwa 0
0%
30 Dhading 6
2%
31 Makwanpur 0
0%
32 Rautahat 0
0%
33 Bara 0
0%
34 Parsa 2
0.7%
35 Chitwan 0
0%
36 Gorkha 5
1.7%
37 Lamjung 0
0%
38 Tanahun 0
0%
39 Syangja 2
0.7%
40 Kaski 5
1.7%
41 Manang 0
0%
42 Mustang 1
0.3%
43 Myagdi 0
0%
44 Parbat 0
0%
45 Baglung 1
0.3%
46 Gulmi 2
0.7%
47 Palpa 0
0%
48 Nawalparasi 2
0.7%
49 Rupandehi 1
0.3%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 0
0%
54 Rukum 0
0%
55 Salyan 0
0%
56 Dang 0
0%
57 Banke 1
0.3%
58 Bardiya 0
0%
59 Surkhet 0
0%
60 Dailekh 0
0%
61 Jajarkot 0
0%
62 Dolpa 0
0%
63 Jumla 0
0%
64 Kalikot 0
0%
65 Mugu 1
0.3%
66 Humla 0
0%
67 Bajura 0
0%
68 Bajhang 0
0%
69 Achham 1
0.3%
70 Doti 2
0.7%
71 Kailali 7
2.3%
72 Kanchanpur 1
0.3%
73 Dadeldhura 0
0%
74 Baitadi 0
0%
75 Darchula 5
1.7%
76 Other 0
0%
81 India 110
36.7%
82 Bhutan 0
0%
83 China 0
0%
84 Bangladesh 0
0%
85 Hongkong 0
0%
86 Malayasia 21
7%
87 Japan 0
0%
88 Saudi Arabia 14
4.7%
89 Qatar 19
6.3%
90 United Arab Emirates 4
1.3%
91 United Kingdom 1
0.3%
92 United States 0
0%
93 South Korea 1
0.3%
94 Australia 0
0%
95 Israel 0
0%
96 Other 6
2%
97 Other 0
0%
Sysmiss 3826
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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