Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F288]
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
177626
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_16

Overview

Valid: 2049
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 21
1%
2 Panchthar 0
0%
3 Ilam 50
2.4%
4 Jhapa 55
2.7%
5 Morang 72
3.5%
6 Sunsari 57
2.8%
7 Dhankuta 26
1.3%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 22
1.1%
11 Solukhumbu 16
0.8%
12 Okhaldhunga 14
0.7%
13 Khotang 51
2.5%
14 Udayapur 38
1.9%
15 Saptari 48
2.3%
16 Siraha 0
0%
17 Dhanusha 47
2.3%
18 Mahottari 64
3.1%
19 Sarlahi 55
2.7%
20 Sindhuli 40
2%
21 Ramechhap 0
0%
22 Dolakha 18
0.9%
23 Sindhupalchok 36
1.8%
24 Kabhrepalanchok 33
1.6%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 25
1.2%
29 Rasuwa 0
0%
30 Dhading 57
2.8%
31 Makwanpur 69
3.4%
32 Rautahat 0
0%
33 Bara 36
1.8%
34 Parsa 26
1.3%
35 Chitwan 0
0%
36 Gorkha 8
0.4%
37 Lamjung 16
0.8%
38 Tanahun 40
2%
39 Syangja 25
1.2%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 9
0.4%
44 Parbat 0
0%
45 Baglung 22
1.1%
46 Gulmi 59
2.9%
47 Palpa 32
1.6%
48 Nawalparasi 70
3.4%
49 Rupandehi 58
2.8%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 47
2.3%
54 Rukum 52
2.5%
55 Salyan 0
0%
56 Dang 77
3.8%
57 Banke 73
3.6%
58 Bardiya 0
0%
59 Surkhet 55
2.7%
60 Dailekh 63
3.1%
61 Jajarkot 43
2.1%
62 Dolpa 0
0%
63 Jumla 7
0.3%
64 Kalikot 36
1.8%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 21
1%
68 Bajhang 55
2.7%
69 Achham 49
2.4%
70 Doti 37
1.8%
71 Kailali 78
3.8%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 27
1.3%
75 Darchula 14
0.7%
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