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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F258]
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
177679
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  • Study Description
  • Data Dictionary
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  • Data files
  • Section_0
  • Section_1
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  • Section_5
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  • Section_5a
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  • Section_6a
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  • Section_6c
  • Section_6d
  • Section_7
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  • Section_9a1
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  • Section_9a3
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  • Section_9b1
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  • Section_9c
  • Section_9d
  • Section_9e
  • Section_9f
  • Section_10
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  • Section_12a
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  • 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_6c

Overview

Valid: 29034
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 209
0.7%
2 Panchthar 0
0%
3 Ilam 660
2.3%
4 Jhapa 1342
4.6%
5 Morang 1323
4.6%
6 Sunsari 911
3.1%
7 Dhankuta 317
1.1%
8 Tehrathum 0
0%
9 Sankhuwasabha 0
0%
10 Bhojpur 289
1%
11 Solukhumbu 249
0.9%
12 Okhaldhunga 258
0.9%
13 Khotang 413
1.4%
14 Udayapur 495
1.7%
15 Saptari 789
2.7%
16 Siraha 0
0%
17 Dhanusha 953
3.3%
18 Mahottari 772
2.7%
19 Sarlahi 1042
3.6%
20 Sindhuli 479
1.6%
21 Ramechhap 0
0%
22 Dolakha 316
1.1%
23 Sindhupalchok 562
1.9%
24 Kabhrepalanchok 626
2.2%
25 Lalitpur 0
0%
26 Bhaktapur 0
0%
27 Kathmandu 0
0%
28 Nuwakot 545
1.9%
29 Rasuwa 0
0%
30 Dhading 676
2.3%
31 Makwanpur 646
2.2%
32 Rautahat 0
0%
33 Bara 760
2.6%
34 Parsa 571
2%
35 Chitwan 0
0%
36 Gorkha 287
1%
37 Lamjung 331
1.1%
38 Tanahun 550
1.9%
39 Syangja 388
1.3%
40 Kaski 0
0%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 176
0.6%
44 Parbat 0
0%
45 Baglung 357
1.2%
46 Gulmi 560
1.9%
47 Palpa 438
1.5%
48 Nawalparasi 1701
5.9%
49 Rupandehi 1806
6.2%
50 Kapilbastu 0
0%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 332
1.1%
54 Rukum 370
1.3%
55 Salyan 0
0%
56 Dang 985
3.4%
57 Banke 940
3.2%
58 Bardiya 0
0%
59 Surkhet 574
2%
60 Dailekh 341
1.2%
61 Jajarkot 246
0.8%
62 Dolpa 0
0%
63 Jumla 99
0.3%
64 Kalikot 189
0.7%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 172
0.6%
68 Bajhang 264
0.9%
69 Achham 367
1.3%
70 Doti 288
1%
71 Kailali 1476
5.1%
72 Kanchanpur 0
0%
73 Dadeldhura 0
0%
74 Baitadi 344
1.2%
75 Darchula 250
0.9%
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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