Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F174]
agricultural-surveys

Household Risk and Vulnerability Survey 2016-2018

Nepal, 2016 - 2018
Get Microdata
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
177454
Downloads
494
  • 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_9e

Overview

Valid: 5654
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 44
0.8%
2 Panchthar 0
0%
3 Ilam 131
2.3%
4 Jhapa 186
3.3%
5 Morang 221
3.9%
6 Sunsari 147
2.6%
7 Dhankuta 74
1.3%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 87
1.5%
11 Solukhumbu 54
1%
12 Okhaldhunga 59
1%
13 Khotang 101
1.8%
14 Udayapur 109
1.9%
15 Saptari 149
2.6%
16 Siraha 0
0%
17 Dhanusha 160
2.8%
18 Mahottari 131
2.3%
19 Sarlahi 173
3.1%
20 Sindhuli 115
2%
21 Ramechhap 0
0%
22 Dolakha 72
1.3%
23 Sindhupalchok 136
2.4%
24 Kabhrepalanchok 133
2.4%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 110
1.9%
29 Rasuwa 0
0%
30 Dhading 170
3%
31 Makwanpur 139
2.5%
32 Rautahat 0
0%
33 Bara 129
2.3%
34 Parsa 105
1.9%
35 Chitwan 0
0%
36 Gorkha 68
1.2%
37 Lamjung 71
1.3%
38 Tanahun 112
2%
39 Syangja 86
1.5%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 38
0.7%
44 Parbat 0
0%
45 Baglung 85
1.5%
46 Gulmi 124
2.2%
47 Palpa 86
1.5%
48 Nawalparasi 241
4.3%
49 Rupandehi 263
4.7%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 77
1.4%
54 Rukum 87
1.5%
55 Salyan 0
0%
56 Dang 169
3%
57 Banke 165
2.9%
58 Bardiya 0
0%
59 Surkhet 125
2.2%
60 Dailekh 101
1.8%
61 Jajarkot 73
1.3%
62 Dolpa 0
0%
63 Jumla 30
0.5%
64 Kalikot 55
1%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 39
0.7%
68 Bajhang 70
1.2%
69 Achham 92
1.6%
70 Doti 68
1.2%
71 Kailali 255
4.5%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 83
1.5%
75 Darchula 56
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.
Back to Catalog
Food and Agriculture Organization of the United Nations

FOLLOW US ON

  • icon-facebook
  • icon-flickr
  • icon-instagram
  • icon-linkedin
  • icon-rss
  • icon-slideshare
  • icon-soundcloud
  • icon-tiktok
  • icon-tuotiao
  • icon-twitter
  • icon-wechat
  • icon-weibo
  • icon-youtube
  • FAO Organizational Chart
  • Regional Office for AfricaRegional Office for Asia and the PacificRegional Office for Europe and Central AsiaRegional Office for Latin America and the CaribbeanRegional Office for the Near East and North AfricaCountry Offices
  • Jobs
  • |
  • Contact us
  • |
  • Terms and Conditions
  • |
  • Scam Alert
  • |
  • Report Misconduct

Download our App

© FAO 2025