Login
Login
|
Microdata at FAO
    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F160]
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
177631
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_6a

Overview

Valid: 46863
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 302
0.6%
2 Panchthar 0
0%
3 Ilam 1026
2.2%
4 Jhapa 1651
3.5%
5 Morang 2090
4.5%
6 Sunsari 1351
2.9%
7 Dhankuta 579
1.2%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 641
1.4%
11 Solukhumbu 449
1%
12 Okhaldhunga 446
1%
13 Khotang 711
1.5%
14 Udayapur 920
2%
15 Saptari 1246
2.7%
16 Siraha 0
0%
17 Dhanusha 1463
3.1%
18 Mahottari 1122
2.4%
19 Sarlahi 1611
3.4%
20 Sindhuli 906
1.9%
21 Ramechhap 0
0%
22 Dolakha 581
1.2%
23 Sindhupalchok 1126
2.4%
24 Kabhrepalanchok 1240
2.6%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 885
1.9%
29 Rasuwa 0
0%
30 Dhading 1168
2.5%
31 Makwanpur 1134
2.4%
32 Rautahat 0
0%
33 Bara 1086
2.3%
34 Parsa 799
1.7%
35 Chitwan 0
0%
36 Gorkha 514
1.1%
37 Lamjung 529
1.1%
38 Tanahun 789
1.7%
39 Syangja 612
1.3%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 391
0.8%
44 Parbat 0
0%
45 Baglung 803
1.7%
46 Gulmi 1192
2.5%
47 Palpa 856
1.8%
48 Nawalparasi 2141
4.6%
49 Rupandehi 2311
4.9%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 720
1.5%
54 Rukum 890
1.9%
55 Salyan 0
0%
56 Dang 1379
2.9%
57 Banke 1453
3.1%
58 Bardiya 0
0%
59 Surkhet 1036
2.2%
60 Dailekh 784
1.7%
61 Jajarkot 585
1.2%
62 Dolpa 0
0%
63 Jumla 206
0.4%
64 Kalikot 404
0.9%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 332
0.7%
68 Bajhang 392
0.8%
69 Achham 585
1.2%
70 Doti 451
1%
71 Kailali 2110
4.5%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 481
1%
75 Darchula 384
0.8%
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