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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F267]
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
177320
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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
  • Section_13b
  • 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_9b2

Overview

Valid: 8934
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 93
1%
2 Panchthar 0
0%
3 Ilam 153
1.7%
4 Jhapa 147
1.6%
5 Morang 173
1.9%
6 Sunsari 207
2.3%
7 Dhankuta 245
2.7%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 252
2.8%
11 Solukhumbu 150
1.7%
12 Okhaldhunga 94
1.1%
13 Khotang 127
1.4%
14 Udayapur 178
2%
15 Saptari 208
2.3%
16 Siraha 0
0%
17 Dhanusha 156
1.7%
18 Mahottari 105
1.2%
19 Sarlahi 126
1.4%
20 Sindhuli 247
2.8%
21 Ramechhap 0
0%
22 Dolakha 137
1.5%
23 Sindhupalchok 128
1.4%
24 Kabhrepalanchok 155
1.7%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 100
1.1%
29 Rasuwa 0
0%
30 Dhading 255
2.9%
31 Makwanpur 97
1.1%
32 Rautahat 0
0%
33 Bara 102
1.1%
34 Parsa 120
1.3%
35 Chitwan 0
0%
36 Gorkha 80
0.9%
37 Lamjung 83
0.9%
38 Tanahun 114
1.3%
39 Syangja 90
1%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 77
0.9%
44 Parbat 0
0%
45 Baglung 213
2.4%
46 Gulmi 384
4.3%
47 Palpa 296
3.3%
48 Nawalparasi 314
3.5%
49 Rupandehi 331
3.7%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 293
3.3%
54 Rukum 315
3.5%
55 Salyan 0
0%
56 Dang 234
2.6%
57 Banke 187
2.1%
58 Bardiya 0
0%
59 Surkhet 279
3.1%
60 Dailekh 222
2.5%
61 Jajarkot 192
2.1%
62 Dolpa 0
0%
63 Jumla 37
0.4%
64 Kalikot 100
1.1%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 55
0.6%
68 Bajhang 91
1%
69 Achham 252
2.8%
70 Doti 305
3.4%
71 Kailali 333
3.7%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 181
2%
75 Darchula 121
1.4%
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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