Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F178]
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
177642
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_12a

Overview

Valid: 3781
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 34
0.9%
2 Panchthar 0
0%
3 Ilam 66
1.7%
4 Jhapa 57
1.5%
5 Morang 68
1.8%
6 Sunsari 50
1.3%
7 Dhankuta 83
2.2%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 136
3.6%
11 Solukhumbu 32
0.8%
12 Okhaldhunga 47
1.2%
13 Khotang 161
4.3%
14 Udayapur 157
4.2%
15 Saptari 92
2.4%
16 Siraha 0
0%
17 Dhanusha 59
1.6%
18 Mahottari 51
1.3%
19 Sarlahi 63
1.7%
20 Sindhuli 111
2.9%
21 Ramechhap 0
0%
22 Dolakha 66
1.7%
23 Sindhupalchok 127
3.4%
24 Kabhrepalanchok 126
3.3%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 57
1.5%
29 Rasuwa 0
0%
30 Dhading 139
3.7%
31 Makwanpur 116
3.1%
32 Rautahat 0
0%
33 Bara 50
1.3%
34 Parsa 46
1.2%
35 Chitwan 0
0%
36 Gorkha 20
0.5%
37 Lamjung 14
0.4%
38 Tanahun 26
0.7%
39 Syangja 10
0.3%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 31
0.8%
44 Parbat 0
0%
45 Baglung 72
1.9%
46 Gulmi 122
3.2%
47 Palpa 69
1.8%
48 Nawalparasi 81
2.1%
49 Rupandehi 62
1.6%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 94
2.5%
54 Rukum 152
4%
55 Salyan 0
0%
56 Dang 111
2.9%
57 Banke 92
2.4%
58 Bardiya 0
0%
59 Surkhet 137
3.6%
60 Dailekh 146
3.9%
61 Jajarkot 94
2.5%
62 Dolpa 0
0%
63 Jumla 36
1%
64 Kalikot 72
1.9%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 35
0.9%
68 Bajhang 31
0.8%
69 Achham 19
0.5%
70 Doti 18
0.5%
71 Kailali 199
5.3%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 31
0.8%
75 Darchula 13
0.3%
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