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    Home / Central Data Catalog / NPL_2016-2018_HRVS_V02_M / variable [F310]
central

Household Risk and Vulnerability Survey, Full Panel 2016-2018

Nepal, 2016 - 2018
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Reference ID
NPL_2016-2018_HRVS_v02_M
Producer(s)
The World Bank
Metadata
DDI/XML JSON
Created on
Jan 16, 2021
Last modified
Sep 07, 2022
Page views
108696
Downloads
855
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • Section_0
    (community
    wave1)
  • Section_1
    (community
    wave1)
  • Section_2
    (community
    wave1)
  • Section_3a
    (community
    wave1)
  • Section_3b
    (community
    wave1)
  • Section_4a
    (community
    wave1)
  • Section_4b
    (community
    wave1)
  • Section_5
    (community
    wave1)
  • Section_0 (hh
    wave1)
  • Section_1 (hh
    wave1)
  • Section_2 (hh
    wave1)
  • Section_3 (hh
    wave1)
  • Section_4 (hh
    wave1)
  • Section_5a (hh
    wave1)
  • Section_5b (hh
    wave1)
  • Section_6a (hh
    wave1)
  • Section_6b (hh
    wave1)
  • Section_6c (hh
    wave1)
  • Section_6d (hh
    wave1)
  • Section_7 (hh
    wave1)
  • Section_8 (hh
    wave1)
  • Section_9a1 (hh
    wave1)
  • Section_9a2 (hh
    wave1)
  • Section_9a3 (hh
    wave1)
  • Section_9a4 (hh
    wave1)
  • Section_9b1 (hh
    wave1)
  • Section_9b2 (hh
    wave1)
  • Section_9c (hh
    wave1)
  • Section_9d (hh
    wave1)
  • Section_9e (hh
    wave1)
  • Section_9f (hh
    wave1)
  • Section_10 (hh
    wave1)
  • Section_11 (hh
    wave1)
  • Section_12a (hh
    wave1)
  • Section_12b (hh
    wave1)
  • Section_12c (hh
    wave1)
  • Section_12d (hh
    wave1)
  • Section_13a (hh
    wave1)
  • Section_13b (hh
    wave1)
  • Section_13c (hh
    wave1)
  • Section_13d (hh
    wave1)
  • Section_14a (hh
    wave1)
  • Section_14b (hh
    wave1)
  • Section_14c (hh
    wave1)
  • Section_15a (hh
    wave1)
  • Section_15b (hh
    wave1)
  • Section_16 (hh
    wave1)
  • Section_17 (hh
    wave1)
  • Section_0
    (community
    wave2)
  • Section_1
    (community
    wave2)
  • Section_2
    (community
    wave2)
  • Section_3a
    (community
    wave2)
  • Section_3b
    (community
    wave2)
  • Section_4a
    (community
    wave2)
  • Section_4b
    (community
    wave2)
  • Section_5
    (community
    wave2)
  • Section_0 (hh
    wave2)
  • Section_1 (hh
    wave2)
  • Section_2 (hh
    wave2)
  • Section_3 (hh
    wave2)
  • Section_4 (hh
    wave2)
  • Section_5a (hh
    wave2)
  • Section_5b (hh
    wave2)
  • Section_6a (hh
    wave2)
  • Section_6b (hh
    wave2)
  • Section_6c (hh
    wave2)
  • Section_6d (hh
    wave2)
  • Section_7 (hh
    wave2)
  • Section_8 (hh
    wave2)
  • Section_9a1 (hh
    wave2)
  • Section_9a2 (hh
    wave2)
  • Section_9a3 (hh
    wave2)
  • Section_9a4 (hh
    wave2)
  • Section_9b1 (hh
    wave2)
  • Section_9b2 (hh
    wave2)
  • Section_9c (hh
    wave2)
  • Section_9d (hh
    wave2)
  • Section_9e (hh
    wave2)
  • Section_9f (hh
    wave2)
  • Section_10 (hh
    wave2)
  • Section_11 (hh
    wave2)
  • Section_12a (hh
    wave2)
  • Section_12b (hh
    wave2)
  • Section_12c (hh
    wave2)
  • Section_12d (hh
    wave2)
  • Section_13a (hh
    wave2)
  • Section_13b (hh
    wave2)
  • Section_13c (hh
    wave2)
  • Section_13d (hh
    wave2)
  • Section_14a (hh
    wave2)
  • Section_14b (hh
    wave2)
  • Section_14c (hh
    wave2)
  • Section_15a (hh
    wave2)
  • Section_15b (hh
    wave2)
  • Section_16 (hh
    wave2)
  • Section_17 (hh
    wave2)
  • Section_0
    (community
    wave3)
  • Section_1
    (community
    wave3)
  • Section_2
    (community
    wave3)
  • Section_3a
    (community
    wave3)
  • Section_3b
    (community
    wave3)
  • Section_4a
    (community
    wave3)
  • Section_4b
    (community
    wave3)
  • Section_5
    (community
    wave3)
  • Section_0 (hh
    wave3)
  • Section_1 (hh
    wave3)
  • Section_2 (hh
    wave3)
  • Section_3 (hh
    wave3)
  • Section_4 (hh
    wave3)
  • Section_5a (hh
    wave3)
  • Section_5b (hh
    wave3)
  • Section_6a (hh
    wave3)
  • Section_6b (hh
    wave3)
  • Section_6c (hh
    wave3)
  • Section_6d (hh
    wave3)
  • Section_7 (hh
    wave3)
  • Section_8 (hh
    wave3)
  • Section_9a1 (hh
    wave3)
  • Section_9a2 (hh
    wave3)
  • Section_9a3 (hh
    wave3)
  • Section_9a4 (hh
    wave3)
  • Section_9b1 (hh
    wave3)
  • Section_9b2 (hh
    wave3)
  • Section_9c (hh
    wave3)
  • Section_9d (hh
    wave3)
  • Section_9e (hh
    wave3)
  • Section_9f (hh
    wave3)
  • Section_10 (hh
    wave3)
  • Section_11 (hh
    wave3)
  • Section_11a (hh
    wave3)
  • Section_12a (hh
    wave3)
  • Section_12b (hh
    wave3)
  • Section_12c (hh
    wave3)
  • Section_12d (hh
    wave3)
  • Section_13a (hh
    wave3)
  • Section_13b (hh
    wave3)
  • Section_13c (hh
    wave3)
  • Section_13d (hh
    wave3)
  • Section_14a (hh
    wave3)
  • Section_14b (hh
    wave3)
  • Section_14c (hh
    wave3)
  • Section_15a (hh
    wave3)
  • Section_15b (hh
    wave3)
  • Section_16 (hh
    wave3)
  • Section_17 (hh
    wave3)

