Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F260]
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
177673
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_7

Overview

Valid: 17444
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 148
0.8%
2 Panchthar 0
0%
3 Ilam 356
2%
4 Jhapa 435
2.5%
5 Morang 620
3.6%
6 Sunsari 555
3.2%
7 Dhankuta 233
1.3%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 258
1.5%
11 Solukhumbu 195
1.1%
12 Okhaldhunga 183
1%
13 Khotang 382
2.2%
14 Udayapur 347
2%
15 Saptari 493
2.8%
16 Siraha 0
0%
17 Dhanusha 391
2.2%
18 Mahottari 312
1.8%
19 Sarlahi 481
2.8%
20 Sindhuli 417
2.4%
21 Ramechhap 0
0%
22 Dolakha 238
1.4%
23 Sindhupalchok 406
2.3%
24 Kabhrepalanchok 425
2.4%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 335
1.9%
29 Rasuwa 0
0%
30 Dhading 437
2.5%
31 Makwanpur 453
2.6%
32 Rautahat 0
0%
33 Bara 372
2.1%
34 Parsa 326
1.9%
35 Chitwan 0
0%
36 Gorkha 178
1%
37 Lamjung 153
0.9%
38 Tanahun 271
1.6%
39 Syangja 221
1.3%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 123
0.7%
44 Parbat 0
0%
45 Baglung 229
1.3%
46 Gulmi 367
2.1%
47 Palpa 232
1.3%
48 Nawalparasi 747
4.3%
49 Rupandehi 884
5.1%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 270
1.5%
54 Rukum 307
1.8%
55 Salyan 0
0%
56 Dang 654
3.7%
57 Banke 560
3.2%
58 Bardiya 0
0%
59 Surkhet 457
2.6%
60 Dailekh 308
1.8%
61 Jajarkot 248
1.4%
62 Dolpa 0
0%
63 Jumla 97
0.6%
64 Kalikot 233
1.3%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 122
0.7%
68 Bajhang 224
1.3%
69 Achham 265
1.5%
70 Doti 199
1.1%
71 Kailali 863
4.9%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 236
1.4%
75 Darchula 198
1.1%
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