Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F180]
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
177812
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_12c

Overview

Valid: 6604
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 43
0.7%
2 Panchthar 0
0%
3 Ilam 156
2.4%
4 Jhapa 300
4.5%
5 Morang 342
5.2%
6 Sunsari 244
3.7%
7 Dhankuta 105
1.6%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 110
1.7%
11 Solukhumbu 47
0.7%
12 Okhaldhunga 63
1%
13 Khotang 139
2.1%
14 Udayapur 133
2%
15 Saptari 175
2.6%
16 Siraha 0
0%
17 Dhanusha 198
3%
18 Mahottari 134
2%
19 Sarlahi 186
2.8%
20 Sindhuli 80
1.2%
21 Ramechhap 0
0%
22 Dolakha 55
0.8%
23 Sindhupalchok 180
2.7%
24 Kabhrepalanchok 207
3.1%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 82
1.2%
29 Rasuwa 0
0%
30 Dhading 104
1.6%
31 Makwanpur 224
3.4%
32 Rautahat 0
0%
33 Bara 115
1.7%
34 Parsa 68
1%
35 Chitwan 0
0%
36 Gorkha 68
1%
37 Lamjung 86
1.3%
38 Tanahun 137
2.1%
39 Syangja 119
1.8%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 71
1.1%
44 Parbat 0
0%
45 Baglung 149
2.3%
46 Gulmi 229
3.5%
47 Palpa 174
2.6%
48 Nawalparasi 313
4.7%
49 Rupandehi 349
5.3%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 31
0.5%
54 Rukum 21
0.3%
55 Salyan 0
0%
56 Dang 251
3.8%
57 Banke 256
3.9%
58 Bardiya 0
0%
59 Surkhet 121
1.8%
60 Dailekh 62
0.9%
61 Jajarkot 11
0.2%
62 Dolpa 0
0%
63 Jumla 22
0.3%
64 Kalikot 21
0.3%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 31
0.5%
68 Bajhang 43
0.7%
69 Achham 74
1.1%
70 Doti 46
0.7%
71 Kailali 328
5%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 53
0.8%
75 Darchula 48
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