Currently living location (s01q06b)

Data file: Section_1 (hh wave1)

Overview

Valid: 958
Invalid: 26641
Type: Discrete
Decimal: 2
Width: 20
Range: 1 - 97
Format: Numeric

Questions and instructions

Literal question
1.6b. Where is ... currently living?
Categories
Value Category Cases
1 Taplejung 1
0.1%
2 Panchthar 0
0%
3 Ilam 2
0.2%
4 Jhapa 3
0.3%
5 Morang 5
0.5%
6 Sunsari 15
1.6%
7 Dhankuta 4
0.4%
8 Tehrathum 1
0.1%
9 Sankhuwasabha 5
0.5%
10 Bhojpur 1
0.1%
11 Solukhumbu 3
0.3%
12 Okhaldhunga 4
0.4%
13 Khotang 1
0.1%
14 Udayapur 8
0.8%
15 Saptari 8
0.8%
16 Siraha 8
0.8%
17 Dhanusha 12
1.3%
18 Mahottari 4
0.4%
19 Sarlahi 3
0.3%
20 Sindhuli 2
0.2%
21 Ramechhap 0
0%
22 Dolakha 2
0.2%
23 Sindhupalchok 3
0.3%
24 Kabhrepalanchok 4
0.4%
25 Lalitpur 1
0.1%
26 Bhaktapur 0
0%
27 Kathmandu 213
22.2%
28 Nuwakot 0
0%
29 Rasuwa 1
0.1%
30 Dhading 12
1.3%
31 Makwanpur 6
0.6%
32 Rautahat 21
2.2%
33 Bara 4
0.4%
34 Parsa 8
0.8%
35 Chitwan 50
5.2%
36 Gorkha 4
0.4%
37 Lamjung 8
0.8%
38 Tanahun 3
0.3%
39 Syangja 4
0.4%
40 Kaski 36
3.8%
41 Manang 2
0.2%
42 Mustang 3
0.3%
43 Myagdi 3
0.3%
44 Parbat 3
0.3%
45 Baglung 9
0.9%
46 Gulmi 14
1.5%
47 Palpa 9
0.9%
48 Nawalparasi 3
0.3%
49 Rupandehi 24
2.5%
50 Kapilbastu 1
0.1%
51 Arghakhanchi 0
0%
52 Pyuthan 0
0%
53 Rolpa 3
0.3%
54 Rukum 0
0%
55 Salyan 1
0.1%
56 Dang 0
0%
57 Banke 0
0%
58 Bardiya 1
0.1%
59 Surkhet 5
0.5%
60 Dailekh 0
0%
61 Jajarkot 0
0%
62 Dolpa 0
0%
63 Jumla 1
0.1%
64 Kalikot 1
0.1%
65 Mugu 0
0%
66 Humla 3
0.3%
67 Bajura 2
0.2%
68 Bajhang 0
0%
69 Achham 0
0%
70 Doti 3
0.3%
71 Kailali 0
0%
72 Kanchanpur 17
1.8%
73 Dadeldhura 1
0.1%
74 Baitadi 0
0%
75 Darchula 4
0.4%
76 Other 0
0%
81 India 181
18.9%
82 Bhutan 0
0%
83 China 0
0%
84 Bangladesh 0
0%
85 Hongkong 1
0.1%
86 Malayasia 44
4.6%
87 Japan 6
0.6%
88 Saudi Arabia 39
4.1%
89 Qatar 56
5.8%
90 United Arab Emirates 16
1.7%
91 United Kingdom 0
0%
92 United States 3
0.3%
93 South Korea 6
0.6%
94 Australia 0
0%
95 Israel 0
0%
96 Other 22
2.3%
97 Other 1
0.1%
Sysmiss 26641
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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