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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F227]
agricultural-surveys

Household Risk and Vulnerability Survey 2016-2018

Nepal, 2016 - 2018
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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
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176420
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  • 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 VDC (vdc)

Data file: Section_12b

Overview

Valid: 489
Invalid: 0
Type: Discrete
Start: 8
End: 32
Width: 25
Range: -
Format: character

Questions and instructions

Literal question
Name of VDC
Categories
Value Category Cases
Aaglung 1
0.2%
Aathbisdandagaun 6
1.2%
Aekamba 1
0.2%
Ainselukharka 9
1.8%
Amalachaur 1
0.2%
Amarpatti 1
0.2%
Arthunge 1
0.2%
Badalamji 1
0.2%
Badegau 2
0.4%
Bajhketeria 1
0.2%
Bajrabarahi 2
0.4%
Balaha Kathal 1
0.2%
Balungpani 2
0.4%
BanakhuChor 4
0.8%
Bashaha 4
0.8%
Bejapur 1
0.2%
Belhara 1
0.2%
Belkot 2
0.4%
Bharaul 2
0.4%
Bharta Pundyadevi 4
0.8%
Bhotasipa 5
1%
Bhote Odar 4
0.8%
Bhulke 1
0.2%
Bidyapur 2
0.4%
BijayaKharka 5
1%
Bijayaswori (Chaurjahari) 3
0.6%
Birkot 3
0.6%
Bisalpur 1
0.2%
Boharagaun 1
0.2%
Boniya 4
0.8%
Bramhatola 1
0.2%
Chamunda 1
0.2%
Charpane 4
0.8%
Chaudandi 2
0.4%
Chhinnamasta 1
0.2%
Chilankha 2
0.4%
Chungwang 5
1%
Chyasing Kharka 1
0.2%
Daman 3
0.6%
Danabari 3
0.6%
Dandagaun 2
0.4%
Dandakhali 1
0.2%
Darakh 5
1%
Darbhung 1
0.2%
Darling 5
1%
Darsing Dahathum 1
0.2%
Dattu 2
0.4%
Deulekh 1
0.2%
Devisthan 1
0.2%
Dewantar 2
0.4%
Dharna 5
1%
Dhitung 5
1%
Dhodeni 3
0.6%
Dillichaur 1
0.2%
Dobhan 2
0.4%
Dubidanda 5
1%
Dulegaunda 1
0.2%
Durgauli 1
0.2%
Duwagadhi 2
0.4%
Ekarahiya 1
0.2%
Falate Bhulmu 2
0.4%
Faparbari 2
0.4%
Fatakshila 2
0.4%
Fatepur 1
0.2%
Gaidakot 2
0.4%
Gajurmukhi 2
0.4%
Ganeshthan 1
0.2%
Ganjari 4
0.8%
Gauriganj 1
0.2%
Geta 1
0.2%
Ghetma 12
2.5%
Gumchal 2
0.4%
Gumi 2
0.4%
Gunsakot 1
0.2%
Halwar 2
0.4%
Haraiya 2
0.4%
Hastichour 2
0.4%
Hasuliya 1
0.2%
Hatiya 3
0.6%
Hatpate 1
0.2%
Haunchur 4
0.8%
Hekuli 1
0.2%
Histhan Mandali 3
0.6%
Hunainath 7
1.4%
Hungi 4
0.8%
Isma Rajasthal 3
0.6%
Jalthal 3
0.6%
Jambukandh 2
0.4%
Jarayotar 4
0.8%
Jhapra 4
0.8%
Jogidaha 4
0.8%
Jogmai 2
0.4%
Jugada 1
0.2%
Jungar 3
0.6%
Jyamrung 2
0.4%
Kadambas 2
0.4%
Kalyan 4
0.8%
Kankada 4
0.8%
Katakuti 1
0.2%
Khailad 4
0.8%
Khajurakhurda 4
0.8%
Khalanga 6
1.2%
Khejenim 1
0.2%
Khiratadi 2
0.4%
Khudi 1
0.2%
Khudunabari 1
0.2%
Khuttapiparadhi 2
0.4%
Khyaha 2
0.4%
Kol 2
0.4%
Kurule 4
0.8%
Ladabhir(Mahendra) 1
0.2%
Lakandra 1
0.2%
Lamidada 3
0.6%
Latikoili 2
0.4%
Liwang 4
0.8%
Madhawapur 3
0.6%
Mahadevsthan Mandan 1
0.2%
Mahankal 2
0.4%
Maintara 5
1%
Maisthan 1
0.2%
Makrahar 1
0.2%
Mali 1
0.2%
Manahari 3
0.6%
Mane Bhanjyang 1
0.2%
Manpur 1
0.2%
Musikot 3
0.6%
Nagre Gagarche 3
0.6%
Nandegada 1
0.2%
Narayanpur 1
0.2%
Naubasta 1
0.2%
Naule Katuwal 4
0.8%
NayaBazar 2
0.4%
Neta 1
0.2%
Nipane 1
0.2%
Odanaku 6
1.2%
Padam Pokhari 2
0.4%
Pagretar 4
0.8%
Panchkhal 2
0.4%
Pathariya 3
0.6%
Pawan Nagar 2
0.4%
Phedi 1
0.2%
PhikalBazar 2
0.4%
Pipalchauri 1
0.2%
Pokhari 2
0.4%
Punama 3
0.6%
Rajhena 1
0.2%
Rajpur 5
1%
Rakam Karnali 1
0.2%
Rakhu Bhagawati 6
1.2%
Rampur 4
0.8%
Ramsikhar Jhala 3
0.6%
Rangsi 5
1%
Rapakot 2
0.4%
Resh 4
0.8%
Sadepani 6
1.2%
Sahare 2
0.4%
Salleri 1
0.2%
Sankhupati Chour 3
0.6%
SanoDumma 1
0.2%
Sanusiruwari 2
0.4%
Sanwa 5
1%
Sarmali 1
0.2%
Shantipur 2
0.4%
Shreepur Chhatiwan 3
0.6%
Sinhasain 1
0.2%
Sipali Chilaune 1
0.2%
Sirise 5
1%
Sisahaniya 1
0.2%
Sitapur 2
0.4%
Souraha Pharsatika 2
0.4%
Soyang 2
0.4%
Sreekot 1
0.2%
Sukatiya 4
0.8%
Sungdel 5
1%
Sunwal 1
0.2%
Syalapakha 6
1.2%
Talabang 4
0.8%
Talegaun 4
0.8%
Tapting 1
0.2%
Tarkukot 3
0.6%
Tatopani 2
0.4%
Thoksila 5
1%
Thulo Lumpek 1
0.2%
ThuloSirubari 1
0.2%
Timure 2
0.4%
Turmakhad 1
0.2%
Uku 1
0.2%
Urma 7
1.4%
Valayadanda 1
0.2%
Vedetar 5
1%
Yangpang 9
1.8%
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.
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