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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F209]
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
Page views
178712
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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
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  • Section_12c
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  • Section_13a
  • Section_13b
  • Section_13c
  • Section_13d
  • Section_14a
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  • 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_6b

Overview

Valid: 21218
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 151
0.7%
2 Panchthar 0
0%
3 Ilam 604
2.8%
4 Jhapa 969
4.6%
5 Morang 919
4.3%
6 Sunsari 644
3%
7 Dhankuta 163
0.8%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 277
1.3%
11 Solukhumbu 168
0.8%
12 Okhaldhunga 158
0.7%
13 Khotang 251
1.2%
14 Udayapur 268
1.3%
15 Saptari 607
2.9%
16 Siraha 0
0%
17 Dhanusha 577
2.7%
18 Mahottari 809
3.8%
19 Sarlahi 1078
5.1%
20 Sindhuli 228
1.1%
21 Ramechhap 0
0%
22 Dolakha 132
0.6%
23 Sindhupalchok 593
2.8%
24 Kabhrepalanchok 634
3%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 262
1.2%
29 Rasuwa 0
0%
30 Dhading 409
1.9%
31 Makwanpur 639
3%
32 Rautahat 0
0%
33 Bara 626
3%
34 Parsa 402
1.9%
35 Chitwan 0
0%
36 Gorkha 231
1.1%
37 Lamjung 229
1.1%
38 Tanahun 389
1.8%
39 Syangja 275
1.3%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 163
0.8%
44 Parbat 0
0%
45 Baglung 301
1.4%
46 Gulmi 428
2%
47 Palpa 307
1.4%
48 Nawalparasi 1011
4.8%
49 Rupandehi 1102
5.2%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 275
1.3%
54 Rukum 354
1.7%
55 Salyan 0
0%
56 Dang 593
2.8%
57 Banke 547
2.6%
58 Bardiya 0
0%
59 Surkhet 493
2.3%
60 Dailekh 304
1.4%
61 Jajarkot 233
1.1%
62 Dolpa 0
0%
63 Jumla 120
0.6%
64 Kalikot 174
0.8%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 125
0.6%
68 Bajhang 225
1.1%
69 Achham 240
1.1%
70 Doti 155
0.7%
71 Kailali 839
4%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 301
1.4%
75 Darchula 236
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.
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