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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / NPL_2016-2018_HRVS_V01_EN_M_V01_A_OCS / variable [F293]
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
177297
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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

District where born Other (s01q05b)

Data file: Section_1

Overview

Valid: 1908
Invalid: 28407
Type: Discrete
Decimal: 2
Start: 76
End: 80
Width: 5
Range: 1 - 76
Format: Numeric

Questions and instructions

Literal question
1.05b. Where was ...born?
Categories
Value Category Cases
1 Taplejung 67
3.5%
2 Panchthar 55
2.9%
3 Ilam 50
2.6%
4 Jhapa 29
1.5%
5 Morang 29
1.5%
6 Sunsari 22
1.2%
7 Dhankuta 24
1.3%
8 Tehrathum 32
1.7%
9 Sankhuwasabha 25
1.3%
10 Bhojpur 55
2.9%
11 Solukhumbu 8
0.4%
12 Okhaldhunga 36
1.9%
13 Khotang 44
2.3%
14 Udayapur 12
0.6%
15 Saptari 5
0.3%
16 Siraha 27
1.4%
17 Dhanusha 29
1.5%
18 Mahottari 35
1.8%
19 Sarlahi 13
0.7%
20 Sindhuli 11
0.6%
21 Ramechhap 19
1%
22 Dolakha 8
0.4%
23 Sindhupalchok 17
0.9%
24 Kabhrepalanchok 26
1.4%
25 Lalitpur 8
0.4%
26 Bhaktapur 1
0.1%
27 Kathmandu 17
0.9%
28 Nuwakot 6
0.3%
29 Rasuwa 3
0.2%
30 Dhading 22
1.2%
31 Makwanpur 11
0.6%
32 Rautahat 12
0.6%
33 Bara 18
0.9%
34 Parsa 14
0.7%
35 Chitwan 27
1.4%
36 Gorkha 8
0.4%
37 Lamjung 25
1.3%
38 Tanahun 25
1.3%
39 Syangja 91
4.8%
40 Kaski 29
1.5%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 3
0.2%
44 Parbat 41
2.1%
45 Baglung 54
2.8%
46 Gulmi 81
4.2%
47 Palpa 66
3.5%
48 Nawalparasi 23
1.2%
49 Rupandehi 19
1%
50 Kapilbastu 11
0.6%
51 Arghakhanchi 20
1%
52 Pyuthan 26
1.4%
53 Rolpa 10
0.5%
54 Rukum 4
0.2%
55 Salyan 36
1.9%
56 Dang 5
0.3%
57 Banke 5
0.3%
58 Bardiya 6
0.3%
59 Surkhet 27
1.4%
60 Dailekh 45
2.4%
61 Jajarkot 8
0.4%
62 Dolpa 0
0%
63 Jumla 8
0.4%
64 Kalikot 3
0.2%
65 Mugu 3
0.2%
66 Humla 0
0%
67 Bajura 6
0.3%
68 Bajhang 7
0.4%
69 Achham 34
1.8%
70 Doti 35
1.8%
71 Kailali 3
0.2%
72 Kanchanpur 6
0.3%
73 Dadeldhura 2
0.1%
74 Baitadi 6
0.3%
75 Darchula 3
0.2%
76 Born in another country 307
16.1%
Sysmiss 28407
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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