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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F213]
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
Documentation in PDF DDI/XML JSON
Created on
Oct 06, 2020
Last modified
Nov 08, 2022
Page views
177513
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  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • Section_0
  • Section_1
  • Section_2
  • Section_3a
  • Section_3b
  • Section_4a
  • Section_4b
  • Section_5
  • Section_0
  • Section_1
  • Section_2
  • Section_3
  • Section_4
  • Section_5a
  • Section_5b
  • Section_6a
  • Section_6b
  • Section_6c
  • Section_6d
  • Section_7
  • Section_8
  • Section_9a1
  • Section_9a2
  • Section_9a3
  • Section_9a4
  • Section_9b1
  • Section_9b2
  • Section_9c
  • Section_9d
  • Section_9e
  • Section_9f
  • Section_10
  • Section_11
  • Section_12a
  • Section_12b
  • Section_12c
  • Section_12d
  • Section_13a
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  • Section_13c
  • Section_13d
  • Section_14a
  • Section_14b
  • Section_14c
  • Section_15a
  • Section_15b
  • Section_17
  • Section_0
  • Section_1
  • Section_2
  • Section_3a
  • Section_3b
  • Section_5
  • Section_0
  • Section_2
  • Section_3
  • Section_4
  • Section_5a
  • Section_5b
  • Section_6a
  • Section_6b
  • Section_6c
  • Section_6d
  • Section_7
  • Section_8
  • Section_9a1
  • Section_9a2
  • Section_9a3
  • Section_9a4
  • Section_9b1
  • Section_9b2
  • Section_9c
  • Section_9d
  • Section_9e
  • Section_9f
  • Section_10
  • Section_11
  • Section_12a
  • Section_12b
  • Section_12c
  • Section_12d
  • Section_13a
  • Section_13b
  • Section_13c
  • Section_13d
  • Section_14a
  • Section_14b
  • Section_14c
  • Section_15a
  • Section_15b
  • Section_16
  • Section_17
  • Section_0
  • Section_1
  • Section_2
  • Section_3a
  • Section_3b
  • Section_4a
  • Section_4b
  • Section_5
  • Section_0
  • Section_1
  • Section_2
  • Section_3
  • Section_4
  • Section_5a
  • Section_5b
  • Section_6a
  • Section_6b
  • Section_6c
  • Section_6d
  • Section_7
  • Section_8
  • Section_9a1
  • Section_9a2
  • Section_9a3
  • Section_9a4
  • Section_9b1
  • Section_9b2
  • Section_9c
  • Section_9d
  • Section_9e
  • Section_9f
  • Section_10
  • Section_11
  • Section_12a
  • Section_12b
  • Section_12c
  • Section_12d
  • Section_13a
  • Section_13b
  • Section_13c
  • Section_13d
  • Section_14a
  • Section_14c
  • Section_15b
  • Section_16
  • Section_17
  • Section_16
  • Section_4a
  • Section_4b
  • Section_1
  • Section_11a
  • Section_14b
  • Section_15a

Name of District (district)

Data file: Section_8

Overview

Valid: 3545
Invalid: 0
Type: Discrete
Decimal: 0
Start: 6
End: 7
Width: 2
Range: 1 - 75
Format: Numeric

Questions and instructions

Literal question
Name of District
Categories
Value Category Cases
1 Taplejung 18
0.5%
2 Panchthar 0
0%
3 Ilam 65
1.8%
4 Jhapa 89
2.5%
5 Morang 217
6.1%
6 Sunsari 149
4.2%
7 Dhankuta 17
0.5%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 23
0.6%
11 Solukhumbu 28
0.8%
12 Okhaldhunga 34
1%
13 Khotang 24
0.7%
14 Udayapur 42
1.2%
15 Saptari 170
4.8%
16 Siraha 0
0%
17 Dhanusha 127
3.6%
18 Mahottari 103
2.9%
19 Sarlahi 135
3.8%
20 Sindhuli 45
1.3%
21 Ramechhap 0
0%
22 Dolakha 35
1%
23 Sindhupalchok 68
1.9%
24 Kabhrepalanchok 60
1.7%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 38
1.1%
29 Rasuwa 0
0%
30 Dhading 75
2.1%
31 Makwanpur 88
2.5%
32 Rautahat 0
0%
33 Bara 147
4.1%
34 Parsa 144
4.1%
35 Chitwan 0
0%
36 Gorkha 28
0.8%
37 Lamjung 35
1%
38 Tanahun 60
1.7%
39 Syangja 31
0.9%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 24
0.7%
44 Parbat 0
0%
45 Baglung 28
0.8%
46 Gulmi 47
1.3%
47 Palpa 31
0.9%
48 Nawalparasi 182
5.1%
49 Rupandehi 291
8.2%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 47
1.3%
54 Rukum 49
1.4%
55 Salyan 0
0%
56 Dang 111
3.1%
57 Banke 127
3.6%
58 Bardiya 0
0%
59 Surkhet 58
1.6%
60 Dailekh 52
1.5%
61 Jajarkot 33
0.9%
62 Dolpa 0
0%
63 Jumla 16
0.5%
64 Kalikot 36
1%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 6
0.2%
68 Bajhang 20
0.6%
69 Achham 19
0.5%
70 Doti 10
0.3%
71 Kailali 231
6.5%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 18
0.5%
75 Darchula 14
0.4%
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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